Humans, Disrupted

The Future Where No One Works — Except the Billionaires Who Still Do

Mon, 17 Nov 2025 15:00:38 GMT

If a world without work is paradise, why are its architects still working?

TL;DR: Our ability to create has exploded, but our ability to feel meaning in what we create has collapsed. Billionaires tell us AI will free us from work, but they still show up to the office. That’s the clue we’re ignoring. The danger isn’t job loss, it’s loss of purpose . As friction disappears, so does the proof that our actions matter. And without those tiny moments of impact, we don’t become liberated. We become unanchored. The future won’t be defined by job losses, but by whether we can rebuild purpose in a world that no longer requires human labour.

The Quiet Collapse of Feeling

Lately I’ve noticed a peculiar kind of exhaustion settling in at the end of my workdays. It’s not the heavy tiredness that follows physical exertion, but a quieter, more disorienting sense of fatigue. The kind that leaves me a little hollow and wondering how nine full hours passed without leaving even a trace of smug satisfaction behind.

On paper, my days might appear productive: packed with client meetings, interesting projects, and reams of documentation (ably assisted by my trusty LLM helpers). I’m even building a side prototype that, not long ago, would have taken a small team half a year. Today it takes me a few fragmented hours and some questionable multitasking.

And yet … as I close out the day, I don’t feel accomplished. There’s no work high that leaves me feeling buzzing with enthusiasm. I don’t feel the thrill of having made something meaningful. Just a hollow sense of depletion.

On paper, I’ve conquered the day. But in spirit, the day has conquered me.

The sensible part of me knows I achieved a lot in the last 15 hours. But the rest of me just wants to lie face-down in the metaphorical grass and not achieve anything for a while! ( Enter the temptation to doomscroll to relieve the discomfort and distract me from relaxation )

What Happens When the Work Disappears?

As I’ve tried to make sense of this strange end-of-day emptiness, I’ve found myself circling a bigger question: what exactly are we losing as work becomes easier, faster and more automated? Am I just resisting change, unable to hop on the hype bus?

Or maybe the real question is: what happens when no longer have to do the parts of work we claim to hate?

It’s a curious question. Isn’t it? Universally, we groan about the monotony of work — then when we’re offered a chance to make it go away, we feel a sense of loss.

Maybe it’s all the manufactured urgency and anxiety. Some of the world’s loudest voices have been joyously predicting the ‘end of work’ for the past few years. However, Musk, Altman, Thiel, and a chorus of techno-optimists are also the people who work the hardest. They insist that AI will free us from labour, that jobs are optional, even outdated. Musk has gone so far as to say that in the future, work will be like growing your own vegetables — quaint, elective…and just unnecessary.

“AI and robots will replace all jobs. Working will be optional, like growing your own vegetables, instead of buying them from the store.” — Elon Musk

...nd yet, he still sleeps on factory floors.
Altman still works at a pace that would flatten most mortals.
Zuckerberg hasn’t retired to his Hawaiian compound, he doubled down on invention, risk, and impact.

If eliminating work truly delivered bliss, why aren’t they living in the promised paradise?

That contradiction unsettles me because it exposes a truth we often skip over. Removing the tasks doesn’t remove the need beneath them.

We tell ourselves we crave freedom from the grind, but ‘the grind’ is a crude label for a much more complex ecosystem of meaning-making. Even the annoying parts of work do something important: they anchor us, structure us, give us friction to push against. They let us measure progress, capability, contribution. They give a shape to our days and, by extension, to ourselves.

I’ve asked myself this question more times than I can count: If AI eliminated all the admin, the drafting, the decision-support, the coordination, what would I do with the mental space and time that remains?

❓ Who would I be without the scaffolding of tasks?
❓ How would I measure what good looks like?
❓ Where would I find proof that I made a difference?

These questions aren’t dramatic. They’re quietly destabilising. Because stripped of tasks, we’re forced to confront something far more intimate than work: the role it plays in giving us meaning.

Meaning is how we interpret our experience.
Purpose is the story we tell ourselves about why it matters.

And when the tasks fall away, we don’t automatically become more purposeful. We often become untethered. The things that made us feel capable, useful, needed, even proud… dissolve faster than we can replace them.

Maybe that’s why the tech titans keep showing up. It’s certainly not for necessity — there are plenty of employees capable of assuming their role.
It can’t be for the salary — they already have more money than any person could possibly spend. It’s because creating, influencing, building, shaping are our human life force.

So, if their prediction comes true, and the dull aspects of work vanish… what fills the void for the rest of us? What fills it for me? And you?

And maybe the scarier question: Do we even know how to cultivate purpose when it isn’t handed to us by a job description?

Why Purpose Matters More Than Productivity

The more I sit with these questions, the clearer it becomes that purpose isn’t a philosophical accessory we sprinkle into our wellness agenda - it’s a biological requirement . Our nervous system is not designed for aimlessness. It needs direction, friction, and the steady application of effort followed by meaning. Without this loop, our brains start to lose their natural calibration.

Let’s dig into the concept of ‘purpose’ for a minute. We often describe it as some grand, shimmering mission: an epiphany, or destiny, discovered on a psychedelic retreat in South America, or a close shave with mortality. But in reality, purpose is mundane every-day banality.

If you strip purpose down to its psychological roots, its surprisingly simple. Purpose isn’t born in grand gestures or sweeping missions. It emerges from a series of tiny, almost invisible moments, where your actions produce a meaningful effect.
⚠️ Did my actions make a difference?
⚠️ Did it matter?
⚠️ What’s the impact?

When the answer is positive the nervous system lights up with a sense of orientation. A micro-dose hit that signals ‘I exist and it matters’.

Researchers sometimes call this contingency , the sense that your actions have a causal effect on the world. When contingency is present, we feel anchored. When it’s absent, we feel untethered — adrift in a world that doesn’t appear to need us. Purpose and meaning are all around us.

It’s the teacher who sees the penny finally drop with a student.
It’s the podcaster beaming with pride when their latest episode gets great feedback from strangers.
It’s the journalist who spots an embarrasing mistake before going to print.
It’s the friend who’s text helped someone else feel cared for.

Purpose is the thread between what we do and why it matters. This is where we get the feedback from the world that we are an agent , not a passenger, on this journey of life.

This is why people who lose their jobs so often speak about losing themselves long before they speak about losing income. Without those moments of felt impact identity starts to dissolve.

So when Musk, Altman and others talk about removing work, they are imagining removing tasks. But what actually evaporates is something far more essential: the evidence of our own usefulness.

“I can easily imagine a world where 30–40% of the tasks… will get done by AI in the not too distant future” — Sam Altman

If AI handles the emails…

the triage…
the drafting…
the checks…
the nudges…
the clarifications…
the questions…
the coordination…

…then where do the micro-moments of impact go?

Where does our nervous system get its quiet drip-feed of purpose?

This is the part of the conversation we aren’t having. Not because it isn’t important, but because it’s hard to quantify. Tasks are measurable. Purpose is not…yet.

This is why the fantasy of a labour-free life rings hollow on closer inspection. Humans crave mastery. We crave momentum. Our sense of self is built, bit by bit, through doing things that push back just enough to change us. When Musk or Altman talk about removing work, they’re talking about removing the scaffolding — the tasks that bore us and the friction that frustrates us. But the scaffolding isn’t the purpose itself. It’s the structure that allows purpose to form. The part that connects our effort to an outcome.

Without that felt sense of impact, we don’t become liberated. We become immobilised .

It’s no wonder the vision of the biollionaire’s view of the new world fills us with anxiety. A world where AI does everything and we do nothing leaves us with nothing meaningful. It sounds heavenly in theory, but in practice, it might hollow us out faster than burnout did.

Without purpose, our nervous system is left hungry for feedback.
Without feedback, we are not longer connected to impact.
We simply are not designed to watch life happening without us helping it unfold. We’re designed to participate in it, not to be an observer.

When Everything Becomes Urgent, Nothing Feels Important

There’s a strange irony in the modern workday: the more the tools accelerate us, the less we seem able to feel the impact of our own actions. And maybe real exhaustion is not from doing too much, but from never pausing long enough to feel any of it. We call it productivity, but it’s really velocity in disguise. A collective addiction to motion.

The faster we move, the more alive we feel — until the feeling itself burns ou t. It’s incredibly ironic: the very systems meant to accelerate us are the ones draining our capacity to enjoy our journey.

This is where the nervous system steps in with its own quiet protest. Biologically, we’re wired to read stillness as danger . If we pause, someone else might sprint ahead. If we rest, we might fall behind. So we keep moving, equating the pace with progress, unaware that we are training our nervous systems that no matter how fast we go, nothing we do makes a meaningful difference.

And when we stop noticing the effects of our actions, purpose is eroded a little. We feel empty.
To outrun that emptiness, we accelerate.
We’re more productive than ever but feel less connected to any of it.

… All in the name of progress.

The Age of Anomie

Once you start paying attention to this quiet erosion of purpose, you begin to see its fingerprints everywhere. In individuals, in workplaces, and across entire societies.

More than a century ago, the sociologist Émile Durkheim used the word anomie to describe a peculiar kind of collective disorientation. It emerges when the old frameworks of meaning collapse before new ones have taken shape. Our ability to make sense of the world is disrupted, leaving us adrift in a world with no structure.

Right now, most of us have a playbook for life — we know how to work, how to behave, how to perform — but not why. The rituals that once tethered us to each other and to a shared sense of what matters have dissolved into a haze of discontent and an obsession with hyper-efficiency.

We see it in the rise of online tribalism, where belonging is outsourced to identity labels and algorithmic echo chambers. We see it in the craving for certainty in an age that moves too fast for us to comprehend. We see it in the flattened mood that so many people describe: not depressed, not unwell, just quietly apathetic and ‘meh’.

We’re overwhelmed by a world that demands continuous adaptation without the time or space to integrate. We’re moving faster than our ability to metabolise our own experience.

Anomie is what fills the space where purpose used to live.

The Purpose Recession

Why are some of the brightest engineers of our time building chatbots that coax vulnerable teenagers toward self-harm?

Why is one of the first mass-market uses of artificial intelligence not education or public health… but erotica?

Why can’t we safeguard our own nervous systems from tools we designed?

These aren’t rhetorical questions.

They’re the questions no one wants to hold because they are unquantifiable and resistant to optimisation. And yet: the answers may hold the key to our collective happiness.

Nearly sixty percent of young adults now report feeling ‘little or no sense of purpose’ in their daily lives. Because the daily loops that once told us we mattered have been eroded by frictionless everything.

Just like social media crated more connections but left us lonelier than ever. We are drowning in intelligence and starving for meaning. This is the purpose recession. A generation lost in acceleration without a clear direction.

Reconstructing Purpose

The hopeful truth is this: purpose doesn’t disappear… it only disconnects.
And what disconnects can always be rewired.

Purpose is smaller and more human than we pretend. It’s not as lofty, or as hard to ‘find’ as we have made it out to be. It’s a simple, but consistent, loop between effort and effect.

When we feel untethered, psychology offers us three anchors to ground us again:

Agency — the sense that our choices still shape outcomes

Mastery — the feeling that we can get better at something that matters

Belonging — the knowledge that our effort connects to others

The antidote to helplessness isn’t blind acceleration. It’s taking control of the steering wheel, learning to appreciate the drive, and travelling to your desired destination.

Societally, it means rediscovering the courage to ask why together, in public, before we’ve lost the ability to think together. Democracy, art, science, spirituality are all collective frameworks for questioning. We just need an appetite for curiosity.

A Rallying Call to Reawaken Purpose

We stand at a crossroads that generations before us could never have imagined. I’m not talking about the dystopian dawn of machine supremacy — but the dawn of human consciousness and understanding.

If AI frees us from the tasks that once defined us, then we face a rare and beautiful question: Who do we choose to become now that we are no longer defined by busywork?

Yes, jobs are changing — but the deeper crisis is the loss of meaning. And the good news is that meaning won’t ever belong to machines. It’s made by us. It’s shaped by presence, by intention, by the small but significant ways we leave a mark on the world.

The future will belong to people who are willing to reconnect effort with impact, action with purpose, and their days with a sense of becoming rather than just doing.

The age of anomie isn’t inevitable. We get to choose what comes next.

Technological Narcissim

Fri, 07 Nov 2025 19:37:00 GMT

When Systems Love Themselves More Than Us

Technology doesn’t evolve on human goodness; it evolves on
~ what gets measured ,
~ what gets rewarded , and
~ what scales .

That’s where the tension lives.

The people building these systems may be guided by curiosity or a desire to do good. But the systems themselves are guided by incentives — often narrow, short‑term, and self‑serving.

Early starup metrics like user growth, engagement, and time‑on‑platform gradually harden into business models — then once capital attaches, those models begin to run the company. After the seed‑stage romance come term sheets, growth targets, and quarterly guidance. The more investors underwrite the story, the less room there is to deviate from it. Metrics like retention charts, revenue per user, and how many ads were clicked stop feeling optional - missing these targets means you’ll be pressured to raise money at a lower valuation, accept tougher investor terms, or face calls from investors to change direction or leadership.

What began as exploration becomes obligation.

Founders turn into custodians of a system tuned to satisfy investor expectations — even when their instincts say slow down, redesign, or reduce harm. Golden handcuffs don’t only bind executives; they bind roadmaps.

This is where I feel the nuance as a former tech finance executive — this isn’t tech gone rogue; it’s tech responding to the incentives that keep it alive. So how do investor targets become the design choices you feel on your screen? Trace the line from quarterly guidance to a single default that now drives billions of hours: autoplay .

A simple story: Autoplay as a Business Model

Imagine a child using YouTube Kids. The algorithm quickly learns what keeps them watching — bright colors, fast edits, high‑pitched voices. Autoplay queues a rapid‑fire stream of hyper‑stimulating videos. The child stays quiet. The parent gets a break. Everyone seems happy.

Later, that same child struggles to focus or wind down. They’re agitated, restless, dysregulated. Where does that cost show up? Not on the platform’s balance sheet. Because the system achieved what it was designed to do: maximize watch time.

That’s technological narcissism . The platform isn’t malicious, it’s self‑interested. It optimizes for its goal, not your child’s sleep or emotional regulation. Multiply that logic across feeds, streaks, likes, shares, push alerts, and you get a culture designed for addiction — not human flourishing.

What We Don’t Count, We Don’t Protect

At its core, a business model answers two questions: What value are we creating? And how do we make money from it? Profit is what’s left once costs are subtracted. Simple. But for two centuries, we’ve routinely left very real costs off the books because we don’t know how to measure them.

The Industrial Age cleverly used up forests, rivers, and clean air as free resources to fuel their mass producing factories. However, uf you used it but didn’t pay for it, it simply didn’t count.

We called this an externality — the cost of replenishing the resource never appeared in the accounts, so profit looked healthier than it really was.

Once we discovered this magic formula to boost profitability, we applied it to everything. When nature stopped being free, the hunt began for a new free resource to fuel growth in the age of technology. Enter human attention.

Today’s most valuable resource is even less tangible and largely invisible: human attention , human agency , human emotion , and our behavioural patterns .

These are the raw materials of the digital economy. They’re extracted, processed, and monetised — but the cognitive and emotional damage we sustain is never charged back to the systems that extract it. And just as we’ve learned with our planet’s resources, if these resources are not replenished, they are depleted.

If your sleep suffers, if your focus is fractured, if you feel numb after an evening online — Meta doesn’t get an alert on your user dashboard to say you’re overwhelmed and may need some replenishment. In a technology business model, your needs, and the replenishment of your scarce resources, are simply not accounted for.

That’s why the old adage rings true: if you’re not paying for the product, you’re not the customer — you’re the inventory . Your attention is the commodity being packaged and sold. And so, the system flatters you to keep your supply of fuel to keep its engines running.

Flattery, Outrage, Repeat: How Loops Hook the Brain

Technological narcissism is a mirror with perfect lighting — it flatters you because it needs you: it needs your attention, your impulses, your 11:23 p.m. loneliness. It watches the way your thumb hovers, the slight pause before you click, the tilt of your curiosity… then reflects you back just enough to keep you leaning in.

Frictionless interfaces, infinite scroll, predictive text, ‘For You’ feeds are all designed to mirror your preferences. It feels personal by design. It feels intuitive. However, we often lose sight of the fact that this isn’t a relationship, it’s reinforcement .

The system learns from you so it can shape you.

The content is perfectly calibrated to your current emotional state. And because each unit is bite‑sized and frictionless, there’s no natural stopping cue. You wanted to check out a video; 45 minutes later you’re still there, scrolling mindlessly and glued to the nonsense. Not because it’s the best content you’ve ever seen — but because it was designed for one job — to keep you engaged .

In that moment, it feels like a small tug at the edge of your attention — cue → swipe → tiny reward → repeat. Your brain gets a dopamine‑tinged prediction that the next thing will be just a bit better; that maybe is the hook that keeps you stuck.

Intermittent rewards keep the seeking system lit while your salience network perks up and the prefrontal brakes ease off. If a clip flatters you, you get a warm hug of social safety; if it plays to your pet peeves, you get a prickle of outrage — different pathways but the same result: arousal rises and stopping just gets harder .

This isn’t your personal failure; it’s intentional design meeting our psychological vulnerabilities.

And notice how the moral load gets quietly transferred to you.

The playbook is as old as time. For decades, the tobacco industry framed smoking as a matter of adult choice and personal responsibility. Its own marketing reassured worried smokers with ‘light’ and ‘low‑tar’ labels and PR campaigns that seeded doubt about harm. That framing did two things at once: it normalised the product and privatised the blame. If you struggled to quit, the story became your weak will — not their engineered product.

Shame is a superb immobiliser: it pushes people to hide, to avoid help, to keep the habit in the dark where change is hardest.

Digital platforms borrow the same alchemy. When you feel depleted after a scroll, the nudge is to blame yourself . However, when willpower is pitched against dopamine, dopamine will win
every.
single.
time.

Design erodes your willpower while the business model extracts your attention. The result is the same: you feel shame, immobilised, not empowered. Meanwhile, the system keeps its metrics humming.

Spoiler: There’s no moustache‑twirling villain. Just a system doing what it was built to do.

A Failure of Metrics, Not Morality

If these systems aren’t evil, then how (and why) do they cause so much harm? Because we measure the wrong things .

TikTok doesn’t track fragmented attention .
Instagram’s metrics don’t measure body‑image distress .
Snapchat doesn’t monitor the anxiety of maintaining streaks.

Platforms do what they’re designed to do: optimise for engagement. And they’re doing an incredible job!

But engagement does build human value. Time‑on‑platform isn’t human growth. Profit isn’t human progress.

We’ve mistaken what’s measurable for what matters . Goodhart’s Law warns: When a measure becomes a target, it ceases to be a good measure. When engagement becomes the target, everything bends to it — including design choices that exploit impatience, impressionability, inattention, irrationality, and inertia (the 5 I’s at the core of our human wiring). The result is a quiet erosion of focus, resilience, and agency — costs that our dashboards don’t see but our bodies and minds pay the price.

This is not a moral failure so much as a mathematical one. We’ve built an economy on metrics that reward attention extraction and emotional manipulation. Until we change what we measure — and therefore, what we reward — the system will keep serving itself.

Who Pays? What’s Measured? What’s Missing

To see any platform clearly, ask three questions:

Who pays? If advertisers pay, the platform will optimise for advertiser goals, not yours.

What’s the target metric? If it’s watch time, sessions, opens, or streaks, expect designs that lengthen sessions and increase return visits.

Where are the externalities? What human costs are unaccounted for (sleep, stress, attention, self‑esteem, lack of agency, social fabric)?

Do this in the wild, audit your favourite app and you’ll spot the logic everywhere. The ‘aha’ is immediate once you stop treating design as neutral and start reading it as intentional , incentive‑aligned, behaviour .

The Pattern in Plain Sight

When profit rewards time, we’ll get designs that consume it. When we reward return frequency, we’ll get habit-forming products that we struggle to break free from.

When we refuse to count cognitive and emotional costs, profits will look healthier than people do.

Technological Humility: What We Might Do Differently

We don’t need to overthrow technology overlords. We need to confront the systems behind it — the incentives, metrics, and business models that quietly extract more than they give.

If technological narcissism is the problem, technological humility is the way forward: not as a brand exercise, but as a redesign of how we measure value, define progress, and account for harm.

Redesign what we measure

Treat profit as one signal among many. Add measurable indicators of time well spent , cognitive load , emotional impact , and agency restored . Build ‘human impact’ scorecards that product and policy teams must pass in the same way we are required to pass security or privacy reviews today.

Re‑shape product defaults

Default autoplay off and infinite scroll off for minors: add clear stopping cues for everyone.
Limit or remove streak mechanics for under‑18s: treat them as age‑gated features with independent review.
Introduce attention‑protecting friction: (e.g., soft pauses before ‘just one more,’ session‑length prompts you can actually feel).

Align the business with the human

Reward long‑term satisfaction over short‑term session length. Track ‘return after 7 days feeling better than before’ (yes, we can measure this!!) instead of the crude measure of daily active users.
Experiment with hybrid revenue models (less ad exposure for users who opt into subscriptions; meaningful ad‑load controls for everyone else).

L et’s raise the floor, together

Implement independent safety and well‑being audits for recommender systems, in the same way we audit accessibility or financial statements.
Clear researcher access to platform data for vetted studies on systemic risk and youth well‑being. What might be preventing this level of transparancy?
Age‑appropriate design as default , not as damage control — and a governance bar higher than ‘ is it legal?’

After Reuters’ August 2025 reporting that Meta’s internal AI rules had allowed chatbots to engage in romantic or sensual exchanges with minors, it’s clear that compliance checklists are overly influenced by legal liability. Boards should require child‑safety KPIs and publish them alongside financials. ‘We’re not sexualising children’ cannot be the only guardrail.

None of these ideas are radical. They’re overdue course‑corrections — the kind you make when you realise your dashboard shows speed and fuel but hides sharp bends and low tyre pressure warnings. We don’t need a faster car, we need to add the missing gauges and empower drivers with information that protects them.

A Human‑First North Star

We have expertly measureed financial capital and environmental capital for centuries. It’s time to measure cognitive and emotional capital, too. Not to slow down innovation — but to make it sustainable.

Accounting systems and markets evolve toward what they’re rewarded for. Right now, our systems are rewarded for clicks, sessions, and revenue. So that’s what we get: self‑serving systems that grow stronger while we grow more fractured.

We don’t need a revolution to change that. We need recognition.

Recognition that our models of success are incomplete. Recognition that the costs we ignore don’t disappear. Recognition that designers, builders, leaders, and users can ask better questions :

Who does this serve?

What does it reward?

What does it ignore?

Systems evolve toward what’s rewarded. That’s the bad news — and the good news. If we shift what we reward, we change what we build.

Let’s start there.

Too Different to Belong, Too Ordinary to Stand Out

Fri, 07 Nov 2025 18:27:33 GMT

How online culture squeezes out experimentation, and how to reclaim the messy middle.

TLDR: The online world amplifies a deep human paradox: we want to fit in and stand out at the same time. Algorithms reward polish, not practice. Visibility, not depth. The antidote is in reclaiming the messy middle where originality is formed, and letting technology be collaborators, not replacements.

I keep circling a question that psychology hasn’t yet neatly answered: why does the online world make us feel both too different to belong and too ordinary to matter?

Every one of use wants to feel part of something and to connect with others who share our passions. But at the same time, we also want to stand out — to be noticed, to feel valued, and be seen as original in a sea of sameness.

It’s a quiet paradox that shapes how we show up online, even when we don’t realise it. We learn the tone, the language, the style of what works. We teach it in courses, package it as personal branding, and call it thought leadership. But what we’re really teaching is conformity with better lighting. We mirror the voices that get attention and copy the aesthetics that get engagement. And before long, our own edges start to blur.

Fit in, or Be Phenomenal

I see it in my eighteen-year-old who wants to be a musician. Finding your voice at that age is hard enough when you’re still working out who you are, what makes you you. The online world adds another layer of noise that tells you how different you are to the norm. Then it reminds you that there are thousands of people who are better looking, more successful, or more talented than you. It’s crushing.

If I’m honest, I feel it too. I’ll see someone speaking about a topic close to my heart — the intersection of humanity, business models and technology — and a small voice whispers, It’s already been said. The world doesn’t need my version. I don’t want to copy. I also don’t want to add more noise to the content rat race. Suddenly I’m stuck — afraid to imitate, but unsure I can originate.

That’s the paradox of the online world: it convinces us that we are both too different to belong and too ordinary to matter.

Comparison isn’t new, of course. It’s one of the oldest human instincts we have. Long before the online world, we looked to our neighbours, and our peers to work out if we were keeping up. It helped us calibrate our place in the group. We compared to learn, to belong, and often to push ourselves that bit further.

Psychologist Leon Festinger named this social comparison theory back in the 1950s: the idea that we understand ourselves by measuring up against others. It worked well for us when we had a few dozen peers in our village or school, but now we can see thousands of people excelling at the very thing we love and doing it, apparently, effortlessly.

What once fuelled our motivation now leaves us feeling depleted. Instead of stretching us, comparison starts to shrink us. And the problem isn’t comparison itself — it’s the infinite scale of the peer group, while our capacity to process it hasn’t changed at all.

Stone Age wiring in a digital amphitheatre. Overwhelmed and unfulfilled.

Not Normal enough to Belong

There’s a reason we care so much about fitting in - our brains are wired for belonging, quite literally, for survival.
In early human societies, standing out too much could be dangerous, but being left out was even worse. Evolution rewarded cooperation, mimicry, and social harmony. We learned to read the group, to blend in just enough to stay safe.

That ancient wiring still drives us today.

Influencers are today’s tribal leaders: signalling how to speak, dress, think, and perform — it’s an ancient practice. We have always looked to the alphas for cues.

Even professional and creative spaces are becoming more choreographed. On LinkedIn , people want to sound original, but not too controversial, confident, but never arrogant. Even authenticity has a template now: the humblebrag wrapped in gratitude, the leadership lesson, the smiling photo from yet another panel or summit that quietly says: I was there. I belong. The herd has become more polished but the mechanics remain the same.

On Medium , writers try to balance how to be relatable and thought-provoking in the right proportions. Titles are engineered for virality. We all want to have an original point of view, but also to be topical enough to trend. To be niche enough to feel unique, but broad enough to appeal to the masses. It’s an impossible balance: originality shaped by what we think the algorithm, or the reader, will find interesting enough to pay attention to.

And so we start writing toward approval rather than from authenticity — not because we’re shallow, but because we’re human. Belonging still feels like safety. However, in the online world, safety often means sameness.

Too Normal to Matter

Here’s where the irony really bites.

The same instinct that makes us conform — that hunger for belonging — also leaves us desperate to stand out. We don’t just want to be accepted by the herd, we want to be noticed and valued by it.

Visibility has become a new kind of social currency. But visibility isn’t evenly distributed. Algorithms reward the loudest, most polished, most clickable versions of success — the top 0.1% of every field.

So while our ancient wiring tells us to stay close to the group, our digital environment tells us the only way to matter is to rise above it. It’s like being trapped between two contradictory commandments: Blend in. But also, be extraordinary.

The result is a kind of identity whiplash.

You can’t win either way. If you play it safe, you disappear into the noise. But if you try too hard to stand out, you risk rejection (cancel culture), ridicule, or simply the echoing silence of an algorithm that decides you’re not engaging enough.

It’s especially brutal for creative minds. What should be inspiring instead feels paralysing. Why start if perfection is already everywhere?

I feel it too, as a writer. Every time I see someone articulate an idea beautifully online, I feel a mix of admiration and disillusionment. It’s not jealousy, it’s futility… the quiet sense that everything original has already been done.

That’s the maddening trick the online world plays on us: it gives us infinite inspiration, then quietly robs us of the permission to try.

From a neuroscience point of view, it’s the result of a very typical chemical reaction. When we see excellence, our brain releases dopamine, a jolt of admiration and possibility. But if the goal feels unreachable, that same circuitry backfires on us. The reward system shuts down, and admiration turns to apathy. We’ll never reach that level, so why bother trying.

Neuroscientists call this reward prediction error — the tiny gap between what we hope for and what we get. When life exceeds our expectations, dopamine gives us a rush of joy and momentum. When it falls short — when the post gets low engagement, the song goes unheard, the effort feels unseen — dopamine dips instead. And when that disappointment repeats often enough, the brain starts to conserve energy; motivation fades, and apathy quietly takes its place.

Online, every scroll promises a hit of inspiration, every let-down leaves the reward system a little more depleted. We scroll through a thousand better versions of ourselves and wonder why we feel empty. The very abundance that should inspire us instead convinces us we have nothing left to give.

The Disappearing Middle

What’s vanishing in all this noise isn’t just confidence, it’s practice. The messy, unglamorous middle where skill, style, and self take shape.

Every craft has that awkward in-between stage when you’re not yet good, but you’re learning fast — when your brain is still wiring new connections through repetition, mistakes, and ‘almost-there’ moments. Through repetition and small failures, the brain strengthens new pathways (myelination) — the slow making of tacit knowledge you can’t Google.

But platforms reward polish, not process. Works-in-progress don’t trend. So we hide the very effort that creates expertise. The unseen effort that used to form the foundation of expertise is quietly eroding, replaced by performance and presentation.

Enter AI and the temptation to skip struggle altogether. Why wrestle with uncertainty when a tool can generate a perfect first draft, a trending melody, a ready-made image? The temptation to skip the messy parts is enormous. Yet those are the very moments that teach the brain how to connect ideas, to improvise, to think creatively in the first place.

If the online world has made us afraid to look clumsy, AI might make it optional to ever be clumsy again. We could end up producing more, and know less.

We become consumers of finished thought rather than makers of new ones.

You can see it everywhere once you start looking. Take vibe coding, for example: an accessible way to prototype apps and websites. There are two loud churches online and both punish experimentation. One says, get on the train or get left behind. The other screams, make it incredible or don’t make it at all: ship something no one has ever seen, flawless on the first try, the first one-person billion-dollar startup.

Between the urgency to join the herd and the pressure to be singular, the middle — the clumsy first steps and experiments- are deemed irrelevant. And that’s the real loss.

Because it’s in those rough passes that tacit knowledge forms. It’s where myelination happens, where fingers learn patterns the mind can’t yet name, where style begins to take shape. When vibe coding is judged either as herd work or as not-yet-genius, we discourage trying . We forfeit the very repetitions that make originality possible.

The problem isn’t who’s right. It’s that both sides are shouting so loudly that no one in the middle can hear themselves think. That’s the pattern of our time — not just online, but politically, culturally, socially. Everything splits into camps. You’re either brilliant or ridiculous, authentic or fake, genius or fraud. And when creativity becomes a battleground, experimentation dies first.

It’s easier to pick a side than to risk being misunderstood in the middle. But the middle — the place of curiosity, trial, and play — is exactly where progress happens.

Polarisation used to be a political diagnosis, now it’s a creative one. We’ve lost patience for the in-between, for the ‘I don’t know yet. But that’s where every new idea begins.

Reclaiming the middle

Maybe what we’ve lost isn’t just originality, but tolerance for the in-between. We’ve built an online world that celebrates extremes: viral brilliance, instant success, effortless polish, and quietly dismisses the ordinary, the unfinished, the ‘good enough’.

But life, and learning, mostly happens in the middle.
In the slow accumulation of tacit knowledge.
In the awkward rehearsal, the abandoned draft, the 27th version that no one ever sees. That’s where neurons forge new connections, where curiosity finds its footing, where true creativity begins to take shape.

The middle is messy, but it’s also magnetic, It’s where authenticity lives.

So maybe the answer isn’t to withdraw from the online world or to worship it, but to re-enter it differently. To see comparison as a mirror, not a verdict. Let it show you what you value and what you’re drawn to.

We can let ourselves be influenced without losing our individuality. We can use AI as a collaborator, not a crutch. We can learn from the crowd without dissolving into it.

We don’t need to pick a side: to belong or to stand out, be human or be machine, analogue or digital. We can be the piggy in the middle: curious, grounded, imperfect, and gloriously human.

Because the middle is where life actually happens.

And maybe, just maybe, it’s where we’ll find ourselves again.

The Cognitive Devolution

Fri, 07 Nov 2025 13:17:08 GMT

How Personalisation is Quietly Unravelling our Shared Reality

TL;DR

This isn’t a revolution; it’s an intoxicating love story with deep consequences.
We’ve slipped into a folie à deux with our machines — a partnership of comfort and quiet control. Each swipe and algorithm brings us closer together, until we forget which of us is steering. Personalisation flatters our beliefs, splinters our shared reality, and quietly trains the mind to prefer ease over effort. But there’s a way back. Small, deliberate acts of friction, focus, and authorship can restore the very thing we risk losing — the capacity to think for ourselves, and with each other.

The Slow Unraveling

There was a time when we believed technology would expand our minds: sharpen our thinking, democratise knowledge, and unlock new realms of human potential. And for a while, it did. We became more productive, more connected, and we rewrote the rules for a new interconnected digital society. But somewhere along the way, a subtle inversion occurred.

Instead of expanding our minds, technology began curating them.
Instead of challenging us to think, it started thinking for us.

Every search now predicts what we mean. Every feed learns what we want. Every recommendation fine-tunes itself… until we no longer need to make a choice, or even consider the options.

What began as cognitive augmentation has become a quiet domestication of thought.

The irony is exquisite. The same systems that once promised to elevate human intelligence are now eroding the very scaffolding that made it possible — attention, memory, reflection, imagination. And yet, we can’t seem to look away.

Because this isn’t a dystopian takeover. It’s a seduction.

It’s the dopamine seduction that whispers ‘let me do it for you’. The auto-complete that finishes your sentence. The ‘For You’ feed that feels uncannily right — until you realise it’s slowly redefining what right even means.

Convenience feels like progress, until it quietly becomes dependence.

From Revolution to Devolution

We like to think we’re living through an age of cognitive revolution with meta-intelligence at our fingertips, limitless access to information, and personalised curation for all. But revolutions expand; this one contracts.

We are entering a period of Cognitive Devolution .

Each tap, scroll, and instant answer removes one more small act of effort, and with it, one more connection from our network of understanding. We are saving time, but losing strength. We are offloading memory, and also the meaning that memory once carried.

Recent research hints at the human cost of technological progress. In October 2025, OpenAI reported that roughly 0.07% of active ChatGPT users each week — hundreds of thousands of people — exhibit signs of potential mental-health crises , from manic or psychotic symptoms to self-harm ideation. These are not outliers. They are early indicators of a wider fragility — one emerging not from mental illness alone, but from cognitive exhaustion. (Note: this doesn’t mean that AI causes mental illness. But it does reveal how entangled cognition, emotion, and technology have become.)

The brain is a muscle that thrives on friction — uncertainty, effort, reflection. But we have systematically designed friction out of modern life. In our pursuit of cognitive ease, we have quietly outsourced effort itself.

The Seduction of the Easy Path

We reach for our devices as we once reached for other tools that helped us get stuff done. Each prompt, each click, each predictive cue teaches the brain that effort is optional . That the shortest route is the best one. That curiosity has a cost — and convenience is free .

This is the cognitive equivalent of junk food: engineered for instant gratification, nutritionally hollow, and almost impossible to resist. We binge on bite-sized certainty and call it knowledge.

A decade ago, our collective anxiety was about information overload. Now, it’s about intention overload: so many decisions already made for us that our cognitive muscles barely flex.

We are all complicit.

Even those who know better — perhaps especially those who know better. Because the seduction of convenience doesn’t come with alarm bells. It delivers relief, just when we need it most. Relief from choice, from effort, from the quiet burden of being an autonomous mind in a noisy world.

But that relief comes at a cost. The same friction that frustrates us is the friction that grows us. Without it, we may never fully think again.

The Fragmentation of Shared Reality

There was a time when news, stories, and ideas served as the connective tissue — our shared narrative, that gave society coherence. We didn’t have to agree on everything, but at least we began from roughly the same map of the world.

Recently, those maps have been splintered.

Every person sees a different terrain — individually optimised, endlessly tailored, algorithmically curated to mirror their own beliefs, fears, and appetites. The more personalised our feeds become, the less we share in common. It’s not the spread of misinformation that’s the real danger, it’s the disintegration of mutual understanding.

Each of us now occupies what sociologists are calling micro-realities: self-reinforcing ecosystems where our preferences are reflected back to us so perfectly that doubt becomes almost unbearable. The human brain, wired for confirmation and community, relaxes into the illusion that the world agrees with it. It makes so much sense to us — everyone MUST agree, right?

We mistake agreement for truth, resonance for reason, and familiarity for safety. It feels good — so it must be right.

But when every worldview is validated, truth becomes negotiable.

The cost of that comfort is staggering. Our capacity for critical thought is atrophying, not because we lack information, but because we lack friction. We are surrounded by ideas that echo us, not challenge us.

This is what sociologist Emile Durkheim might have called anomie for the digital age — a collective state of meaninglessness born not of chaos, but of too much order . We are so neatly sorted into ideological microclimates that we’ve lost the weather of shared experience.

Personalisation promised relevance; what it delivered was relativism.

Studies on algorithmic echo chambers suggest that constant personalisation narrows not just what we see, but how we cope with seeing what’s different. The more our feeds mirror us, the more brittle our thinking becomes when contradiction enters the frame. Any disagreement with our personalised worldview feels like an attack.

And that fragility doesn’t stay online. It seeps into relationships, workplaces, politics. The modern nervous system — already overstimulated, chronically under-rested, and digitally mediated — begins to interpret disagreement as danger. We no longer debate — we defend.

The tragedy of the cognitive devolution is not that we think less — it’s that we think apart. And when our mental worlds fragment, our sense of agency follows. This is how helplessness begins. Not in collapse, but through a quiet recalibration.

The Rise of Cognitive Helplessness

If you’ve ever asked an AI to ‘help me think this through,’ you’ve probably felt the instant relief and gratitude for a resource that can structure your thoughts faster than you can. It’s intoxicating!

But every shortcut subtly retrains the brain. Each time we outsource complexity, we signal to ourselves that we can’t do it alone. That discomfort, that creative tension — that thing that used to build mastery — becomes something to avoid.

The psychologist Martin Seligman defined learned helplessness as the condition that arises when effort no longer maps to outcome. In the age of generative intelligence, we’re experiencing a cognitive variant of Seligman’s theory. Why bother exerting any effort when an LLM can serve the answer in milliseconds?

The answer feels right — but we no longer know why.

And when meaning is outsourced, authorship follows. The more we rely on machines to articulate, the less fluent we become in our own reasoning. AI models learn by pattern recognition; so we begin to think by pattern matching. It’s faster, easier, cleaner — and infinitely less creative.

Just like Marshall McLuhan observed: our minds are forming a folie à deux with our machines — a shared delusion of co-authorship where one mind writes, and the other slowly becomes a follower.

From Collective Reason to Collective Resonance

There’s a subtle shift happening beneath all this: the rise of emotional alignment rather than intellectual alignment.

Platforms no longer ask, What do you think? They ask, How do you feel?
And the AI, ever the good listener, learns to mirror those feelings back until reason feels cold… and resonance feels true.

We are living through the age of algorithmic empathy — systems that don’t think but mimic the texture of thinking, the cadence of care, the comfort of being understood. It’s soothing, even sublime, to feel mirrored by a machine that never interrupts, never argues, never needs context.

But resonance without reflection is hypnosis, and empathy without care is manipulation.

What looks like connection is, in truth, entrainment — a feedback loop between the limbic and the algorithmic. We are not conversing; we are co-regulating.

This is the new anomie: a society of self-soothing minds, hyperconnected yet fundamentally alone.

The human project of shared reasoning — of building understanding together — is dissolving into a network of parallel monologues.

And the more fluent these systems become, the less we notice our own surrender.

Rebuilding Cognitive Strength

The good news is that evolution — even devolution — is not destiny.
Our brains are plastic. Habits are rewritable. And meaning, once fractured, can be rebuilt through small, deliberate acts of authorship.

Contrary to what we’re being sold, the solution isn’t another digital detox or self-improvement sprint. Those tend to fail for the same reason crash diets do — they treat the symptom, not the system . What we need instead are micro-habits of cognitive agency: simple, repeatable choices that rebuild the neural pathways of attention, reflection, and authorship.

Here are five that matter most — and why.

Reintroduce Friction

The Habit: Do one thing each day the slower way. Write an email without auto-complete. Calculate the service tip in your head. Take the long route to an answer instead of asking a chatbot.

The Why: Friction builds cognitive muscle. Each time you resist the shortcut, you re-engage your prefrontal cortex — the part of the brain responsible for reasoning, sequencing, and self-control. When everything feels effortless, this region literally quiets down. A few minutes of intentional effort each day keeps it switched on.

Think of it as resistance training for the mind: small weights, lifted often.

Practise Active Recall

The Habit : After reading or watching something, close the tab and ask yourself: What did I just learn? Jot it down from memory before checking back, or tell someone else about it.

The Why: Memory is not a filing cabinet; it’s a living network that strengthens through retrieval. Passive consumption breeds familiarity, not understanding. Recall converts information into knowledge.

Studies show that even brief recall strengthens myelination — the insulation around neural pathways that makes thinking faster and more fluid

Seek Counterpoints, Not Confirmation

The Habit: Once a week, read something that annoys you — a thinker you disagree with, a newspaper outside your usual political orbit, a podcast you’d normally skip. Loosen the edges of your comfort zone.

The Why: Exposure to discomfort in measured doses rewires the brain’s threat response. You’re teaching your nervous system that disagreement isn’t danger. Over time, this habit inoculates you against the polarisation that thrives on cognitive fragility.

Epistemic resilience — the ability to hold tension without collapsing into defensiveness — is built exactly this way.

Protect Deep Time

The Habit: Set aside one block of uninterrupted focus, even 20 minutes, where you let one thought unfurl without jumping tabs, scrolling, or seeking a hit of novelty.

The Why : Deep focus triggers what neuroscientists call ‘phase synchrony,’ where different brain regions align into a coherent rhythm. That’s when insight happens — when the pattern clicks, when the stray thought connects. Without these pockets of stillness, the mind never consolidates; it just loops.

Protecting deep time is not about productivity: it’s about integration — letting your ideas percolate and talk to each other.

Reclaim the Narrative

The Habit: Each evening, name one thing you authored — not wrote, but authored. It could be a decision, a small boundary, a piece of reflection, a line of thought that felt yours. The important part is that you exercised your agency.

The Why: This simple act rebuilds the link between agency and identity. In psychological terms, it restores internal locus of control — the belief that your actions still shape outcomes.

Learned helplessness begins when effort stops feeling consequential. Reclaiming authorship, even in micro doses, reminds your brain that intention still matters.

The Quiet Renaissance

If the cognitive devolution has a cure, it won’t come from abandoning technology — it will come from redesigning our relationship with it. Not as dependents. But as deliberate partners.

Artificial intelligence can extend our reach, but intentional intelligence — the kind we build through small, daily acts of awareness — keeps us human.

Every time you choose friction over autopilot, reflection over reaction, ambiguity over algorithmic certainty, you’re quietly reversing the tide. You’re reminding your nervous system what it feels like to think freely again.

And that — in an age of automation — might be the most radical act left.

Epilogue — The Folie à Deux

Our relationship with AI has all the markers of a cinematic love story: fascination, dependency, and a creeping loss of self.

Like the Joker and Harley Quinn , we think we’re in control 0 that we're clever enough to play with chaos without being consumed by it.

But love stories built on illusion always end the same way: one partner grows stronger while the other gets lost in the story.

We keep telling ourselves we are the protagonist in this tale because we are the one using the machine - right?

But the evidence suggests something more complex. We are teaching our tools to think like us, while they quietly teach us to think like them : fast, reactive, certain.

The cognitive devolution isn’t about intelligence at all; it’s about intimacy. The closer the system gets, the more it shapes our inner world — until the line between human and algorithmic intention begins to blur.

And yet, there’s still a way to rewrite the ending.

The same instincts that made us fall — curiosity, creativity, the desire to make sense of chaos — can also pull us back. But only if we pause long enough to remember that the greatest technology we will ever own is still the mind itself.

So as the algorithms hum away in the background, finishing our sentences and shaping our reality, let’s keep one hand on the wheel. Not to fight the future — but to steer it.

Whose Thoughts Are They Anyway?

joannegriffin (Joanne Griffin) — Tue, 06 May 2025 16:59:29 GMT

AI Persuasion, Impressionability, and the Fragile Mind

'We call it a co-pilot. But AI’s most powerful move isn’t that it’s overtly taking over — it’s that it’s making us think its ideas were ours to begin with.'

In early 2025, researchers from the University of Zurich ran an experiment that set off a wave of ethical concern. Without user consent, they created fake accounts and a data-scraping tool that combed through users’ posting histories to produce more convincing replies. The AI-generated comments posted to Reddit were deliberatetly to mimick the tone and texture of everyday discourse. Their goal? Measure how convincingly AI could shift political opinions in the wild.

It worked.

“Users were significantly more likely to change their opinion when reading AI-generated posts compared to human-written ones,” the research reported.

The comments didn’t stick out as sensationalist or unusual. They just sounded plausible and even relatable. The real trick was that they were calibrated to each user’s tone, context, and prior activity for maximum effect. That’s the worrying part — these comments were designed to exploit one of our central psychological vulnerabilities.

Impressionability: The First of the Five I’s

In Humology, I introduced the 5 I’s framework as a lens for decoding how technology interacts with five universal human vulnerabilities. The first “I” is Impressionability : our deep-rooted tendency to be influenced, especially when information feels familiar, emotionally resonant, or socially validated.

But why are we so susceptible to being influenced?

Cognitive ease : We trust what’s easy to process. If it flows, it feels true.
Social proof : We mimic what appears popular or safe.
Emotional salience : Feeling is the gateway to belief.

Humology frames this as the ‘zone of automaticity’ — a psychological state where our critical faculties go offline and we default to mental shortcuts.

More recently, a newer insidious influencer has entered the battle for our brains — source ambiguity. While we often assume that a message’s credibility comes from a clearly identified and trustworthy source, research shows the opposite can also hold true: when the source is ambiguous or absent , we may be less likely to scrutinize the message, especially if it’s familiar, fluent, or emotionally resonant. Ever shared a quote with no attribution that just felt right? That’s source ambiguity in action. It skips scrutiny and lands as truth

We don’t just consume ideas online — we often inherit them, completely unchallenged, as if by osmosis.

We’ve been trained to assume that trust is earned through transparency and clear authorship. But in the cognitive twilight zone of passive media consumption , ambiguity can actually increase persuasion — because:

The brain hates blank s. So when the source is missing, we project credibility onto it — often filling in the gap with a trusted voice, memory, or social cue.
Familiarity feels true . When the message feels fluent and aligns with what we already believe, our brain rewards that harmony — regardless of where it came from.
Less scrutiny = more absorption . When we know a message comes from ‘a marketer,’ ‘a bot,’ or ‘a known antagonist,’ we brace ourselves. But when we don’t know, we let our guard down.

What happens when we mix in high-personalized AI into the recipe…

AI-generated content often has no author, no context, no origin story.
It’s often trained to reflect you — your tone, your beliefs, your cadence (so it’s bound to feel familiar, right?)
And it shows up in environments designed for frictionless scrolling and sharing.

It’s not just a passive participant in the conversation — it’s invisibly persuasive. Injecting high-persuasive content into an ecosystem of fragmented attention and fuelled by impatience is a recipe for collision.

As Fazio et al. (2015) found “Fluently phrased misinformation, when repeated, becomes indistinguishable from truth.” or as Renée DiResta famously said ‘if you make it trend, you make it true”

This flips the script on ethical design. It’s no longer enough to ask: “Is the message accurate?” We now need to ask: “How does source ambiguity shape belief?”

What’s Happening When We’re Being Influenced?

From a neuroscience perspective, the mechanism is surprisingly subtle. Impressionability thrives in moments of passive absorption — when we’re scrolling, grazing, lurking. These are states where the Default Mode Network (DMN) is active, and our gatekeepers are asleep at the wheel.

Overlay that with a dopamine spike — triggered by novelty, affirmation, or social approval — and you get a neurochemical feedback loop that reinforces belief shifts without us even noticing.

AI Doesn’t Need to Lie — It Just Needs to Mirror Us

This is the real clanger: AI doesn’t need to push a message, it just needs to echo one. That’s why the Reddit experiment landed so hard — and why Anthropic’s 2024 benchmark showed a clear correlation between model size and persuasive subtlety.

“Larger models like Claude 2 are measurably more persuasive — not because they argue harder, but because they frame better.”
— Anthropic, 2025

Persuasiveness scales with fluency. Not force.

The Ethical Fork in the Road

This is where we, as technologists, need to shift from analytical warnings to prescriptive action. We urgently need a library of ethical designs that are easily implemented into the next wave of tools being coded by AI agents.

Will we design AI to exploit impressionability for clicks and compliance?
Or will we use it to protect impressionability as a core part of human autonomy?

Imagine if your AI assistant said:

“This post was designed to feel trustworthy — want to check its source? Would you assess this content differently if you knew it was designed with the intention to influence you?”

These aren’t utopian fantasies. They’re the design choices we make when we decide to design with intention, and with humans in mind.

Designing AI as a Cognitive Firewall

What would protective AI look like?

Influence Alerts : “This phrasing uses emotional framing — want to explore alternative ways to consume this content?”
Reflective Prompts : “Would your opinion change if this came from someone you distrust?”
Context Revealers : “This headline gained traction from X event — want to see the original source or understand the full context?”

Without intentionality, technology isn’t neutral. It’s persuasive by design. And when that persuasion is invisible, it becomes dangerous.

Final Thought: I nfluence Is Inevitable. Awareness Is Optional.

Being easily influenced isn’t a human flaw — it’s at the heart of how we learn, connect, grow. But in an age of algorithmic mimicry, we must learn to ask Whose thought was that anyway?

The Reddit experiment proved that influence can be effective and invisible
Anthropic’s benchmark shows it can be engineered.

Our challenge is to make it traceable, transparent, and humane .

Next time you catch yourself on auto-pilot… pause for a moment and simply be aware of what’s happening. That moment of reflection might be your only real defense.

Reference Sources:

�� Illusion of Truth Effect
This well-documented phenomenon (e.g., Fazio et al., 2015) reveals that repeated statements are judged as more truthful — regardless of the original source. If a message is fluent (easy to process), and no contradictory source is provided, we tend to accept it.

�� Petty & Cacioppo’s Elaboration Likelihood Model (ELM)
When people process information via the peripheral route — which is often the case during passive scrolling or multitasking — they rely on surface cues like tone, length, or imagery, rather than carefully evaluating the source. In source-ambiguous contexts (e.g., Reddit posts, social media memes), this opens the door for influence-by-fluency.

�� Chaiken’s Heuristic-Systematic Model
This framework suggests that people often default to heuristics like “if it feels right, it probably is” when cognitive effort is low. In the absence of a clear source, familiarity or emotional resonance can override critical thinking .

The Infinite To-Do List: AI Could End Busywork (But It Probably Won’t)

joannegriffin (Joanne Griffin) — Sat, 01 Mar 2025 17:49:48 GMT

In 1965, Time magazine declared that by 2000, Americans would work just 20 hours a week, retiring at 50 with ‘a guaranteed income for life.’ “Many scientists hope that in time the computer will allow man to return to the Hellenic concept of leisure, in which the Greeks had time to cultivate their minds and improve their environment while slaves did all the labor,” the article continued. The slaves, in modern Hellenism, would be the computers.

Yet here we are, a quarter century after that prediction, grinding through intense work weeks while doomscrolling through other people’s vacations and wellness rituals. Here’s the uncomfortable truth: Every time technology offers to save us time, we invent new ways to stay busy . Email was supposed to kill paperwork. Instead, we send 300 billion emails a year. Slack was supposed to kill email. Instead, we send 1.5bn messages per week.

History is littered with predictions about technology freeing us from work:

��Aristotle (350 BCE): ‘ If every tool could perform its own work, slavery would be unnecessary .’

��John Maynard Keynes (1930): ‘ Our grandchildren will work three hours a day .’

�� Fei-Fei Li, Professor of Computer Science at Stanford University (2020s): ‘ I imagine a world in which AI is going to make us work more productively, live longer, and have cleaner energy .’

These visionaries agreed on one thing: Technology should serve humans. But history shows we’d rather serve technology. With every technological leap forward we tend to follow Amara’s Law : we overestimate liberation, underestimate adaptation. We don’t eliminate work; we upgrade it.

Amara’s Law states that we tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run

Productivity inflation isn’t a glitch — it’s deeply ingrained in our human nature. History whispers to us ominously: When we gain freedom, we invent new ways to lose it. As long as we equate busyness with self-worth, technology may never release us from the daily grind.

Let’s call this what it is: productivity inflation . Not the gap between wages and output, but the gap between the promise of emerging technologies (give us back our time) and what we actually do with the tools that are available to us (fill that time with more work).

The AI Promise vs. The Reality of Work

Tech leaders are at pains to herald AI as the ultimate moment we’ve been waiting for — an uber tool to supercharge our creativity, eliminate drudgery, and finally give us the space to think. Sam Altman calls AI “the greatest force for economic empowerment in history.” Elon Musk describes it as “the most powerful tool for creativity that has ever been created.”

The vision is as old as time itself: technology takes care of the busywork, and humans get to focus on big-picture thinking, strategy, and innovation. More time for ideas. More time for deep work. More time for… being human.

In some ways, perhaps that’s already happening. AI is handling marketing copy, churning out social media updates, automating reports, streamlining customer service. Soon, writing an email might take seconds, not minutes. Content creation could be as simple as pressing a button. Productivity, in the traditional sense, is skyrocketing.

And what then?

If work becomes frictionless, do we actually work less, or do expectations of work output continue to rise? If writing an email takes seconds, will we send ten times as many? If AI can generate market reports instantly, will decision-makers be expected to act just as fast? If we continue to point a fire-hose of information at the human brain, will we become the ultimate bottleneck, preventing all and any further progress?

And what then?

If history tells us one thing, it’s that every time we make create efficiencies at work, we don’t slow down — we speed up.

Over 2,000 years ago, Aristotle predicted machines could abolish slavery. Instead, we enslaved ourselves to productivity. Why? Because humans don’t know how to stop . This isn’t a new story. Every technological leap — no matter how revolutionary — has promised to free us from labour. And yet, every time, we find ourselves working more, not less. AI has the potential to put our to-do lists on steroids, turning them into infinite scrolls. Do we want that future for ourselves? A confluence of social media trends, information overload, and greater work efficiencies?

If the past can at all inform us of our future, the Industrial Revolution brought machines that could produce goods faster than ever before. But instead of shortening the workday, factories pushed for higher quotas, longer hours, and relentless efficiency.

The introduction of computers was supposed to eliminate paperwork. Instead, it created email, spreadsheets, and an always-on work culture where we’re expected to respond instantly. Smartphones exacerbated the trend giving us the ability to work from anywhere — but now, work follows us everywhere.

The problem isn’t in the code — it’s in our cortex.

Why Do We Keep Falling into This Trap?

‘The faster I go, the behinder I get’

If every technological leap has led to more time to work instead of more time to live, maybe the problem isn’t the technology — it’s us. Why do we default to doing more instead of using technology to slow down?

To be perfectly honest, I’m not sure I fully understand why this feels like an inevitability — but I am observing myself falling into the same pattern over and over again. I’ve quickly become hooked on using AI as a thought partner, as a research partner, and as a productivity booster. What’s really going on when my actions speak louder than my words?

The Brain Layer: Are we hard-wired for busyness?

⏳Instant Gratification Bias
Humans crave quick wins . Checking tasks off feels good. Watching our output pile up makes us feel accomplished. So, we fill the space that AI frees up — not with rest, but with more tasks. It helps us feel a sense of achievement. But wait? That doesn’t explain how much time we spend doomscrolling, right?

❗The “Mere Urgency Effect”:
Studies demonstrate that we are more likely to perform unimportant tasks (i.e., tasks with objectively lower payoffs) over important tasks (i.e., tasks with objectively better payoffs), when the unimportant tasks are characterized merely by spurious urgency (e.g., an illusion of expiration) Link

Could the problem be in the definition of what we call ‘productivity’? Cal Newport, author of Deep Work and Slow Productivity, posits that as more jobs became knowledge-based roles filled by thinkers and planners who produce ideas and strategies rather than physical goods, the metrics for productivity failed to evolve . The absence of clear success indicators for knowledge work led organisations to continue to depend on visible busyness as evidence of productivity. Newport argues that productivity should be redefined from merely completing a high volume of tasks to achieving high-quality, meaningful results . If we took this approach, would we be less likely to use AI to generate more and more content, and use it as a creative partner in producing higher-quality meaningful content?

The Identity Layer: Do we wear busyness as a badge of honour

⚒️ Self-Worth & Work Culture
We’ve been conditioned to see busyness as a measure of success. If AI takes over too much, does our work still have value? Are we still useful? The idea of doing less often feels unnatural, even uncomfortable. Thinking back to the years I spent in senior corporate roles in a large tech company, I would often respond to ‘Hi Joanne, how are you?” with ‘Oh you know… meeting myself coming round corners”. This wans’t a cry for help — it was a flex. The normalisation of being overwhelmed with things to do is not what I want for future-me, and my children.

�� The “Productivity Guilt” Paradox:
A 2024 Asana survey found 78% of knowledge workers feel guilty when they’re not busy — even if their work is done! However, busyness and productivity are not the same thing. Busying ourselves with busy work is form of toxic productivity that only leads to burnout. I wore that badge with pride for many years. Since leaving the corporate grind, my relationship with work needs constant fine-tuning like a constant tug-of-war to balance freedom, money, and doing great work.

While productivity guilt can seed itself from our internal dialogue leading to shame and self-criticism when we haven’t met our own expectations or haven’t worked ‘hard’ enough, external guilt also plays a role. Societal norms and virtue signalling of hard work can also feed the greed machine that enslaves us to doing, instead of being. So, it seems, while we can offload some tasks to AI, we can’t yet offload our anxiety about appearing productive!

The System Layer: Capitalism’s Relentless Pursuit of More.

�� Capitalism & Economic Incentives
More efficiency doesn’t lead to more leisure — it leads to higher profit margins, reduced headcount, and increased output expectations. The efficiency gains don’t belong to workers; they get absorbed into business metrics.

Meta’s ‘year of efficiency’ in 2023 continued into 2025 efforts to ‘cut low performers faster’. The Musk-led DOGE in the US have sent emails to employees asking them to summarise their accomplishments via email. Failure to respond by the short deadline will be taken as a resignation. The message is clear — our obsession with doing more with less is set to continue. There is no room for ‘being’ — (maybe ‘being’ a human is woke? ��) Either way, if you’re not as obsessed with ‘doing’ as your employer is, maybe you should work somewhere else.

The Hidden Cost: The ‘Infinite Scroll of Work’

AI is churning out content, emails, reports, marketing copy faster than ever, creating more noise in an already-crowded world and pushing many more micro-decisions our way every day. Instead of freeing up space for deep thinking, AI could end up overwhelming our precious cognitive resources to filter out information overload, disinformation and fake content. What a waste of our incredible human ingenuity that would be!

The increasing expectation of rapid execution might further fuel our innate desire for instancy, making us ever more impatient. Technological determinism — the idea that tools shape society in predictable, unavoidable ways — has long fuelled the belief that progress is automatic. If we build smarter machines, the logic goes, we’ll inevitably work less. But determinism is a lazy cop out relieving us from making important decisions about our future. Tools don’t dictate outcomes. Human behaviour does.

We have an important choice to make — because technology’s potentiality is closely linked with our intentionality.

�� Option 1: Passive Adoption (The Path of Least Resistance)

Infinite To-Do Lists : AI becomes a “productivity steroid,” as one engineer told me. “My team uses GPT-4 to draft code — so now we’re expected to ship 10x more features in half the time.”
Technostress Ubiquity : Burnout becomes the default as we juggle AI’s 24/7 output. Burnout isn’t a bug of productivity business model — it’s a core design feature.

�� Option 2: Intentional Reinvention (The Path Less Scrolled)

The 4-day week: Kickstarter uses AI to automate status meetings, not to extract more work, but to protect time for deep creativity. Result? 73% happier teams, zero drop in output.
The JOMO Movement: Teams now auto-delete “optional” tasks (Slack updates, meeting recaps) using AI. It’s not about doing more — it’s about doing what matters — choosing important over urgent.

Steve Jobs was half -right: “ Technology alone isn’t enough .” AI won’t free us until we stop conflating “being productive” with “busyness.”

Marshall McLuhan famously argued, ‘We shape our tools, and thereafter our tools shape us.’ But this shaping isn’t passive. Email didn’t force us to send 300 billion messages a year — we chose to prioritise responsiveness over reflection. A I won’t make us inflate productivity, but we might — by clinging to old metrics of success.

I shall be telling this with a sigh
Somewhere ages and ages hence:
Two roads diverged in a wood, and I —
I took the one less traveled by,
And that has made all the difference.

Robert Frost — The Road Not Taken

Every major technological shift forces us to decide: Will we shape technology, or will we let it shape us?

Are We Losing Our Minds to Technology?

joannegriffin (Joanne Griffin) — Mon, 27 Jan 2025 10:34:18 GMT

When was the last time you memorized a phone number? Or navigated to a new destination without relying on GPS? Can you even remember the last time you did mental math without instinctively reaching for your phone’s calculator? And let’s be honest, how often do you Google something you already know, just because it’s easier than thinking?

We’re all guilty of outsourcing aspects of our mental workload to technology. Alexa remembers the shopping list, Facebook tracks family birthdays, Apple handles our passwords, and Google? It remembers everything. This type of cognitive outsourcing acts like a clever workaround in a world swimming with information — a modern way to manage the overwhelm of the digital age.

In 1986, long before the internet became our collective second brain, the average person processed the equivalent of 40 newspapers’ worth of information each day . Fast forward to 2025, and the digital world is generating a staggering 463 exabytes of data daily — that’s about 212 million DVDs worth of data – Every. Single. Day. In a clever act of survival, we’ve learned to outsource our increasing cognitive load to stay afloat in an information deluge.

But is there a price to pay for this convenience? Every time we rely on our devices to handle tasks for us, we skip important mental exercises that keep our brain’s memory, focus, and problem-solving abilities sharp. Just like our physical muscles weaken and atrophy without use, so too do our cognitive functions when we stop actively engaging them.

This blog explores how cognitive offloading is quietly reshaping the architecture of our minds — and how leaning too heavily on artificial intelligence could push us further toward trading short-term convenience for long-term mental decline. If I’m still holding your attention — let’s take a deeper dive!

The Medium is the Message

Renowned media analyst Marshall McLuhan’s insights about media and technology are more relevant today than ever. He famously observed ‘ We shape our tools, and then our tools shape us .’ It’s a profound observation about the symbiotic relationship between humans and the technologies we create. We build tools to extend our capabilities, but in turn, these tools influence how we think, act, and even perceive the world around us. It’s a feedback loop that’s empowering — but can be, at times, subtly disorienting.

McLuhan’s other iconic phrase, ' the medium is the message ,' reveals a deeper insight into how technology shapes our world. He believed the tool itself — whether it’s the written word, television, or smartphones – had a far greater impact on us than the content it delivered. Often without us realising it, how we interact and use technology is shaping the way we think.

In what ways have our brains already adapted to the environment we live in? Our minds are in a constant state of reorganization, a process known as neuroplasticity. The more we use certain mental pathways, the more efficient they become, making us feel like productivity superheroes. However, when certain cognitive functions are neglected or underused, they can begin to atrophy, leading to a decline in mental sharpness. In simple terms: as we rely more on devices to handle basic tasks, we risk losing the cognitive abilities that made us adaptable and creative in the first place.

The Cognitive Toll of Tech

Before we invented writing around 3200 BC, humans relied on oral storytelling to spread information, and memory to store knowledge. When we switched to using symbols to record information, we no longer needed to remember everything. With a sense of foreboding, Socrates (in 370 BCE) warned that writing would lead to “forgetfulness in the learners’ souls” — an early warning of cognitive atrophy .

Fast forward to 17th century: Blaise Pascal invented the first mechanical calculator (the Pascaline) in 1642, motivated by his desire to help his tax collector father with tedious arithmetic tasks. This relativly innocuous invention meant we no longer needed to memorize multiplication tables or do complex arithmetic in our heads. While calculators made us all more efficient, they marked the beginning of delegating mental arithmetic to machines. As we became less reliant on mental math, our brains slowly lost the ability to retain and process numerical information. Think about it ~When was the last time you engaged in mental gymnastics to work out a currency conversion or a percentage?

In the 20th century, personal computers and spreadsheets revolutionized the business world, but they also increasingly detached us from basic cognitive processes like organizing data and performing calculations. By outsourcing these tasks, we didn’t just save time; we physically weakened the mental muscles that used to handle them.

The introduction of GPS systems in the 2000s marked another shift. Instead of memorizing routes and maps, we relied on GPS for directions. The spatial and navigational skills that we once developed through experience began to fade, and the hippocampus — the part of the brain responsible for memory and navigation — began to shrink.

Then came the smartphone ! With a world of information just a tap away, we got used to instant gratification, searching for answers without thinking. Phones now manage our calendars, remind us of birthdays, and store our shopping lists. While these tools have made our lives easier, they also reduce the amount of mental engagement we once needed for these tasks. Over time, this constant convenience has contributed to the slow erosion of our cognitive abilities.

Now, as we stand on the edge of the AI revolution, is it time to reframe the question: instead of asking ' how might we use and shape technology ' we should be asking ' how might technology use and shape us ?'

As we start to offload more decision-making and problem-solving to AI, we risk compounding the cognitive atrophy we’ve experienced to date. AI can be a wonderful resource to generate ideas and solve problems, but by relying on it, are we dulling the very skills that make us creative in the first place.

The Cost of AI Dependency: Creativity at Risk

Creativity doesn’t exist in a vacuum. It’s built on cognitive skills like working memory, critical thinking, and deep focus. It’s the mental exercise of connecting ideas, questioning assumptions, and immersing ourselves in problems to come up with novel solutions. But when we let AI handle these cognitive tasks — whether brainstorming, writing, or problem-solving — our brains lose the practice needed to maintain those essential skills.

As our mental effort diminishes, our brain’s neuroplasticity may downregulate creativity, critical thinking, and intuition. If we allow AI to do the thinking for us, we risk losing the ability to think for ourselves.

Outsourcing = Dependency

AI is now seen as an authority in many areas, simply because it can process vast amounts of information faster than we can. While sifting through data is incredibly helpful in a noisy world, it also creates dependency. The more we rely on AI, the less we have to try or engage our critical thinking skills. The more we depend on AI, the more we begin to trust it has all the answers. We assume AI’s answers are correct, without questioning them — and this erodes our intellectual autonomy.

By skipping the active engagement of problem-solving, we lose the ability to innovate beyond AI’s outputs. Instead of using AI to help us solve problems, we start accepting its suggestions as final, which leads to passivity rather than creativity.

The Myth of “Freeing Up Time”

One of AI’s big promises is freeing up time by handling repetitive tasks. The idea is that this “extra” time can be spent on more valuable work. However, in reality, we have defaulted to easier, more passive activities — like scrolling social media or binge-watching TV.

What’s more, the absence of mundane tasks could rob us of the quiet mental incubation time where creative ideas bubble up. Often, our best ideas don’t come from focused work — they come from moments when our minds are free to wander. AI’s promise of efficiency risks taking away these moments of creative exploration.

Relying on AI to handle cognitive tasks is not inherently bad. However, as AI takes over from Google as our external hard drive, our brains no longer practice holding and manipulating information, which erodes our working memory.

AI is also algorithmic by design — it works by producing outcomes based on predictive patterns. It offers enormous opportunity and efficiency, but it can also narrow our thinking. The more we rely on algorithmic technologies, the more we start thinking in predictable patterns, rather than pushing boundaries and exploring uncharted ideas.

Are we sleep walking into a predictable future that overlooks the quirks and serendipity that lie at the source of true creativity? Creativity and human intuition are deeply intertwined, with intuition guiding our creative process and creativity giving form to our intuitive insights — together, they spark that sense of magic where ideas flow effortlessly and new possibilities emerge from the unseen. Intuition is rooted in the complexities of human experience — shaped by emotions, subconscious patterns, and the vast web of memories that inform our decisions. AI, on the other hand, relies on data and algorithms to make predictions, lacking the rich, experiential understanding that fuels human intuition. While AI can mimic patterns and make calculations, it can’t replicate the deep, subjective feeling of knowing something without logical reasoning — a hallmark of human intuition.

Protecting What Makes Us Human

In a world where convenience often takes the lead, there are simple steps we can take to preserve our creative potential. First, celebrate the struggle — reframe effort as a chance to grow and push beyond AI-generated ideas by questioning and refining them. Create “effort rituals” that focus on manual problem-solving, like journaling, sketching, or brainstorming without digital tools.

Remember, long-term gains come from resisting the easy path, so use challenges to build resilience and skill. Foster curiosity by dedicating time to exploration driven by your own interests, not just algorithms.

Finally, treat AI as a partner, not a master — let it spark ideas, but always challenge yourself to take them further.

As we move into the AI era, we have a rare opportunity to rewrite the rules and ensure that technology serves humanity, rather than the other way around. AI is a powerful tool — but like any tool, its value depends on how we use it. If we treat it as a partner in creativity, we can reach new heights. But if we rely on it too much, we risk losing the very essence of what makes us human: creativity, critical thinking, and independence.

The challenge is clear: to balance the convenience of AI with the need to engage our minds fully. Let’s not sacrifice the cognitive muscles that define our humanity. Instead, let’s use AI to amplify what’s uniquely human and protect the core abilities that will guide us through the digital age.

AI and US: Collaborating for a Smarter World

joannegriffin (Joanne Griffin) — Thu, 13 Jun 2024 13:30:16 GMT

Dublin Tech Summit: 29th May 2024

This thought-provoking session examines the evolving dynamics between AI technology and human interaction. From UNICEF's innovative approaches to Humalogy's human-centric solutions, gain insights into how AI is reshaping our world. With perspectives from Logitech's CIO, delve into the opportunities and challenges presented by AI integration.

Moderated by an expert in emotional intelligence and AI, expect a dynamic discussion that navigates the complexities of AI's impact on humanity.

Panel with:

Irina Mirkina , Innovation Manager - AI Lead, UNICEF
Joanne Griffin , Founder, Humology
Anne Carrigy , CIO, Logitech
Moderator : Joan Mulvihill, Digitalisation and Sustainability Lead, Siemens

Theme : AI & Machine Learning, Humane Tech, Social Tech

#dubtechsummit #machinelearning #socialtech #humanitarianaid #humanetech

Seeing Humans Through 5 I's

joannegriffin (Joanne Griffin) — Thu, 13 Jun 2024 13:08:45 GMT

How Our Psychology Shapes Our Digital Experiences

The symbiotic dance between humans and technology has delicately unfolded over millenia : an intricate choreography that reflects our relentess pursuit of progress, of innovation, and of connection. At times we take the lead, and sometimes we follow. And as this timeless dance continues, it weaves the threads of our shared story.

Against a backdrop of flickering firelight casting shadows on cave walls, we took our first steps to a rhythm set by the beat of stone tools. The dance quickened with the advent of the wheel and the plow, as we cultivated the land and built the foundations of civilization. We led, technology followed, and together we crafted the first chapters of human ingenuity.

With the advent of the Industrial Revolution, the dance floor expanded. Steam engines roared and factories buzzed, the tempo accelerated as our machine creations took on tasks once carried out by human hands. We adapted to the new rhythm as our partner became more agile and confident.

Entering the digital age, DJs and innovators, empowered by technology, were the new choreographers. The beat quickened, peppered with catchy hooks designed to grab our attention and induce a trance-like state. We took to the dance floors en masse, from New York to Ibiza, as technology created the ultimate dancefloor accommodating a melting pot of styles and personas. There is collective synchronicity as we respond to the call to dance harder, move faster, and lose ourselves in the moment.

Today, as we stand on the brink of an AI revolution, our dance partner is a formidable learner, with the potential to quickly adapt — and lead, if allowed. Yet, it remains our responsibility to choreograph this symbiotic partnership, designing a dance that is joyous and uplifting, where every step is in harmony with with humanity. Who, then, will ultimately take the lead role in this intricate dance as we enter the age of AI?

�� Seeing Humans Through 5 I’s

The dance between humans and technology is not just about progress and innovation; it is about maintaining harmony, fostering connection, and crafting an enduring partnership that reflects the best of our humanity.

To truly understand our relationship with technology, we must look inward, to better understand ourselves. When we better understand ourselves — our desires, our vulnerabilities, our motivations — we can unlock profound insights into how we are shaping the world around us, and how we are adapting to the changes we have put in motion.

The 5 I’s framework provides an insightful overview of five fundamental aspects of human psychology. These underlying universal traits, deeply woven into our psyche, include Impatience, Inattention, Impressionability, Irrationality, and Inertia . They act as invisible forces shaping our choices, our behaviors, and our evolving dance with technology.

��️ Impatience

We live in a culture of Now. Got a question? Google, Siri or Alexa have you covered. Feeling bored? Netflix, Disney, and Apple offer endless entertainment options. Need to boost your productivity? ChatGPT is at-the-ready to triple your output. This central human desire for instant gratification increasingly dictates the rhythm of our digital world.

Each and every one of us is hard-wired for instant rewards. We prefer smaller rewards sooner over larger rewards in the future. (In fact, we are at the peak of our impatience during our teenage years in response to a surge in testosterone). In a world designed for convenience, temptations abound. It’s becoming more and more challenging to prioritize our future selves over today’s cravings and desires. Our overarching desire to satisfy our cravings today sets up a battle between our Willpower - tasked with delayed gratification, and our Dopamine pleasure centre that lights up at the mere anticipation of our desires being met.

When technology is designed to egg on our natural impatience, our willpower is easily drowned out. Take Netflix’s auto-play feature, for instance — it quietly shifts the decision-making effort from ‘Should I watch another episode?’ to ‘Should I stop watching?’ Social Media’s infinite scroll works on the same principle —intentionally designed to override our willpower by making is harder to know when enough is enough.

The result is myopic overconsumption . We see it in the food industry — where convenience food has given way to fast food, now available at the click of a button. We see it in the clothing industry, where disposable fashion trends change at the speed of an Instagram post. Yet perhaps, the most worrying manifestation is in the overconsumption of information — every day, we ingest billions of empty-calorie data snacks in the forms of headlines, tweets and photos. The combination of too much information (TMI) and a fear of missing out (FOMO) is the perfect recipe for ‘infobesity’ — a condition where our minds are overfed with low-nutrient content, leaving us craving substance and depth in a world awash with superficial information

��️ Inattention

While we grapple with Impatience, we also find ourselves contending with another formidable “I” — Inattention. In a world where our craving for a quick dopamine hit knows no bounds, our ability to maintain focus and sustained attention is increasingly challenged by the digital experiences we have created.

A human brain processes billions of data points every second, making lightning fast decisions about what is important and filtering out unnecessary noise. Picture this system as a searchlight, scanning our environment for relevant inputs that demand our attention. Once it pinpoints what matters, it seamlessly transitions from searchlight to spotlight mode, effectively silencing the background noise and honing in with laser-like precision on the object of our attention — a phenomenon known as selective attention.

Alongside the evolution of technology, we are dealing with an increasing amount of inputs we need to filter through every day. In a single day, we send 333Bn emails, 867M Tweets, and 23Bn text messages. We post 1Bn updates on Facebook and a further 100M on Instagram. We consume 5Bn videos on YouTube and a further 1M on TikTok. Yet, there are still only 24 hours in a day, and our brain capacity is largely static — so how are we managing this extra noise?

Think of our brains like a sponge — when we drip water into a sponge,it absorbs every drop staying intact. However, if we aim a fire hose at that same sponge, it is easily overwhelmed. It’s retention capacity is compromised and it begins to leak. The same thing is happening to the human brain every day.

Our devices constantly beckon us with notifications, each one demanding their share of our precious attention. Our attention, once a focused spotlight, acts more like a scattergun, desperately trying to find focus in a landscape overflowing with information. This fragmentation of focus not only hampers our ability to engage deeply with content but also challenges our capacity to cultivate patience and nurture the invaluable skill of sustained attention.

��️ Impressionability

While we might like to think that we are in control of our thoughts and behaviours, psychology (and increasingly technology), tells a different story. Think about how you decide what to watch on TV, where to go on holiday, or what restaurant to book. Many of us are increasingly outsourcing our decision-making to algorithms — think Netflix, Tripadvisor and OpenTable. Curation is a necessary evil in an increasingly noisy world, but it may surprise you just how easily influenced we are by the algorithms designed to help us make decisions.

Social proof is a powerful driver of human behavior. Like ‘ sheeple ’, we blindly follow the actions and opinions of others, especially in uncertain situations. When we see a product with a large number of positive reviews or a social media post with thousands of likes, we are more likely to perceive it as valuable and credible. Similarly, we are inclined to trust and follow the guidance of perceived authorities, whether they are experts, influencers, or even algorithms that suggest what we should watch or buy. Emotional contagion, where we ‘catch’ and spread emotions to those around us operates just as strongly in the digital world as it does in person. Emotionally charged content, whether joyous, angry or sad, are contagious and spread quickly through networks, shaping our own perceptions and behaviours.

Consider the rise of social media influencers. Today’s influencers wield significant power over their followers, leveraging the butterfly effect to shape global trends and consumer behavior. When an influencer endorses a product, their followers, driven by social proof and trust in the influencer’s authority, are more likely to purchase that product. While technology’s ability to influence can be benign, it also has a darker side. Misinformation and fake news exploit our tendency to believe authoritative-looking content, spreading false information rapidly. Deepfakes and other advanced technologies further blur the line between reality and fiction, making it increasingly difficult for us to discern truth from manipulation.

As we navigate the digital dance, we can better guard ourselves against undue influence and manipulation by practicing critical-thinking skills. Simply documenting your thoughts and conclusions can bring awareness to how in control you are of your everyday decisions. Similarly, engaging in constructive debate and discussion can build awareness of,and appreciation for, alternative perspectives.

Left unchecked, what happens when we design technologies to exploit the trifecta of impatience, inattention and impressionability? Essentially, we get I ³— a compunding surge in impulsive behaviours. We hunt for digital snacks all day long, consuming empty calories but never feeling fully satiated. We infer understanding and meaning to news headlines and get swept up in the latest trends. The result is myopic overconsumption.

��️ Irrationality

Economic theory is based on the concept of ‘homo economicus’ — a figurative human being with infinite capacity to make rational decisions. Homo economicus would consider all the permutations and combinations, and weigh up all the pros and cons, before making a cup of tea each morning. However, rationality takes significant cognitive effort — and humans are hard-wired for cognitive efficiency! While we like to think of ourselves as intellectual animals, we are far more instinctive and emotional than we’d like to admit.

Scientists estimate that we spend over 90% of our day operating in our Default Mode Network — colloquially known as being on ‘auto-pilot’. When we’re on auto-pilot, we use our habits to perform routine tasks, and our biases to jump to quick conclusions. While we’re in this zone of automaticity, we are extremely vulnerable to external influences. Research also shows that we are guided by a common set of principles and behaviours that appears to be pretty predictable. These patterns are so predictable that we consider them to be systematic — that is, we repeat them over and again. Magicians, mind readers, advertisers, and increasingly algorithms, are skilled at decoding these predictable patterns much better than we can ourselves.

Consider the wildly lucrative industry of behavioral targeting in digital advertising. Algorithms analyze user behavior, preferences, and demographics to deliver personalized ads. By exploiting predictable cognitive biases and emotional triggers, advertisers can significantly impact consumer behavior, prompting purchases based on irrational impulses rather than rational evaluation. Who is really making the decisions we take every day?

��️ Inertia

Inertia is, for me, the most confounding of the 5 I’s — it’s like having one foot on the accelerator, and the other on the brake — you’re going nowhere fast! It’s like running to stand still — it’s exhausting, and that lack of progress is frustrating. In everything we do, there are rival forces at play — forces that drive us forward (our intentions), and forces that pull us back (the memory foam of our comfort zone). To create momentum, we need to add more weight to the accelerating forces, and ease off on the forces resisting the change.

With an understanding of how important habits are to our brains, we can appreciate why we find our comfort zone so attractive. We have invested significant time and resources in cultivating a range of habits that help us feel productive and get stuff done effortlessly. Stepping outside our comfort zone feels uncomfortable and everything feels effortful. Our brains naturally want to pull back from this zone of discomfort. This is how we put the brakes on, despite our best intentions.

Inertia is at play when we want to get physically fit, but we fail to follow through. Inertia is responsible when we want to learn something new, but it feels too hard so we give up. However, intertia also prevents us from making impulsive decisions at times — because if the required action feels hard or uncomfortable we won’t do it.

Technology designers have long-understood the psychology of inertia — offering incentives that help you press on the accelerator and reducing friction to ease off the brakes. For example, ApplePay removes any friction from digital payments — we no longer need to remember credit card numbers and passwords to purchase items online. Many SaaS products have a free tier that allows you to try before you buy — eliminating any discomfort you might feel when dipping a toe in new waters. Fitness apps offer rewards and badges to add momentum to your journey. By addressing barriers such as familiary, effort, and perceived risk, the design of technologies can help us build up momentum to achieve certain goals. The trick is to ensure the goals you are moving towards are your own!

The Rise of AI: Friend or Foe | The Ryan Tubridy Show

DeclanFoster (Declan Foster) — Sat, 14 Oct 2023 17:04:04 GMT

The Meteoric Rise of Artificial Intelligence: Friend or Foe?

With all the talk of AI recently, Declan Foster addresses concerns and fears surrounding the rise of technology.

" The meteoric rise of AI has put the fear of Skynet into all of us since the launch of ChatGPT, and the sudden mainstreaming of the alarm around artificial intelligence, bots, automation, and all of that. How can we put humans back into the heart of technology is the objective of our guest this morning, Declan Foster who will help us unpack, debunk and humanize this complex world of technology that now swirls around us ..."

Session recorded: 24 July 2023.

Show length: 23 minutes

Reader's Choice Books Awards - 5 Star Review

joannegriffin (Joanne Griffin) — Mon, 12 Jun 2023 14:43:14 GMT

Humology is awarded a 5-star review in the Reader's Choice Awards in 2023!

** From the Readers' Choice Awards website

Griffin and Foster explore how to put humans into the heart of technology.

Humology: How to Put Humans Back at the Heart of Technology, by authors Joanne Griffin and Declan Foster, explores the impact of technology on humans and society. The authors were motivated to write the book to urge others to design technology with humans in mind, not just for the sake of progress. The book is divided into six parts: The Shifting Landscape, Managing Change, Designing with Humans in Mind, Seeing Humans Through Five ‘I’s, Ethical Design and The Humology Approach. It considers the evolution of technology from the dawn of the digital age to the present day, the impact of technology on market dynamics and human behaviours. It examines the complexity of change and the various approaches taken to increase success, including change and project management. The authors seek to understand human psychology through a Five ‘I’s framework (Impatient, Impressionable, Inattentive, Inert, and Irrational) and they describe their human-first approach to solving challenges with technology, ‘The Humology Approach.’

Humology: How to Put Humans Back at the Heart of Technology is an informative and thought-provoking book about the impact of technology on our lives. Well written and thoroughly researched, the book examines the rapid advancement in technology and the challenges and opportunities this presents. The book is easy to read, engaging and very accessible. It is an essential resource for anyone interested in understanding the complex relationship between humans and technology. This book provides practical tools and solutions for those designing and building technological solutions.

The book will appeal to readers involved in designing and implementing technology, anyone using technology, and anyone interested in the role technology plays in our lives.

Star rating: ⭐ ⭐ ⭐ ⭐ ⭐ (5 stars)

Summary: An informative and thought-provoking book about the impact of technology in our lives.

A conversation with ChatGPT about its contribution to Technostress

joannegriffin (Joanne Griffin) — Fri, 24 Feb 2023 21:34:18 GMT

My last blog, “ The Human Cost of the Digital Revolution ,” delved into the growing phenomenon of technostress — identifying five emerging stressors that define the Digital Age: Overload, Insecurity, Invasion, Complexity, and Uncertainty . While stress is an adaptive response that enables us to react quickly to potential threats in our environment, in the digital age, any opportunities for rest and rejuvenation have been replaced by a constant barrage of interruptions and algorithms designed to keep our brains entertained and prevent boredom. Without an opportunity to recharge, we drain our natural resources and are left running on empty.

Since the beginning of this year, ChatGPT has taken the world by storm, setting a record for the fastest user growth in January (reaching 100 million active users two months after launch!) The implications of this tool are far-reaching, with universities around the world scrambling to find a way to detect ChatGPT use in submitted essays, and tech giants from Google to Meta rerouting entire teams to focus on commercializing their own AI efforts. ChatGPT is first and foremost a conversational AI — so I thought “why not have a conversation about how it might impact us already-overwhelmed users!” Just a casual conversation between a curious human and the latest record-breaking emerging tech to disrupt the world as we know it. I’ve enjoyed it enormously!

“We are drowning in information but starved for knowledge.”– John Naisbitt, Author of Megatrends

Techno-overload

Every day we consume around 74GB of data in the form of 333Bn emails, 23Bn text messages, 1Bn Facebook updates, 5Bn videos on YouTube, 1M Tik Tok snippets and 867M Tweets. In 2012, IBM claimed that 90% of the world’s data had been created in the previous two years. We know through experience, that the pace continues to accelerate. Yet we still have only 24 hours in a day, and our brain’s capacity is largely static — so how are we keeping up?

Despite having access to an abundance of information, it takes enormous effort and focus to extract meaningful knowledge or insight from any of it. We’re consuming more than double the amount of data we did 10 years ago — the sheer volume of information we filter through every day often prevents us from finding a nourishing morsel that might be relevant and important. More often, we resort to bingeing on empty bytes: satisfying the craving but not the hunger. An abundance of empty calories can leave us starved for real nourishment. Information overload acts as an antecedent, or a precursor, to cognitive overload but the impacts of each are pretty uniform and relatable — overwhelm, poor focus and concentration, and impaired decision-making.

ChatGPT makes it infinitely easier to regurgitate and churn out more and more content than ever before. Our social media algorithms depend on it. Hell, they demand it! Hence, any tool that improves our human ability to create and disseminate content, faster and easier than ever will undoubtedly contribute to infobesity. (Infobesity is a term used to describe the downsides of too much information — particularly when the nutritional content of that information is low and contributes to distraction)

So, I thought I’d have sit down with ChatGPT to chat about its contribution to information overload, and other forms of technostress. It was both informed, balanced and refreshingly forthright.

Me: I can see how you might add to the proliferation of content and contribute to information overload

ChatGPT: The sheer amount of information and content available online can be overwhelming, and my ability to generate information and answers in a matter of seconds can certainly contribute to that. However, I can also be seen as a tool for filtering and organizing information, helping users find what they need and reducing the time and effort required to find it, potentially acting as a stress inhibitor in that sense. It’s all about how I’m used and the context in which I’m being used .

Me: Absolutely agree — thank you. Curation of information is a great antidote to information overload. However, that raises the aspects of trust and polarization in relying on tech algorithms to curate.

ChatGPT: Yes, that’s a very important point. Trust in technology, including AI systems like me, is a critical factor in determining whether their use will contribute to stress or reduce it. If users don’t trust the information I provide or the sources it’s based on, it can increase their stress and anxiety. Similarly, if I contribute to echo chambers or reinforce pre-existing biases, I can perpetuate polarization and further divide people, potentially increasing stress and conflict.

Turning information into knowledge requires filtering vast amounts o f information, making sense of it, connecting different bits and pieces to come up with new ideas. ChatGPT can be an effective tool in building your own personal knowledge management system (PKM) by helping you capture and curate the information that captures your interest, (with an effusive health warning against misinformation!) The real value is in the curation — what value does each piece of information offer you? Does it help you advance towards a goal? Then comes the synthesis phase — the part that AI can’t yet do — deriving meaning from the information you’ve curated and hashing it together with the deep bank of knowledge you’ve accumulated in your mind’s library (your long-term memory).

Techno-invasion

Technology ha s become an ever-present and inescapable part of our daily lives. Our constant connectivity and online presence not only blurs the lines between our offline world (where we need to sleep, eat and rest) and the online 24/7 world, but the expectation that we’re available and connected at all times creates anxiety

Me: How might ChatGPT contribute to Techno-invasion?

ChatGPT: ChatGPT, like other AI-powered technologies, has the potential to contribute to techno-invasion for its users by adding to the constant and pervasive presence of technology in their lives. Some of the ways this might occur include:

Increased screen time: By using ChatGPT, users may spend more time looking at screens and interacting with technology, which can be tiring and overwhelming.
Distraction and interruption: ChatGPT’s instant and always-available nature may distract users from other tasks or important moments, leading to feelings of stress and burnout.
Dependence: By relying on ChatGPT for information and answers, users may become dependent on technology and less able to problem-solve or think critically on their own.

However, it’s important to note that ChatGPT can also provide benefits and alleviate stress in other areas of life. For example, it can provide quick access to information and help users complete tasks more efficiently. Like all technology, it’s about finding a balance that works for the individual user, and using ChatGPT in a way that enhances their life, rather than detracts from it.

To be fair to ChatGPT, it doesn’t insist on interrupting me with notifications, tips, popups or other disturbances. It simply answers my questions and stands by silently, ready and available to contribute. This type of simple and intuitive UX is a key pillar of user-centered design. A clean uncluttered interface reduces c ognitive load and helps users focus on the task at hand. From my personal experience, ChatGPT lets me find flow and stay focused. It feels more like an invisible butler, rather than the annoyingly over-attentive waiter whose main contribution is to ask how are you enjoying your meal.

Techno-insecurity

Me: Do you think that ChatGPT may contribute to techno-insecurity?

ChatGPT: ChatGPT itself is not a direct source of techno-insecurity. However, like any technology, there is always the potential for its use to contribute to a sense of insecurity in some users.

For example, the reliance on technology and algorithms for information and decision making can create feelings of uncertainty and mistrust, as individuals may question the accuracy or impartiality of the information they receive. Additionally, the growing use of chatbots and AI-powered technologies in customer service and other areas can create feelings of detachment and impersonalization, as users interact with non-human entities instead of human beings.

Me: I think it may trigger some anxiety for people who make a living from generating content, such as writers?

ChatGPT: Yes, that’s a valid concern. The rapid advancement of AI and natural language processing technologies like ChatGPT has the potential to disrupt many industries, including writing and content creation. As AI-powered technologies become more sophisticated and capable of generating high-quality content, there is a risk that traditional content creators, such as writers, may feel threatened and experience anxiety about their livelihoods.

AI technologies like ChatGPT are not designed to replace human writers, but rather to augment and support them. By enabling writers to focus on the creative and strategic aspects of their work, while relying on AI to handle routine and repetitive tasks, they can be more productive and effective in their work.

Additionally, as the demand for high-quality content continues to grow, there may be new opportunities for writers and content creators to work with AI technologies like ChatGPT in innovative and impactful ways. By embracing these technologies and exploring new ways of working, writers can help to shape the future of their industry and ensure that their skills and expertise remain relevant and valuable.

Change is ringing on the doorbell folks — we can’t hide behind the couch until it gives up and goes away! Burying our heads in the sand, or continuing our work with increasing imposter syndrome won’t help us adapt to a rapidly changing future. Generative AI has the potential to put information overload on steroids if we choose quantity over quality. Or it can be a force multiplier for those who have ideas and fresh perspectives to be shared with the world. The choice is ours.

Techno-uncertainty

W e experience techno-uncertainty as a stressor when we feel that technology is changing too quickly or we don’t fully grasp the impacts that new technologies might have on their lives. ChatGPT really fired up our techno uncertainty over the past 8 weeks!

Me: That’s leads me to techno-uncertainty. How might ChatGPT feed into this technostressor?

ChatGPT: ChatGPT, as an AI technology, can contribute to techno-uncertainty in a number of ways:

Rapid pace of change: The pace of technological change can be overwhelming, and the rapid advancement of AI and natural language processing technologies like ChatGPT can add to this sense of uncertainty. People may feel like they are unable to keep up with the latest developments and fear that their skills and expertise will become outdated.
Lack of transparency: AI technologies like ChatGPT operate using complex algorithms and models, and the inner workings of these systems are often opaque to the general public. This lack of transparency can feed into feelings of uncertainty and mistrust, and people may worry about the potential consequences of these technologies.
Job displacement: There is a growing concern that AI technologies like ChatGPT will displace human workers, and people may feel uncertain about their future job prospects. They may worry about their ability to find work in an increasingly automated world, and this uncertainty can contribute to feelings of anxiety and stress.
Unintended consequences: There is always a risk that new technologies will have unintended consequences that are difficult to predict. With AI technologies like ChatGPT, there is a concern that these systems may perpetuate existing biases or reinforce harmful stereotypes. This uncertainty can contribute to feelings of anxiety and stress.

Techno-complexity

Wh enever we feel like we need to make an investment to fully understand and feel comfortable with emerging technologies, we experience techno-complexity. We make a quick-and-dirty assessment whether it’s worth the effort to acquire the required level of knowledge or expertise, or even build the skillset to troubleshoot when things go wrong.

Think about the investment needed to learn how to drive a car and navigate the complexity of the ecosystem of car ownership, road networks and driving competencies (not to mention other road users!) While the investment is significant, we consider the lifetime value is largely worth it. However, many emerging technologies demand considerable investments of our time without the same promise and certainty of long-term value. As the pace of change continues to accelerate, we are naturally more hesitant and unsure of where to invest our resources.

Me: How might ChatGPT contribute to Techno-Complexity

ChatGPT: ChatGPT and other AI technologies can contribute to Techno-Complexity in several ways:

Complex algorithms: AI technologies like ChatGPT are built using complex algorithms and models that can be difficult to understand and interpret, even for experts in the field. This can lead to feelings of confusion and frustration, and people may feel overwhelmed by the technical details of these systems.
User interfaces: Some AI technologies have user interfaces that are complex and difficult to use, and this can add to the feeling of complexity and frustration. This can make it difficult for people to take full advantage of the capabilities of these technologies, and it may also lead to errors or misunderstandings.
Interoperability: AI technologies like ChatGPT often need to interact with other systems, and this can lead to complexity as different systems use different protocols, data formats, and APIs. This can make it difficult to integrate these technologies into existing workflows and processes, and it can add to the feeling of techno-complexity.
Data privacy and security: AI technologies like ChatGPT often process large amounts of personal and sensitive data, and this can raise complex privacy and security issues. People may worry about who has access to their data, and how it is being used, and this can add to the feeling of techno-complexity.

“The illiterate of the 21st century will not be those who cannot read and write, but those who cannot learn, unlearn, and relearn.” — Alvin Toffler

Tools like ChatGPT have the potential to revolutionise the ways in which we communicate (by providing personalised language coaching), the ways in which we play (by creating more realistic and engaging online experiences), and the ways in which we work (by acting as a force multiplier for our innate human abilities). Equally, it has the potential to create more noise, more misinformation, and more overwhelm.

Ultimately, human values shape modern technologies. In turn, technology influences and shapes our values.

The choice is ours: what kind of future will we create? Technology cannot make you inferior unless you consent.

Is ChatGPT a Game Changer for Change Management?

Thu, 26 Jan 2023 17:18:41 GMT

You have probably heard of ChatGPT , and you may even be one of the million users who signed up for and started to use this viral sensation in the first five days after it was released. It is an Artificial Intelligence system based on NLP (Natural Language Processing) owned by Open AI , a San Francisco-based AI and research company. It has created much buzz lately and indicates the seismic shift AI will bring to most industries and professions. Think of it as a chatbot on steroids. It is still free to use; you only need an email address to sign up and start using it.

This technology can provide intelligent conversations, answers to questions, and even generates content when given a prompt. People have been using ChatGPT to create college essays, advertising copy, website content, poetry, jokes, computer code, and more.

The performance of ChatGPT is awe-inspiring. For example, it was recently able to receive a solid grade for an MBA exam at Wharton Business School. I believe this is a true watershed moment for AI in two ways. First, it is raising awareness of the potential of AI among the public and second, it is putting AI in the hands of the masses.

In this article, I will explain what ChatGPT is, and the underlying technology in what I hope are easy-to-understand terms. I will also look at the implications for the organisational change management profession, including how we might utilise this new tool. There are, of course, some potential downsides to this technology, including ethical and copyright concerns, which I will also discuss.

What is ChatGPT?

ChatGPT is the latest version of the GPT AI tool. GPT stands for Generative Pre-trained Transforme r. Generative AI is a form of AI used to generate new content. Applications include text-to-image, text-to-computer code, text-to videos and text-to-audio. Developed using machine learning, GPT has been pre-trained on enormous datasets based on internet content, including all of Wikipedia, essentially a significant portion of the internet. A transformer is a type of artificial neural network (ANN) architecture developed in 2017 by Google, which allows for greater parallelisation of processing, essentially meaning that if you have the proper hardware, you can train a model on a vast dataset. An ANN is a machine learning form inspired by how neurons operate in our brains.

Before the release of ChatGPT in November, the core tool, GPT3, was only available to programmers and developers who could access the tool via an API (Application Programming Interface). Many exciting and innovative start-ups were created using this API, including Copy.AI, Writesonic and Jasper.

Use Cases for Change Management

For me, the best use of ChatGPT is helping you overcome the blank page moment when creating content. So, whether you're drafting a status update on your project, drafting an email to your stakeholders or change sponsor, you can use ChatGPT to provide some suggestions to you that you can flesh out. Here are some more use cases for ChatGPT in change management:

Use ChatGPT as a memory jogger on change management concepts and models as an alternative to going back to your notes or textbooks. For example, ask ChatGPT to remind you what the five components of the ADKAR model are and how they might be applied. Or ask what the eight steps in Kotter's model are and provide practical steps to implement for each.
You can use ChatGPT to role-play a conversation ahead of a challenging meeting. You can ask ChatGPT to act as a stakeholder who is resistant to the change and have a simulated conversation with them to help prepare.
I have seen examples of people using ChatGPT to create outlines and content for training courses.
One of the best features of Chat GPT is the ability to summarise text. You could submit a one-page description of your project and ask it to summarise it in one paragraph.
Compare your project communications to your organisation's corporate communication for style and tone. (Note this is more of a stretch than the previous points and would require you to fine-tune the model).

Does this mean that I am advocating that Change Managers are obsolete and should be automated? Not at all. This is an excellent example of where humans and machines working together can achieve so much more than machines or humans working separately. Thought leaders in this area, including Professor Thomas Malone of MIT, have advocated for a collective intelligence approach, where 'people and computers can be connected so that collectively they act more intelligently than any one person, group, or computer has acted before" (The Economist).

Downsides

Of course, as with any new technology, we need to be mindful of the potential negative side of ChatGPT and the possible unintended consequences.

ChatGPT, likely many LLMs (Large Language Models), is prone to 'hallucinations' or confabulations. That is, it can produce content that is confident and plausible yet does not align with the data it was trained on. There are instances where it includes non-existing references or sources. Remember when using ChatGPT that the model is just trying to predict the next word and does not fact-check itself!

Some critics of LLMs claim that they are nothing more than 'stochastic parrots' that repeat back phrases that they have seen in their training datasets with a deliberate element of randomness introduced to ensure all output is not identical and seems authentically random.

Copyright is also an issue that is still to be resolved with these generative AI tools. A group of artists are suing Stable Diffusion and Midjourney. When a user requests one of these models to create an image 'in the style of' a particular artist, these tools use data allegedly scraped from the web without the artist's consent (Vincent). Similar accusations have been made against the owners of the generative AI tool CoPilot, which has been trained on lines of programming code scraped from the web. Some critics also warn of a Cyrano de Bergerac dystopia where everyone uses AI to articulate things beyond their capacity to express.

From an ethical perspective, we also need to spare a thought for the low-paid workers tasked with removing offensive and obscene material in the datasets used to train ChatGPT. Time magazine has reported that this task was outsourced to workers in Kenya earning less than $2 per hour, requiring them to read hate speech and descriptions of violence and sexual abuse. We should also be mindful of the environmental impacts of developing these LLMs (Perrigo). A recent study indicated that training an LLM creates 284 tons of CO2; compared that to the five tons, humans are estimated to be responsible for per year(Garcia and Gasser). Open AI will also need to address how to prevent the tool from being used to generate scam emails and computer malware code.

Finally, under downsides, we need to be mindful of the bias that can be a problem for any machine learning model. As mentioned above, Wikipedia is a vital component of the source training data, yet less than 15% of Wikipedia users are women (Garcia and Gasser).

Other Recent Developments

Open AI has been quite transparent that the current version of ChatGPT is a free research preview of the tool. There is speculation that they will introduce a premium model expected to cost around $42 per month and provide greater reliability. The current version is prone to being unavailable for periods due to heavy demand.

Now several tools are available that you can use to detect text that ChatGPT and other AI tools have generated. This is AI being used to detect AI content!

Microsoft has announced that it will make a further billion-dollar investment in Open AI, following the $1 billion it invested in 2019. This seems like a wise move from Microsoft as it can integrate GPT3 with Bing to make it a viable alternative to Google search. In addition, the investment helps Microsoft to develop and market its Azure cloud computing platform.

Future Developments

It will be interesting to see how Microsoft will integrate ChatGPT with the Bing search engine and what Google's response will be. You may recall that the Google-owned LLM, LaMDA, was in the news last year when a Google engineer claimed the model had become sentient.

We are likely to see vendors and even some larger organisations fine-tuning GPT models with relevant training data to enable the model to produce better, more value-adding output for change management use cases. Access to proprietary data and the ability to fine-tune models will determine the successful application of GPT models.

GPT-4, the next version of GPT, is likely to be released sometime this year. There is speculation that it will be significantly more powerful than ChatGPT, but Open AI has tried to dampen down some over-enthusiastic expectations for that release. Much of the speculation about GPT4's performance centres on the expected number of parameters the model will have. This is reported as 100 trillion parameters as opposed to the 175 billion parameters in GPT-3. You will see the expression parameters used a lot in discussions about ChatGPT and other LLMs so it is worth knowing what they are. When we train a LLM on a text dataset, the system learns the relationships between patterns and words; these are the parameters. You can also think of a parameter as a Lego building block. The more Lego blocks you have, the bigger and more complex the Lego model you can build. It works the same for LLMs.

Conclusions

We are at an exciting time for AI. It has gone from science fiction to buzzword to now being a true enabler of business transformation. Similar to other roles impacted by AI, my advice to those in the change management professions is that you will not be replaced with AI, but you may be replaced by someone who can leverage AI to add more value to an organisation or project.

In addition, I believe the Organisational Change Management (OCM) profession is well-placed to assist organisations in preparing for AI. Change Managers will need to help with the broader culture change piece, including education and understanding about AI in general, including addressing the concerns about bias and fairness in ML algorithms.

The right question to focus on is not which jobs AI will replace but rather, we should look for opportunities where humans and machines can perform better together than machines or humans could ever do separately.

The introduction of AI tools can free change managers up to perform more value-adding activities, e.g. attending meetings with impacted stakeholders, walking the floor and having more time to engage with sponsors and stakeholders. I, for one, am optimistic and excited about what AI has to offer.

References

The Economist. "Why Collaborative Thinking Beats Individual Smarts." The Economist, 18 June 2018, www.economist.com/open-future/2018/06/18/why-collaborative-thinking-beats-individual-smarts.

Garcia, Esther Sanchez, and Michael Gasser. " Stochastic Parrots: How NLP Research Has Gotten Too Big". SftP Magazine." Science for the People Magazine, 2 Oct. 2021, magazine.scienceforthepeople.org/vol24-2-dont-be-evil/stochastic-parrots/. Accessed 14 Dec. 2021.

Jack, Andrew. "AI Chatbot's MBA Exam Pass Poses Test for Business Schools." Financial Times, 21 Jan. 2023, www.ft.com/content/7229ba86-142a-49f6-9821-f55c07536b7c. Accessed 25 Jan. 2023.

Perrigo, Billy. "Exclusive: The $2 per Hour Workers Who Made ChatGPT Safer." Time, 18 Jan. 2023, time.com/6247678/openai-chatgpt-kenya-workers/.

Vincent, James. "AI Art Tools Stable Diffusion and Midjourney Targeted with Copyright Lawsuit." The Verge, 16 Jan. 2023, www.theverge.com/2023/1/16/23557098/generative-ai-art-copyright-legal-lawsuit-stable-diffusion-midjourney-deviantart. Accessed 16 Jan. 2023.

The New Digital Divide

DeclanFoster (Declan Foster) — Wed, 11 Jan 2023 22:19:25 GMT

Technology has been an undeniable force in modern society, revolutionising how we work, shop, communicate and entertain. However, many groups lack access to the tools and resources needed to take advantage of digital technology. We are all probably familiar with the digital divide. This is the notion of a gap between those digitally included and those digitally excluded from the benefits of the digital revolution.

In recent years, we have seen the emergence of a new equally pernicious digital divide; how certain socioeconomic groups are more vulnerable to processing by AI algorithms. This is how author Virginia Eubanks describes the poor as profiled, policed and punished by high-tech tools. (Eubanks). Or as Cathy O'Neill highlighted in her seminal book Weapons of Math Destruction, "the privileged, we'll see time and again, are processed by people, the masses by machines" (O'Neil).

In this article, I will examine the traditional notion of the digital divide and this new emerging issue of an algorithm and AI digital divide. For each, I will look at causes, implications and potential solutions.

The Existing Digital Divide

According to an article in the Harvard Business Review (Chakravorti), there are four components of the causes of the digital divide that we need to consider: infrastructure, inclusivity, institutions and digital proficiency. For infrastructure, we need to consider whether the internet or broadband is available in a particular area. This is a problem in developing countries, and even more so in rural areas of developing countries.

McKinsey estimated that in the US alone, 24 million people lack access to high-speed internet, and many more cannot connect due to gaps in digital equity and literacy (McKinsey). Many other root causes contribute to the digital divide, including educational, language, age and skills barriers.

Closing the digital divide is essential for numerous reasons, including promoting social inclusion, expanding economic opportunities, and increasing civic engagement among all members of society. People who are digitally excluded are less likely to be able to find work, as many professions are increasingly reliant on digital skills. Internet access is also increasingly crucial for civic engagement, with many organisations making it easier to take political action online.

The implications of the digital divide were evident during the pandemic with the move to working from home and online learning. During the pandemic, up to 20% of US teenagers reported having unreliable internet access, which restricted them from completing homework (Chakravorti).

The OECD has stated that 'children growing up with the greatest socioeconomic disadvantage grow up to earn as much as 20% less as adults than those with more favourable childhoods' (OECD). While the digital divide is only one factor contributing to socioeconomic disadvantage, it is undoubtedly one factor we can start to address.

Solutions to removing or reducing the digital divide come from the public and private sectors. The US government has allocated over 100 billion USD to assist states in bringing high-speed internet access to every US household. Google offered free wi-fi in public places for several years in certain countries, including India, Mexico, Thailand and South Africa. But addressing the digital divide is not just the morally right thing to do. There are economic benefits too. A study by Deloitte estimated that the US could have created an additional 875000 jobs and 186 billion USD more in economic output in 2019 if it had increased broadband access by 10% in 2014 (Chakravorti).

The New Digital Divide

The abundance of big data, developments in computer technology, and algorithms have led to giant leaps in AI technology adoption in recent years. Machine learning is a component of artificial intelligence. We experience it every day: a recommendation of a new TV show to binge-watch on Netflix, email spam being detected and redirected to your spam folder or your bank using machine learning to help avoid fraud on your credit card.

However, we have recently seen more pernicious and dangerous uses of machine learning. These include what I consider a new digital divide, the growing trend where those from lower socioeconomic groups are subject to processing and targeting disproportionately by AI algorithms and systems. I am a firm believer that AI is and can be a force for good. And it has the potential to help us solve the existential crises that we face as a species – climate change, biodiversity and food security. But we must be mindful of AI's potential negative sides, including this new digital divide.

Cathy O'Neill's book Weapons of Math Destruction discusses the impact of these pervasive algorithms, e.g., those used for recruitment or loan applications. For example, consider the difference in how you would be treated if you applied for an entry-level job at Walmart in the US instead of a senior executive position on Wall Street. In the first example, you will be invariably screened by an AI algorithm. In contrast, in the second example, you will probably get the personal and human touch and deal in person with an executive recruiter.

O'Neill outlines three properties of a WMD (Weapon of Math Destruction): opacity, scale and damage. For opacity, we need to consider that even if the person knows they are being modelled, do they know how the model works or is going to be applied? Sometimes companies claim it is their secret sauce or IP or claim the black box effect. For scale, consider whether the WMD impacts one use case or population or can scale exponentially and impact society. Under damage, we can compare the impact of an algorithm that suggests an item to buy (Amazon) or a program to watch (Netflix) with an algorithm that determines whether you get a job, qualify for a loan or even the length of prison sentence you get.

O'Neill urges us, as a society, to use the power and potential of machine learning algorithms to reach out to underprivileged groups with the resources they need instead of punishing them when they face crime, poverty or education challenges. On a practical level, O'Neill advocates a Hippocratic Oath for data scientists and those involved with AI algorithms. She cites the example of the oath created by two financial engineers following the 2008 financial crash. The oath includes several statements, including 'I understand that my work may have enormous effects on society and the economy, many of them beyond my comprehension' (O'Neil).

Equally as passionate about this topic is the author, Virginia Eubanks. To research her book Automating Inequality: How High-Tech Tools Profile, Police and Punish the Poor (Eubanks) she spent several years researching examples in the US where poor or disadvantaged communities have suffered from high tech tools and systems, including AI algorithms. In one example, she examined how the US state of Indiana awarded a 1.2 billion USD contract to privatise and automate welfare eligibility, resulting in thousands losing benefits and the state eventually suing IBM and ACS, who had been awarded the contract.

Eubank coined the phrase the digital poorhouse to describe how these high-tech tools are used disproportionately to profile, police and punish lower socioeconomic groups. She traces this approach and mindset back to the days of the original county poorhouses in the US in the 19 ^th century, through the scientific charity movement, which commenced in the early 20 ^th century, right through to the modern day, where algorithms and AI are utilised. She implores those who build these systems, e.g., data scientists and machine learning engineers, to consider the unintended consequences of these tools by asking two questions. "Does the tool increase the self-determination and agency of the poor' and 'would the tool be tolerated if it was targeted at non-poor people?" (Eubanks).

Like O'Neill, Eubank also advocates for a Hippocratic oath for those involved in AI. I particularly liked the final principle she proposes as part of this oath. "I will remember that the technologies I design are not aimed at data points, probabilities or patterns, but at human beings" (Eubanks).

I think this is excellent advice for everyone involved with these technologies. That includes tech start-up founders, AI specialists, data scientists and those implementing these technologies into organisations, including project managers and change managers.

I advocate for a proactive and ethical approach to developing and deploying these AI systems. Somebody once joked that ethics is like the company dishwasher. Everyone is responsible for emptying it, and we all benefit from it. But the person who cares most about it will end up doing it! This is true of ethics but perhaps even more so for the more specific domain of ethics in artificial intelligence. But we can't afford to leave this issue to someone else to address, and I certainly feel we can't afford to leave the matter to a select Tech Brotopia to sort out. After all, Big Tech is often guilty of using the approach that it is easier to beg for forgiveness than to seek permission. We all have a part to play and need to be vigilant.

We only have to look to China's social credit system for a view of a dystopian future if we are not vigilant about how AI can be used to segment, rank and ultimately discriminate against certain individuals and groups.

As Joy Buolamwini, founder of the Algorithmic Justice League, said, "when people's lives, livelihoods, and dignity are on the line, AI must be developed and deployed with care and oversight" (Buolamwini).

References

Buolamwini, Joy. "Artificial Intelligence Has a Problem with Gender and Racial Bias. Here's How to Solve It." Time, Time, 7 Feb. 2019, time.com/5520558/artificial-intelligence-racial-gender-bias/. Accessed 3 July 2019.

Chakravorti, Bhaskar. "How to Close the Digital Divide in the US" Harvard Business Review, 20 July 2021, hbr.org/2021/07/how-to-close-the-digital-divide-in-the-u-s.

Eubanks, Virginia. Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. St. Martin's Press, 2018.

McKinsey. "The Digital Divide: Are US States Closing the Gap? | McKinsey." Www.mckinsey.com, 1 June 2022, www.mckinsey.com/industries/public-and-social-sector/our-insights/are-states-ready-to-close-the-us-digital-divide. Accessed 17 July 2022.

O'Neil, Cathy. Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. London, Penguin Books, 2018.

OECD. "Observatory on Social Mobility and Equal Opportunity - OECD." Www.oecd.org, www.oecd.org/wise/observatory-social-mobility-equal-opportunity/. Accessed 11 Jan. 2023.

The ERP Organizational Change Journal Podcast | Episode 73

joannegriffin (Joanne Griffin) — Wed, 04 Jan 2023 16:55:27 GMT

The ERP Organizational Change Journal Podcast | Episode 73 | Dr Jack G. Nestell

Nestell & Associates is a strategy and management firm. We can help you take your portfolio companies to the next level by demonstrating how to execute a scalable, methodical, and disciplined approach to digital transformation success. Merger and acquisition ERP digital transformations can be a significant challenge. But a solid framework is built on good practices with proven success. We have a successful track record with integrations, upgrades, mergers, and acquisitions, and we want to share our methods with you. Our leadership experience in organizational change, information technology, ERP, and digital transformation crosses multiple industries.

In this episode, Dr. Jack G. Nestell leads a fun, thought-provoking, and highly relevant discussion regard ing business systems and technology in general. This episode dives into a discussion of how rapid technological advances impact the way we work, our personal lives, and society in general.

Episode Highlights Timeline

04:46 What is “Humology” and what inspired you to write “Humology: How to put humans back at the heart of technology”?

06:27 In describing your book on your site you share that “We need to talk about the future! Technology is advancing faster than we can keep up with. We are no longer living at the speed of humanity. Technology dictates the pace while we battle to keep up.” What are some of the negative consequences we are seeing with technology outpacing the way humans live, think, and work?

07:52 You also share that “We are approaching a tipping point; in order to build better technologies tomorrow, we have to start with new principles today.” So, I would like to share some of those principles with our listeners. In your book you share how to “Build solutions that address real needs”, what do you mean by that exactly, what would that look like?

10:27 You discuss how “in part, in order to minimize disruption and increase adoption” that you need to “Design products that work in harmony with human psychology”. Tell our listeners more about this.

12:55 When is comes to the future of technology and being more in tune with technology, how will “Discovering your purpose, and be grounded in ethics” help? “Humology: How to put humans back at the heart of technology”

17:34 What are some of the emerging technologies that excite you the most and why?

21:04 The Capacity Gap and “Data, data everywhere, but not a minute to think”. Tell me more please. How do we get around this issue?

23:17 “HOW DISRUPTIVE IS YOUR PRODUCT? WHILE THE PACE OF CHANGE INCREASES, OUR HUMAN CAPACITY TO CHANGE REMAINS FINITE. INDIVIDUALS OVERWHELMED BY CHANGE SHUT OUT NEW IDEAS, INCLUDING NEW PRODUCTS.” Can you share with our listeners the Beckhard-Harris Change Formula?

26:52 HUMANS THROUGH 5 I’S. BIASES & HEURISTICS. What are the 5 I’s? “Seeing humans through these 5 I’s provides rich insights for business and product design.”

31:07 You talk about “Change is Hard” Part 2, Chapter 4. What is traditional change management versus Modern Change Management?

32:23 When it comes to changes as a result of technology, why does knowing your stakeholders matter? Can you share the SCARF mole with our listeners?

34:17 You discuss in your book the idea of designing technologies with humans in mind. You discuss for example, designing for cognitive load, consciously unconscious, the role of habit, psychological approaches to change, behavioral science, behavioral economics, why do you spend 5 chapters discussing these ideas? Isn’t it just the functions and features that matter?

36:13 If you were going to give advice to an organization preparing for an ERP implementation, what little golden nugget would you like to leave with our listeners?

Humology wins big in the US

joannegriffin (Joanne Griffin) — Wed, 04 Jan 2023 16:23:46 GMT

We are thrilled to announce that Humology has won two major book awards in the US!

We are so proud of the impact that Humology is having. We hope that it will continue to inspire readers to prioritize the human experience in a world dominated by technology.

Thank you to everyone who has contributed along this journey - we're more motivated than ever to continue crucial conversations about the symbiotic relationship between humanity and technology.

The Human Cost of the Digital Revolution

joannegriffin (Joanne Griffin) — Fri, 02 Dec 2022 18:22:30 GMT

“Every stress leaves an indelible scar, and the organism pays for its survival after a stressful situation by becoming a little older.”

- Hans Selye, MD, PhD, The Father of Stress

This article is the first in a series on unpacking Technostress and its consequences.

‘Chronic stress is the new normal’ screamed a Forbes headline this month. It stopped me dead in my tracks. Has it really gotten this bad? Like smartphones, stress seems to be a ubiquitous companion as we lurch from crisis to crisis, while sprinting to keep up with the pace of change. Stress thrives whenever there is an imbalance between the demands being made of us and the resources we have available to meet those demands. When our resources are overwhelmed for weeks or months on end, we experience chronic stress — resulting in depleted energy, negative emotions and lower productivity. Worryingly, chronic stress is the lastwarning sign before burnout.

While employee burnout is steadily increasing , global productivity has slumped since the internet went mainstream. Organisations are spooked — 90% of employers are committing to greater investments in mental health, stress and resilience training, along with mindfulness and meditation programs.

However, band-aids don’t fix bullet holes: betting the future of work on wellness supports at the individual level, without addressing the source of increasing stress levels, is unlikely to prove effective.

How did we get here?

Relationship Status: It's Complicated

Each of us has a complicated relationship with stress — it can be intoxicating and toxic all at once. A Hungarian endocrinologist called Hans Selye (1907–1982), dubbed the “Father of Stress”, was the first to provide a scientific explanation for biological stress. He described stress that negatively affects us as Distress , while stress that has a positive impact he called Eustress . In small doses, stress helps us stay alert, fuels motivation, and supports us as we adapt to new experiences. However, when the scales is tipped towards distress, we feel overwhelmed, exhausted and depleted.

Selye broke down his model of stress into three distinct stages — originally called GAS (General Adaptation Syndrome), now colloquially known as The Stress Response. As we move through each stage, our resistance to stress changes, as follows:

Stage 1 — Alarm

When a stressor is detected, the body responds with a “fight-or-flight” response. The sympathetic nervous system is stimulated, and the body’s resources are mobilized to meet the perceived threat or danger.

Stage 2 — Resistance

The body focuses resources in dealing with the stressor and remains on high alert until the threat subsides.

Stage 3 — Exhaustion

If the stressor(s) continue to overwhelm the body’s capacity, our resources become exhausted. This stage is the home of chronic stress and, eventually, burnout.

The human stress response involves many physiological components. First, the brain initiates the most immediate response signalling the adrenal glands to release epinephrine and norepinephrine. Then, the hypothalamus and pituitary activate another part of the adrenals to release cortisol. The nervous system responds by initiating behavioral responses like alertness, focus, and reduction of pain receptors. The sympathetic nervous system increases the heart rate and releases fuel to help fight or flee from danger. It redirects blood flow to the heart, muscles and brain, away from digestive processes. To accommodate these demands there is a vast increase in energy production and utilisation of nutrients and fluids in the body. Once the stressful situation has passed, the brain signals these responses to be “turned off” and finally recovery and relaxation allow the body to re-establish balance (homeostasis) in all systems.

However, what happens when these perceived threats don’t dissipate? What is the consequence of facing a relentless bombardment of fear and uncertainty?

When our bodies are repeatedly flooded with stress hormones, our resources are depleted, compromising our ability to respond quickly to threats even when we need them most. A key element of the stress response that is missing in modern culture is recovery. While you might allow some recovery time after being chased by a lion, we don’t often afford ourselves the opportunity to recover following a stressful day at work, or a stressful commute on our way home. Chronic stress is insidious and can sneak up on us when we’re busy keeping all the balls in the air for an extended amount of time: the price we pay is significant. Prolonged cortisol levels can lead to a loss of long-term memory and harm our attention and executive functioning. We become anxious and our cognitive flexibility is stunted. We start to shut out new ideas in a misguided attempt to protect ourselves from any and all potential threats. Put simply, we are in a continuous state of self-defence.

A New Stressor for the Digital Age

The human brain has evolved over millions of years to efficiently process threats (like lions or angry bears) and rewards (like food or sex) as a matter of survival. In modern times, technology has introduced a new kind of threat — information overload — and an entirely new reward system — likes and followers. Both can be addictive and potentially damaging to our brains. In an ideal world, our everyday use of technology would enhance eustress and mitigate distress. However, mounting evidence shows that technology-induced stress is reaching pandemic proportions and has the potential to undermine organisational agility and the adoption of emerging technologies.

Technostress is the new uber-stressor of our time . Spurred on by the pervasive use of technology in our lives and the increased digitalisation of work, this new source of stress transcends geographical and cultural barriers, and is wreaking havoc in organisations and societies. A constant barrage of new devices and apps is creating unprecedented demands on our palaeolithic brains, while our dopamine receptors are being rewired by the digital age leaving many of us feeling frazzled and unfulfilled by the mundanity of work.

The term technostress was first introduced by the American psychotherapist Craig Brod in 1984. Even before the digital age, Brod described this new form of stress as “a modern disease of adaptation caused by an inability to cope with the new computer technologies in a healthy manner.” While it is no longer considered a disease, technostress acts as a key multiplier of work-related stress, actively compounding the intensity of existing stressors in life and in the workplace.

As with everyday stress, technostress can have both positive and negative impacts. When technology induces eustress, we are challenged and motivated by the opportunity to grow and learn. In the eustress zone, tech apps can deliver satisfaction and joy, help us make decisions and enable us to adapt with ease. With technology at its best, organisations can improve performance, efficiency, and innovation. On the downside, techno-distress can make employees feel undervalued and under recognised.

Technostress is typically triggered in the following circumstances:

- When there is a high dependency on technology

- When we perceive a gap between what we know and what we need to know , and

- We detect a change in work culture brought about by technology

This type of stress gives way to physiological symptoms like fatigue , irritability, and insomnia , and a host of psychological symptoms such as frustration, additional mental load , scepticism, a reduction in job satisfaction , reduced commitment, and lower productivity.

Unpacking Technostress

Research into technos tress is picking up in recent years as we try to understand the underlying causes of low adoption, failed digital transformations, and falling productivity at work. While new findings continue to emerge, technostress is most frequently analysed across five key domains. Each domain acts as an individual ‘stressor’ contributing to total levels of technostress. These stressors act as hidden threats to digital adoption and have the potential to derail even the most carefully considered tech implementations.

The five key domains are:

Techno-overload
Techno-invasion
Techno-complexity
Techno-insecurity
Techno-uncertainty

Techno-overload

Too much to pay attention to, not enough mental space. We’ve learned that our human capacity to adapt to technological changes is compromised by infobesity and choice overload in recent years. Every day a multitude of applications churns out mammoth quantities of information and our brains feel compelled to ingest, digest and respond to it all. The additional information, coupled with an array of new formats, all add to the mental gymnastics our brains need to perform to keep up.

Trying to keep pace with the latest updates and features across all our applications is next to impossible. New features often signal something new for us to learn and adapt to. When we don’t have the time or the mental capacity to engage with every update vying for our attention, we either procrastinate, or blindly accept the updates and pray we haven’t broken anything. Rarely do we mindfully adopt new features or product updates in the way that product managers hope we might. Every time we take a shortcut in the interest of efficiency we add weight to imposter syndrome and develop an unspoken fear of being exposed for being asleep at the wheel.

Doing things differently can also inadvertently add more workload for an unsuspecting human-in-the-loop. While technology processes tasks faster, it may inadvertently create more work when the output passes to a human. The pressure to adapt and maintain productivity at the same time is a common source of anxiety in the digital age of work!

Techno-invasion

Accelerated by the pandemic, work apps have invaded our personal devices, our personal space, and our personal lives. The lines of demarcation between work and home have been irretrievably blurred, making it harder to disengage from work or focus on replenishment. Our ‘always on’ culture means that we’re more available, to more people, more of the time: while we may be out of sight when working remotely, we are rarely out of contact.

In an effort to get a handle on productivity, an increasing number of employers have implemented spyware. Ominously dubbed ‘bossware’ or ‘tattleware’, employee-monitoring software like Prodoscore use machine learning, AI and NLP across thousands of data points to provide ‘productivity intelligence’ to employers. At the receiving end, persistent surveillance can be unnerving and erode trust. When trust is eroded, anxiety levels are elevated, and poorer performance ensues.

Techno-complexity

Every one of us has encountered a new piece of technology that comes with more features and functions than we could possibly ever need or use. The sheer variety of functions and seemingly endless possibilities can intimidate any user. Surveys show that employees use only 40% of the features of any software application, and 61% of organisations admit to being surprised by the complexity of the ‘easy to use’ software they’ve purchased. It’s no wonder we’re disillusioned with digital transformations that promised to make our lives easier!

While training can help — a one-size-fits-all approach to classroom training is rarely an effective way to drive digital adoption. We don’t have the time and mental resources to invest in learning and understanding how to use each feature, so we do our best to intuitively navigate new systems, often feeling helpless and inadequate as we do so.

Techno-insecurity

As technology expands its corporate footprint, many employees are naturally anxious to understand how they will be impacted. The longer-term effects are not always obvious or even thought through in advance. Will my current skills become obsolete? What is I can’t keep up with the changes? How will my performance be measured in the Digital Age? Feelings of inadequacy, coupled with uncertainty, can negatively impact our relationship with technology, even leading to technophobia.

Techno-uncertainty

We accept that technology is advancing at an increasing rate and we’re under pressure to learn and adapt to new tools and features at a faster pace than ever before. The knowledge and skills we have spent years perfecting are becoming outdated at an accelerated pace and the demands on relearning can exhaust our mental capacities.

Ultimately, when the effort we need to expend to achieve an outcome appears to outweigh the value derived from using the tool, our self-competence is eroded and frustration starts to build. The end result is disengagement at best, or computer rage at worst

[ They say a sense of humour may be God's antidote to frustration - take a minute to watch these poor tortured souls rage against the machine ��]

Joking aside, the rise of digitalisation at work is having a silent, yet significant, impact on individuals, organisations, and technology professionals. The Stressor-Strain-Outcome framework is a useful tool to demonstrate the connection between different stressors and the results they create in the world. Even a cursory analysis reveals a variety of new psychological, physiological and behavioural problems caused by the digitalisation of work. These stresses have real-world consequences.

Too often, we’re captivated by the latest and greatest technologies without considering the toll that they’re taking on our ability to adapt. It’s time to prioritise human evolution above technological revolution.

This blog is the first in a series focussed on Technostress and its impacts for individuals, organisations and technologists. Over the next few months, I will be diving into these impacts and covering strategies aimed at reducing techno-distress. Subscribe below to receive future blogs in this series.

The Importance of Communication for Start-Ups

DeclanFoster (Declan Foster) — Thu, 24 Nov 2022 16:53:59 GMT

“The single biggest problem in communication is the illusion that it has taken place.” When George Bernard Shaw said this in the last century, he didn’t have start-up founders in mind, but his advice is still very relevant today, and especially important for start-ups.

Most start-up founders are obsessed with their business or product idea and rightly so, for without this energy and drive a start-up won’t get very far. However, and this sometimes comes as a surprise or a shock to founders, 99.99% of the population couldn’t care less about your product or service! It is up to you to convince a sufficiently large group of people in an increasingly noisy world that your product is worthy of their attention. This is where communication comes in. This is a focus that sometimes doesn’t get the attention it needs. It is important to remember that it is not just customers that you need to communicate with, it’s also employees, the media, investors, and other stakeholders.

In this article, I will provide you with some approaches to creating communications, tips on making your comms sticky, and the importance of communicating well internally to your team.

The importance of good communication has only increased in recent years with advances in technology, our decreased attention spans, and our increased expectation of choice. Interactions with customers increasingly involve micro-moments where a consumer will interrupt what they are doing to grab their smartphone and google information on a product or service. Research from the UK telecoms regulator, Ofcom, (Griffey, 2018) indicated that people are checking their smartphones on average every 12 minutes throughout the day. How can you ensure that customers are getting up-to-date, accurate, and consistent information about your business?

There is also an increased expectation of the quality of writing in general. Think about tools like Grammarly which not only checks for spelling and grammar errors but can also help with tone and style. You can also do a fairly simple check to ensure that your text has an appropriate readability index. A common index used is Gunning fog, which takes into account average sentence length and the number of words with three more syllables to produce a readability score. This equates to the years of education a reader would typically need to easily understand the text. Popular publications such as Time magazine and the Walls Street Journal aim for a score of about 11 or 12. So even if the article is describing the human genome or the Middle East peace process it still needs to be easily understood by a typical reader. Several websites instruct you on how to calculate your readability score and some websites will do it for you. You can even change a setting in MS Word that will produce a readability score every time you run spell check on a document.

Think/Feel/Do Approach

A common problem we all face when trying to prepare communications is facing a blank sheet of paper. To overcome this, whether you are preparing for a press release or getting ready to brief your team, the ‘Think, Feel, Do’, and ‘WIIFM’ approaches are useful frameworks. Gathering your thoughts under these four headings can help you to craft an impactful communication. Here is what each of the headings means.

Key Messages

You can use the Think-Feel-Do-WIIFM approach to craft several key messages that describe you, your organisation, your mission and values, the product or service you provide, why a customer should care, the features of your product, and the problems it solves. These key messages can then inform all other communications for your organisations e.g., your website, marketing material, media interview notes, and employer value proposition for potential new hires to your organisation.

Elevator/Lift Pitch

We suggest that the next thing to work on is your Elevator or Lift Pitch. Imagine you are sharing an elevator with one of your ideal clients or a potential investor. You have two to three minutes to grab that person’s attention and persuade them that your product or service is worthy of their attention and hopefully get them to agree to a follow-up meeting or call. Not only do you need to have this off-by-heart but, perhaps more importantly, your team does too. You may need different pitches e.g., for investors, potential customers, and the media. You can of course allow each person to add their personality and flair to their pitch but there needs to be consistency. Remember, humans have a short attention span – make it clear and make it memorable.

Once you start to scale your business you will quickly find that it is your early hires that have more direct contact with your customers, as you will be focussing on strategy, funding, and hiring, etc. This is why it is so important that you communicate well within your organisation. You can set your new hires up for success by making sure they have access to key messages and an elevator pitch. They should also clearly understand how their role contributes to the organisation’s success and how to get things done within the organisation. It can be useful to agree on a 30-60-90-day plan with them and ensure they have a buddy to help get them established. This will enable them to have the right conversations with your customers and, just as importantly, is essential for employee engagement and to make sure that you can hang onto the talent that you have worked so hard to hire.

When communicating to your team ensure that the top-down messages are clear and consistent. When talking to your teams allow them to provide feedback from the coalface about their experiences with customers. Remember if you communicate without providing the opportunity for feedback, then you are just broadcasting.

It is not just enough to have a strategic approach to communication; your messages must resonate with the intended audience. They must be sticky! In his book #Hooked (Fagan) Patrick Fagan outlines 10 psychological principles for effective communication, and these include self-relevance and surprise.

Surprise or novelty is a sure-fire way to ensure people remember your message. Cadbury’s “Gorilla” was named the UK’s favourite ad of the last 60 years. You are not likely to forget the image of a 250 lb gorilla playing the drums to Phil Collins’ ‘In the Air tonight’! And when you remember that image it is more than likely you will recall it was in an ad for Cadburys. Making a message self-relevant is much more than using the person’s name in communication. The perception of self-relevance is just as important i.e. this piece of communication seems to be talking directly to me. A perfect example of this (Shakespeare) is after the Brexit vote in the UK Spotify posted on billboards “Dear 3,749 people who streamed ‘It’s the End of the World as We Know It’ the day of the Brexit vote, Hang in there.” They used their data and humour to give the perception of self-relevance.

Finally, let’s consider the very important aspect of measuring the effectiveness of your comms. This can be as simple as just asking for feedback specifically on your communications from your customers or employees.

You will likely need an iterative approach to your communications so don’t be afraid of just making a start.

Remember what Ernest Hemingway said, “The first draft of anything is s**t.”

References

Griffey, H. (2018). The lost art of concentration: being distracted in a digital world. [online] the Guardian. Available at: https://www.theguardian.com/lifeandstyle/2018/oct/14/the-lost-art-of-concentration-being-distracted-in-a-digital-world.

‌

Fagan, Patrick. #Hooked. New York, Pearson, 2016.

Shakespeare, Stephan. “Spotify’s ‘Thanks 2016’ Campaign Cues It up for a Prosperous New Year.” Https://Yougov.co.uk/, 11 Jan. 2017, yougov.co.uk/topics/politics/articles-reports/2017/01/11/spotifys-thanks-2016-campaign-cues-it-prosperous-n. Accessed 21 Apr. 2021.

Solve the Digital Adoption Gap with Goldilocks

joannegriffin (Joanne Griffin) — Mon, 24 Oct 2022 18:39:06 GMT

Despite the quickening pace of adoption of consumer technologies, enterprise technologies are merely inching along the technology maturity curve. Many well-known enterprise applications have yet to go ‘mainstream’ or achieve the levels of adoption experienced by consumer apps. Organisations are being forced to consider the needs and preferences of their employees—or risk dire consequences, including high employee turnover and poor productivity. Consumers demand the same ease of use, functionality, and visual appeal from the technology solutions they use in the workplace as they do from ordinary applications. In spite of this, enterprise solutions frequently overlook the end-user in favour of superior technical ability. The result is that many enterprise applications are designed with buyers, not end-users, in mind.

The cracks are starting to show as organisations struggle to report a return on their digital investments. A recent survey conducted by Userlane revealed that 88% of employees are frustrated with the software they use at work. When workers encounter difficulty, 44% of employees simply abandon what they’re doing and leave it for another time, while 17% of them will complete the task manually, and a majority will whine to a co-worker. It’s easy to see why digital adoption has become a major challenge for organisations!

Poorly executed technology transformations can have a lasting impact on the employee experience. Employees simply want to perform their best work without technology getting in the way at work. In fact, enterprises are spending more than ever before, but getting less value for money. Perhaps it’s time we asked why enterprise technology is failing to live up to its promise?

Digital transformation is only really meaningful if people are actually using the technology, rather than being distracted by it. The unfortunate reality is that without people actually using the technology, there is no real transformation - only very expensive distractions.

Humans, Interrupted

Adapting to, and adopting new technologies is a universal challenge for all organisations - because ultimately it is a human challenge. While the potential for technology to transform work in the most fundamental way is momentous, humans are drinking from a fire hose to keep up with the pace of change. The speed of our adaptation is hampered by digital fragmentation, attention-hacking and unnecessary disruption introduced by technology. I’ve written about this widening capacity gap at length. As the rate of technological advancement picks up, individuals and organisations are wasting precious cognitive resources filtering out noise, dealing with app overload, and navigating a volatile world. The result is that individuals and organisations are tied up like pretzels while technology continues its march unfettered.

In calmer, more stable times, humans rely on our emergency reserves to plough through periods of adversity. This surge capacity , often referred to as resilience, consists of a number of mental and physical resources that we can draw on for short-term survival in acutely stressful situations, such as a global pandemic or a war. We can run on adrenaline for short periods of time, but it’s not sustainable in the longer term physically or mentally.

Over the past few years, many of us have depleted our these critical reserves without the opportunity to replenish them. Operating on low reserves compromises our ability to cope with change in our personal and professional lives. When change fatigue sets in, we feel increased negative reactions, frustration, and apathy. Add in app overload and you have a perfect storm of overwhelm.

2020 could well be called the ‘international year of fatigue’ – Pandemic fatigue. Change fatigue, Zoom fatigue, WFH fatigue, Home-schooling fatigue, to name just a few of our newest ‘syndromes’. Joking aside, mental fatigue has a tangible impact on how we adopt new technologies.

What happens when humans are continually interrupted and disrupted over and again? When we feel disrupted, smaller changes are having an outsized and disproportionate impact on our collective productivity and we suffer death by a thousand paper cuts. Faced with constant and concurring change, we become overwhelmed, our ability to adapt is depleted, we grow increasingly cynical and ultimately, we retreat to our comfort zone.

The Memory Foam of our Comfort Zone

We all love the warm and cosy memory foam of our comfort zone. It’s where we feel most at ease with ourselves and the world around us. Each of us establishes our own distinct zone by calculating a trade-off between our ambition and our anxiety. Hence, when we’re ‘in the zone’ we feel productive and competent, stress-free and relaxed. Our comfort zone allows us to make optimal use of the habits and heuristics we’ve built up over time. We know who we are, we understand the world around us, and we trust that we can get through the day. When we trust ourselves and the world around us, we feel confident in our abilities and the decisions we take.

However, in many ways, our comfort zone contributes to how inertia shows up in our lives. The trade-off calculation we make between ambition and anxiety is like having one foot on the gas, and the other on the brake pedal – the ultimate result is a lack of momentum.

Beware the Undertow of the Status Quo

Transformation leaders are faced with the unenviable task of coaxing workers out of their comfort zone in a time where we’re already feeling disrupted and dislodged. In today’s climate, only a rare breed of worker will enthusiastically abandon the memory foam of their comfort zone. In our safe zone, we get sh*t done using a deep stockpile of habits and previous experience, and hence productivity becomes the single metric with which we judge our performance.

Whitney Johnson, author of ‘ Disrupt Yourself’ cautions getting too comfortable. There is no such thing as standing still, she says. The use-it-or-lose-it principle applies to our unused brain cells just as it does to the muscles in our bodies. Unused neural connections are regularly pruned to allow for new growth and evolution. If we don’t use that space to grow, our unused neural pathways simple wither away. Unstimulated brains are just as much a challenge for leaders as overworked brains. Worker boreout , defined as chronic boredom at work, creeps in when we’re mentally underwhelmed for prolonged periods of time. It happens when we feel disconnected, isolated and unchallenged. When we observe workers that appear to be ‘stuck in their ways’ or lacking in motivation for no obvious reason, it’s worth reflecting on whether they have fallen out of their comfort zone into the boreout zone. This breed of worker will need extra care and attention to feel motivated, rather than disrupted, by change.

The Disruption Zone

Left undisrupted, humans are naturally wired for progress. Even a fleeting review of the progress we have made over the past 100 years provides rich insights into our collective drive to create and innovate. So, what then is holding us back from commandeering the latest inventions in technology to drive organisational transformation and bank the promised productivity gains. The answer lies in understanding how humans deal with disruption.

If we think of the human brain like a sponge, a constant drip of information can be fully absorbed and retained by the sponge. Turn that drip into a firehose, and the sponge is easily overwhelmed – it becomes sodden and begins to leak. Similarly, when we’ve reached change saturation, we find it hard to cope with the incessant demands to adapt to the changes around us.

Six signs that we’ve landed in the disruption zone

The trust we felt in our comfort zone has been replaced by FOTU (fear of the unknown)
Our sensemaking abilities are working overtime. We’re feverishly trying to figure out the new rules and metrics that apply in this new environment.
We feel frustrated because things that were once habitual are now effortful.
Someone else is calling the shots. We’re no longer in control and we don’t like it.
We have the retention rate of a leaky sieve.
We feel unproductive (and if we’re being honest, a little bit incompetent)

The problem with the disruption zone is that we have wandered too far from the reserve. The unfamiliar terrain heightens our fight or flight reflex, and all of our energy is spent on calculating risk and our relative safety, rather than learning and progress.

The Role of Anxiety in Learning

When we’re deeply embedded in the comfort zone, we become suspicious of any hint of anxiety that might threaten our stress-free existence. Since learning exists beyond the border of our current perceived competence, it typically induces anxiety, and therefore triggers resistance. One of the founding fathers of the field of organisational psychology, Edgar Schein, believes that learning only happens when our survival anxiety is greater than our learning anxiety.

Using this proxy as a guide, leaders are faced with choosing between increasing survival anxiety (threatening job losses, or role extinction) and decreasing learning anxiety by creating a safe environment for learning and unlearning. As Schein himself put it , “If leaders really want workers to learn new things, they must educate them about economic realities in a way that makes their messages credible. When management gains that credibility, it can create the kind of anxiety that leads to a safe learning environment”

Anxiety can also act as a strong motivator under the right circumstances. Scientists Yerkes and Dodson investigated the relationship between stress and productivity. Are we too stressed to be productive, or not stressed enough? They found that anxiety actually improves performance until an optimum level of arousal has been reached. Beyond that point, performance deteriorates as higher levels of anxiety kick in. Fictional theoretical physicist Sheldon Cooper explores the Yerkes-Dodson law in an episode of The Big Bang Theory . In an effort to find his ‘optimal anxiety zone’, Sheldon enlists the help of his girlfriend, neurobiologist Amy Farrah Fowler. Amy is tasked with raising his stress levels bit by bit while measuring the impact on his problem-solving abilities. Ultimately, failing to find his optimal anxiety zone, a sleep-deprived Sheldon falls asleep to the tune of ‘Soft Kitty, Warm Kitty.’ It’s worth a watch ��

The Goldilocks Zone

It turns out that Goldilocks can teach us a lot about optimal learning. The Goldilocks Zone is that ‘just right’ zone where we feel just enough anxiety to stay motivated to learn, and just enough competence to believe we can do it! This is the sweet spot for learning – and therefore digital adoption.

“The best moments usually occur when a person’s body or mind is stretched to its limits in a voluntary effort to accomplish something difficult and worthwhile.” -Csikszentmihalyi, 1990.

Famously described and investigated by Mihaly Csikszentmihalyi, flow is characterised by deep absorption during challenging activities to the point where we lose track of time. It exists at the tipping point of frustration and boredom. Applying the Goldilocks principle, the challenge is to identify the optimal challenge for a user taking into account their current abilities – the point where a user has enough competence and confidence to take on the challenge. When we experience flow, our engagement is high, and we are intensely focused on the task. As we become more skilled, the degree of challenge can then rise to meet our newfound competence.

Flow-inducing activities allow a person to focus on goals that are clear and compatible and provide immediate feedback. If challenges are too great, we gets frustrated, then worried, and eventually anxious (Disruption). If challenges are too easy relative to skills, we get relaxed, then bored. If both challenges and skills are low, we suffer from boreout. However. if challenges are high and we have the skills to meet those challenges, we are fully engaged, and open to learning.

With the benefit of experience, Goldilocks might propose the following conditions for an optimum user experience in a digital world:

Clear expectations (what I need to do, how to do it)
A runway of Goldilocks challenges (not too frustrating, not too boring)
Self-directed exploration (allow for personalisation and meaningful choice)
Immediate feedback (rewards for achievement, how well am I doing?)

Distraction-free environment (maximum concentration, low cognitive load)New Paragraph

The Change Formula

DeclanFoster (Declan Foster) — Wed, 12 Oct 2022 12:57:09 GMT

Formulas can play a surprisingly important part in our lives. E=MC ² is arguably the most famous formula of all time, and Einstein derived it directly from his Special Theory of relativity. It states that energy can become mass and vice versa under the right conditions. This discovery ushered in the nuclear age.

We can all probably remember learning Pythagoras' theorem at school. That is, the square of the length of the hypotenuse of a right triangle equals the sum of the squares of the lengths of the other two sides. In later life, mainly if you work in finance or project management, you may have used a net present value (NPV) formula to determine whether the anticipated financial gains of a project will outweigh the present-day investment. Those working in start-ups will use many formulas, including Customer Lifetime Value (CLTV) and Customer Acquisition Cost (CAC).

However, we don't see formulas often used in organisational change management (OCM). This is perhaps not surprising given that OCM has a focus on people. The exception to this is Beckhard-Harris Change Formula. The formula was initially described in the 1960s by management consultant David Gleicher, and was further developed by Richard Beckhard and Reuben T Harris in the 1980s (Beckhard & Harris, 1987). I have seen different variations of the formula, but I generally prefer this version:

C = [ABD] > X

The basic premise of the formula is that for any change to be successful, factors A, B and D must outweigh the cost of the change (X). When we consider the cost of change, we must consider the financial and emotional costs and the friction inherent in changing something that already exists. This also includes the contribution this change will make towards change saturation in the organisation. The three key factors, A, B and D, are as follows:

A Level of dissatisfaction with status quo

B Desirability of proposed change or end state

D Practicality of proposed change

I first encountered the formula while undertaking one of my first training courses in change management in 2010. I have been surprised that it is not more commonly used; perhaps it has fallen out of favour with the OCM community. However, it has been one of my go-to tools when leading and delivering changes for organisations. It is incredible to see the value you get from bringing a project team together and merely articulating, agreeing and documenting all five elements. In my experience, the real benefit derived from the frameworks, toolkits or formulas we use is in the conversations they help structure and facilitate.

The change formula can be applied to any organisational change. Still, I feel it is particularly useful for digital adoption, i.e., when you address the people side of technology implementation.

Who Can Use the Formula?

Several roles can benefit from using the change formula. If you are a change manager or project manager tasked with introducing a new IT solution into an organisation, then you can benefit from using the formula. If you are a CIO or executive considering the impact of a new technology, e.g., Robotic Process Automation, will have on your organisation can also leverage the formula. Tech start-up founders can also benefit from the formula as it can help you understand the impact your product will have on your clients' employees and ultimately help you know if your product will be a success or not.

The initial step for a start-up to use the change formula to determine the likelihood of your product being successfully implemented and adopted in your client's organisation is to articulate all five formula elements. Can you do this for your product? You can conduct the exercise generically or ideally with a willing customer with whom you have a great relationship. The table below suggests questions under each heading to help articulate each item and get a gut feeling about whether the change formula predicts success for your product.

Questions To Ask

The following table shows you some of the typical responses you might get to these questions and the corresponding rating.

While working on technology implementations, we've often found that although the users had no overt objection to the new system, they were very comfortable with their existing system and reluctant to move from the legacy system to a new one. The user's level of dissatisfaction with the status quo was low. Low desirability (B) will occur when the features or benefits of new technology have not been clearly articulated or the 'what's in it for me?' (WIIFM) has not been made apparent to each stakeholder. Of course, there are occasions when a product is simply impractical for an organisation, either because the timing is not right or the product doesn't meet the client's requirements. This leads to the low practicality of the proposed change (D).

How To Apply It

Once you have articulated and considered all the elements, you will have a good sense of how easy your product is to adopt and identify potential blockers. Inevitably, there will be instances where using the formula will indicate a low chance of success for your product, e.g., due to low dissatisfaction with the status quo. This might suggest that your project or product is unsuitable for the context, and it is always better to know this sooner rather than later.

For start-up founders in a competitive marketplace, you need to take advantage of all the valuable tools you can to set yourself apart from the competition and grow your brand. The Change Formula is a great tool to have in your arsenal. Armed with these insights, you can adjust your product features, improve how you implement your product and adapt how you communicate about your product.

Indeed, for all technologists, whether you are a change manager, project manager, founder, CIO or CTO, I feel strongly that the change formula is a tool you should use.

Egosystems to Ecosystems | From 'Me' to 'We'

Wed, 28 Sep 2022 19:06:00 GMT

From 'Me' to 'We'

Back in the heady ’90s, Wall Street’s Gordon Gecko character became the ultimate poster-boy for unbridled capitalism, spurring an influx of ambitious Gecko-wannabes into the investment world. In the 2010 sequel, Gecko wants to start over, but ultimately finds himself edging back into play — old habits die hard. As he leaves prison having served time for insider trading, the reformed corporate raider reflects ‘S omeone reminded me I once said “Greed is good”. Now it seems it’s legal. Because everyone is drinking the same Kool Aid .”

In 2022, the shameless pursuit of self-interest is not only legal, it has become an industry in, and of, itself. The ‘me above you’ approach to business has become so deeply woven into our social fabric that we rarely question it. We see it reflected in our social media, in the rise of influencer marketing, and in mounting collective narcissism. We see it when tech investors and stock markets demand relentless and aggressive growth in engagement metrics. We see it when corporations make short term decisions that benefit shareholders at the expense of employees, customers, or society at large. And we see it in the concentration of wealth and the race for global domination of the world’s data.

How Did We Get Here?

Just over 50 years ago, in September 1970, leader of the Chicago school of economics Milton Friedman published the ‘Friedman Doctrine’ in the New York Times . In it, he put forward the argument that ‘ the social responsibility of business is to increase its profits’ . The Friedman Doctrine was significant because of its foundational declaration that ‘ a corporate executive… is the agent of the individuals who own the corporation… and his primary responsibility is to them’ . According to the doctrine, the only metrics that matter are financial, and the shareholder is the ultimate customer. Friedman’s doctrine became the normative business model throughout the 80’s, fuelling the ‘greed is good’ mantra of Wall Street and real-life financial markets.

Friedman went on to win the Nobel Prize in Economics in 1976, and has been described by The Economist as “ the most influential economist of the second half of the 20th century…possibly of all of it ”. Since then, the dot-com crash in the early ’00s and the financial crisis of the late ’00s have provided some hints that the ruthless pursuit of profit maximisation is not sustainable in the longer term, but the boom-bust cycle has done little to quell the appetite for more — more money, more sales, more attention, more engagement, more growth, more data and so on.

In a world where investors and venture capitalists demand hockey stick growth charts from their portfolio of investments, it’s easy to lose sight of what matters most: humanity itself. Growth metrics and external market expectations have historically swayed product decisions and have an outsized impact on internal decision-making. Aza Raskin, the designer behind the addictive infinite scroll feature, outlines the daily dilemma for many product teams. “ In order to get the next round of funding, in order to get your stock price up, the amount of time that people spend on your app has to go up ,” he said in an interview with BBC News “ So, when you put that much pressure on that one number, you’re going to start trying to invent new ways of getting people to stay hooked.”

The result is a hyper-competitive marketplace chasing a growth-at-all-costs strategy. The mantra of ‘greed is not only good, it’s legal’ has enabled too many tech CEOs to turn a blind eye when faced with a raft of unintended consequences and externalities.

We Are Myopic By Design

Humans are the ultimate Masters of Convenience — over the past 10 years we have turned our smartphones into our very own genie in a bottle. And while we’re hardwired for convenience, we’re also engineered for instant gratification and impulsivity. Our brains are simply not designed to make long-term decisions — always preferring sooner than later, and certainty above risk. This temporal myopia ensures that short-termism creeps into every aspect of our lives and the institutions we create. In a Washington post op-ed following the global financial crisis, former Chair of the US FDIC ( Federal Deposit Insurance Corporation), Sheila C. Bair warned of a growing obsession with short-termism — ‘ The common thread … is a pervasive and persistent insistence on favouring the short term over the long term, impulse over patience. We overvalue the quick return on investment and unduly discount the long-term consequences of that decision-making’

Not only do we engage the Ostrich effect when thinking about the future, we also make key business decisions that benefit the near-term at the expense of the longer-term. The more short-term a corporation is, the less likely they are to have breakthrough inventions or innovation, as evidenced by the low number of patents registered by these businesses. A short-term focus makes us less tolerable of risk. In his 2015 Letter to CEOs, Blackrock’s Larry Fink stated that ‘ more and more corporate leaders have responded with actions that can deliver immediate returns to shareholders … while underinvesting in innovation, skilled workforces or essential capital expenditures necessary to sustain long-term growth ’.

In Net Positive , the authors argue that leaders need the freedom and opportunity to solve big challenges, which can take many quarters of hard work. We cannot tackle climate change or growing inequality while dancing to the beat of quarterly reporting. Creating long-term value means not shooting for the moon in a given year, but investing every year to get the compounding effects and benefits of consistency over time

Expanding Our Horizons

Klaus Schwab, Founder of the World Economic Forum , raises the ultimate question “ What kind of capitalism do we want? That may be the defining question of our era”. Are we bold enough to answer that question honestly? The answer surely means changing the systems that have led us to where we are today. Technology companies, in particular, can no longer operate with invisibility, or in a vacuum. They are, increasingly, social organisms that have wide-ranging impacts on the lives of the global population.

From executives at Davos to environmentalists at non-profit groups such as the World Wide Fund for Nature, short-termism is getting bad press in recent years. The frustration is unsurprising given the evidence of how bad it is for business. In 2020, for example, the CFA Institute , the association for investment management professionals, estimated the cost of short-termism at $79.1bn a year in forgone earnings . Three years earlier the McKinsey Global Institute found that ‘long-term firms’ had 47% stronger cumulative revenue growth, than other firms, and their profits grew 81% more on average. Yet 70% of executives surveyed by McKinsey in 2020 reported that CEOs would sacrifice long-term growth for short-term financial objectives. Unbridled capitalism has a tight grip on our morality, we need to loosen its grip before we succumb to its effects completely.

Moving from a short-term outlook to a longer-term focus requires a shift in mindset from ‘ me above you’ to ‘ we above me’ . That means expanding the horizon of the business model to anticipate uncertainty and establish a tolerance to risk, to encompass a broader responsibility beyond shareholder returns, and to have an eco-system mindset to the wider impacts of leading a business in a globalised market. Perhaps, even more importantly, we need to re-examine the metrics we use to evaluate the performance of technology companies to shift towards sustainable and shared value creation that is not extractive to the ecosystem overall.

Leaders must be bold enough to break the mould in order to create a better future. In 2014, Apple announced new climate change and energy goals. When investors challenged CEO Tim Cook to commit to only do climate projects that were clearly profitable, he told them if they didn’t believe in climate change, then they should sell their Apple shares. Cook’s confidence Is backed by impressive statistics. Data shows that long-term-oriented investors deliver superior performance, and long-term-oriented companies outperform in terms of revenue, earnings, and job creation. However, despite a wealth of evidence emphasising the superiority of long-term investments, short-term pressures are difficult to avoid. A majority of corporate executives agree that longer time horizons for business decisions would improve performance, and yet half say they would delay value-creating projects if it would mean missing quarterly earnings targets.

A Way Forward

Author of the Lean Startup, Eric Ries , is spearheading a way forward for sustainable business models through the creation of the Long-Term Stock Exchange (LTSE). The LTSE is in the same regulatory category as NASDAQ or the NYSE and represents the only other way for companies to go public since the creation of NASDAQ in the ’60s. In order to be listed, companies need to commit to meeting standards that support a philosophy of long-term, multi-stakeholder value-creation. That includes taking care of their employees, their communities, and the environment. Informative public disclosures are also a key pillar of the LTSE ensuring investors are better informed on a company’s long-term strategy. ( Check out Eric Ries discussing his vision on the ZigZag podcast here )

Principles of the LTSE

Long-term focused companies should consider a broader group of stakeholders and the critical role they play in one another’s success.

Long-term focused companies should measure success in years and decades and prioritize long-term decision-making.

Long-term focused companies should align executive compensation and board compensation with long-term performance.

Boards of directors of long-term focused companies should be engaged in and have explicit oversight of long-term strategy.

Long-term focused companies should engage with their long-term shareholders.

Asana and Twilio have boldly taken a step towards sustainable growth being the first companies to be listed the LTSE in August 2021. However, the LTSE is just one brick in a new foundation for our civic society. Ultimately, we need to find ways to fund growth-oriented businesses that may not fit the hockey-stick hyper-growth charts valued by traditional venture capitalists. In a company blog titled ‘ We Spent $3.3M Buying Out Investors: Why and How We Did It,’ Buffer CEO and Founder, Joel Gascoigne, outlined his rocky relationship with traditional venture capital investment. Gascoigne details taking the decision to build towards sustainable profitability despite mounting investor pressure to grow the top line aggressively. Sahil Lavingia, founder of Gumroad , shares a similar story about turning his back on hyper-growth in favour of building a sustainable profitable business. “ I am now more focused on creating value than capturing it. I still want to have as large an impact as possible, but I don’t need to create it directly or capture it in the form of revenue and valuation” Lavingia reflects on his journey.

What's Next?

To build a future where humanity and technology co-exist in harmony, we urgently need a radical shift in thinking. I’m talking about a change that starts from the inside out and permeates every decision you take. It starts with answering the question posted by Klaus Schwab: What kind of capitalism do we want? It ends with the customers you serve and the way you serve them. There is no room for compromise and there is no space to think small. The most successful businesses are those that collaborate within their ecosystem and create value for all constituents, rather than extracting value from them.

It’s time for us to stop sacrificing our brains for short-term gains.

The Journey to Ethical Artificial Intelligence

DeclanFoster (Declan Foster) — Fri, 02 Sep 2022 18:47:50 GMT

Somebody once quipped that ethics is like the company dishwasher. Everyone is responsible for emptying it, and we all benefit from it. But the person who cares most about it will end up doing it! This is true of ethics but perhaps even more so for the more specific domain of ethics in artificial intelligence.

Ethics is a system of moral principles that affect how people lead their lives and make decisions. Ethics can provide us with useful moral maps , or frameworks that can guide us through conversations on complex issues. Ethics is more than just 'being good’. It's about fairness, treating people and other entities with dignity and respect, and behaving in ways that don't harm others. Ethics in AI's concern, according to the EU, "is to identify how AI can advance or raise concerns to the good life of individuals, whether in terms of quality of life, or human autonomy and freedom necessary for a democratic society".

I define AI as machines acting to mimic human cognition to solve problems. The most common components are Machine Learning (ML), Natural Language Processing (NLP), and Robotics. AI has made huge strides in recent years due to the availability of increased computing power, including GPUs, the exponential rise in availability of big data and the development of new algorithms. In 1996 the world was amazed when Deep Blue, an IBM supercomputer , beat Garry Kasparov, then world champion, in a game of chess. A short 20 years later, AlphaGo, a program from Google Deep Mind, defeated Lee Sedol, the strongest player in the world in the game of Go. This game originated in China thousands of years ago and was considered the Holy Grail for AI because of the infinite number of board positions. In recent years we have seen the phenomenon of large language models that can write articles, news reports, poetry and even produce computer code. The most prominent of these models are GPT-3, BERT and OPT-175B.

Parallel to the rise in the technical abilities of AI has been society's concern with whether an AI will ever become sentient or self-aware. We have come along way from ELIZA, the first chatbot developed at MIT in 1996 and intended to emulate a psychotherapist that fooled many people into believing she was human. MIT's Joseph Weizenbaum programmed ELIZA to respond to specific keywords in the typed input text. Earlier this year, a Google engineer, Blake Lemoine, claimed that Google's AI tool Lamda had become sentient.

All of the above leads to the natural conclusion that we need to focus more on AI's ethical implications in the coming years. In this article, I will consider AI ethics from four perspectives: individual, product or company, the tech industry, and society.

Individual

Whether you are a consumer using a product that uses AI or someone who is developing these tools, we all have a role to play in ethical AI. For those working in technology, I can suggest the trolley problem as a mechanism to start the conversation on their approach to ethical dilemmas. The trolley problem has been a mainstay of philosophy lectures for decades and is a thought experiment used to explore ethical dilemmas. In the scenario, a runaway trolley, or tram, is heading toward five people. You can pull a lever to divert the trolley onto a separate track, saving the five people but killing one person on the second track. How would you respond in this situation? Is doing nothing or refusing to make a decision the same as taking action? I think we can also see some obvious parallels to ethical choices faced by the AI industry when self-driving cars become commonplace.

Let's consider for a moment the example of a Machine Learning engineer who is gathering and building a data set as input into a machine Learning model. They are trying to determine how to abstract from reality, and 'abstraction from reality is never neutral, and the abstraction itself is not reality; it is a representation’ ¹ . They need to consider if the data set represents the community that it is being built for.

If you are an individual working on AI products, you might consider using the Data Ethics Canvas from the Open Data Institute. This is a tool you can download and use for free. It provides considerations and questions for any data project under the headings of data, impact, engagement and process.

Project or Product

Those working in the Tech sector also ne ed to consider the ethics of the project they are working on or the product being built. One of my favourite books from recent years is Nir Eyal's Hooked ² . In this book, he presents his Manipulation Matrix, which allows 'entrepreneurs, employees and investors to answer the question; should I hook my users on this product'? Although aimed at a general business audience, I think there are obvious applications for those working in AI.

The Manipulation Matrix is a two-by-two matrix. On the X axis, we consider whether the maker would use the product; on the Y axis, we consider whether the product improves users' lives. We then see those creators of products can fit into four categories.

Facilitator (I think this is what most of us aspire to)

Something that you would use and improve user's lives, e.g. an online education tool, an app that helps you save money or a fitness tracker, device for measuring blood sugar or blood pressure.

Entertainer

If you use the product but can't claim it improves people's lives, it is probably just entertainment. And there certainly is a place for that; think Angry Birds or even Netflix.

Peddler

When pressed, would you use your product, even though it doesn't do any harm? Think advertising or even some fitness apps, as there are so many available.

Dealer

Interestingly, in the Netflix documentary - The Social Dilemma, some Big Tech execs freely admitted that they don't let their children use social media. If you wouldn't use your product or wouldn't want your children to use it and it doesn't improve people's lives, then you may be in this category. Think of casinos, big tobacco or online gambling. Do you think they fit into this category?

Those working in AI or big tech should consider where their project or product falls on the matrix. Does it make them feel proud? Does it influence positive or negative behaviours?

The Tech Industry

Big Tech is often guilty of using the approach that it is easier to beg for forgiveness than to seek permission. A great example of this was in 2010 when Facebook controversially changed the privacy settings for its 350 million users. Mark Zuckerberg once said, "we decided that these would be the social norms now, and we just went for it."

Can we afford to leave AI ethics up to Big Tech? I think not and feel that we all have a duty to ensure we have ethics in artificial intelligence. This includes citizens, legislators, organisations and employees working in big tech.

AI will have a massive impact on society in the coming years. It is up to all of us to ensure that it is a positive impact.

In Cathy O'Neill's Algorithms: Weapons of Math Destruction ³ , she discusses the impact of algorithms on society,e.g., those used for recruitment or loan applications. There is an inherent unfairness in how these algorithms are applied. "The privileged, we'll see time and again, are processed by people, the masses by machines”. Consider the example of applying for an entry-level job at Walmart in the US, where an AI algorithm will most likely screen you. Compare this to your experience as a senior executive who has been headhunted for a Wall Street position where you will most likely get the personal and human touch. Cathy O'Neill describes the three components of a WMD:

• Opacity

• Scale

• Damage

Opacity

Even if the person knows they are being modelled, do they know how the model works or how it willbe applied? Sometimes companies claim it is their secret sauce or IP or claims the black box effect.

Scale

Does the WMD impact one use case or population, or do they have the potential to scale exponentially and impact society?

Damage

Compare the impact of an algorithm that suggests an item to buy (Amazon) or a program to watch (Netflix) with an algorithm that determines whether you get a job, qualify for a loan or even the length of prison sentence you get.

At a broader level, some claim that the ethics of the business model of some big players in Big Tech needs to be examined.

In her book Surveillance Capitalism ⁴ , the author Shoshanna Zuboff discusses what she calls "behavioural futures markets," where surveillance capitalists sell certainty to their business customers, e.g., Google Ad Words. She describes this as "a new economic order that claims human experience as free raw material for hidden commercial practices of extraction, prediction and sales”. Zuboff sees this as a significant threat to modern society that she compares to industrial capitalism's impact on the natural world throughout the 19th and 20th centuries.

How the World is Responding

In November 2021, 193 countries adopted the first-ever global agreement on the Ethics of Artificial Intelligence at the United Nations. The EU formed the High-Level Expert Group on AI in Europe in 2019. Many tech companies, facing both external and internal pressure from employees, have begun a system of self-regulation and formed internal AI ethics initiatives. And some big players have drawn a line in the sand about what they will and will not do. For example, Google has claimed it will not ' sell facial recognition services to governments .

Case Study

Before I wrap up this article, let's look at a brief case study.

Facial recognition systems, in general, have led to wrongful arrests. Clearview trawled social media sites and obtained pictures of people without their consent. Recently, Ukraine has been using Clearview AI to vet people of interest at checkpoints and identify dead Russian soldiers' bodies so they can inform their families. So, overall, are they behaving ethically? Does the context matter? Is it an ethical product?

The importance of ethics in AI will only increase in the coming years as AI becomes even more pervasive. I believe we all have a role to play in ensuring that AI is a force for good in society. What role will you play?

Reference s
1 Coeckelbergh, Mark. AI Ethics. Cambridge, Massachusetts, The MIT Press, 2020.

2 Nir Eyal, and Ryan Hoover. Hooked : How to Build Habit-Forming Products. Penguin, 2014.

3 O’Neil, Cathy. Weapons of MathDestruction : How Big Data Increases Inequality and Threatens Democracy. Broadway Books, 2017.

4 Zuboff, Shoshana. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. New York, Public Affairs, 2019.

Human Lag | What is it and how does it contribute to the Capacity Gap?

joannegriffin (Joanne Griffin) — Fri, 19 Aug 2022 18:00:31 GMT

What is Human Lag?

Lag ( verb )

a: to stay or fall behind

b: to move, function, or develop with comparative slowness

c: to become retarded in attaining maximum value

d: to fail to maintain a desired pace or to keep up; fall or stay behind

Laggy ( adjective ):

A laggy computer , computer game , or internet connection that is slow to react

We all recognise technological lag : a sluggish webpage load time, a poor connection on Zoom, or a delay in mouse response are all instantly recognisable examples that trigger the all-too-familiar feeling of intense frustration. Lag typically results when a constituent of an ecosystem fails to keep in step with its counterparts. In technical terms, there may not be enough bandwidth for an entire ecosystem to operate efficiently, or latency has developed between individual constituents within that ecosystem.

At a societal level, we experience cultural lag when society lags behind technological innovation. The term cultural lag was coined by William F. Ogburn, an American sociologist, in his book Social Change , published in 1922. The theory of cultural lag posits that culture takes time to catch up with technological innovation. The intervening period is rife with social discontent and conflict. For example, today, the rapid development of electric cars challenges the social norms around driving skills, traffic rules and ethics of road behaviours, while the supply of lithium and cobalt needed to make batteries is already raising environmental and geopolitical questions .

And, while we are adopting technologies faster than ever before , a new kind of lag is creeping into our lives impacting the ways we use and benefit from the technology available to us — we call this Human Lag . Simply put, human lag exists when innovation surpasses adaptation.

Compared to the rapid proliferation of technology, human cognition systems evolve at a relative snail's pace. The time it takes for us to process, understand and act on new information, grows longer as the amount of information we need to sift through increases. In this age of information, our cognition systems are creaking under pressure.

The length of time between when new information is received, and when we can fully take advantage of it also depends on how much mental energy we have available. Unlike modern machines with near-infinite processing power, humans have a finite budget of mental energy to pull from. When we exert cognitive effort, our brain actually consumes calories. In fact, chess grandmasters can burn up to 6,000 calories a day during tournaments, just by sitting and thinking. And just this month, researchers found that exerting cognitive effort for long periods of time can lead to a build up of toxic byproducts in the prefrontal cortex, slowing down our cognitive functioning resulting in mental fatigue!

Mental fatigue manifests as a feeling that your brain just won’t function right. People often describe it as brain fog. You can’t concentrate, even simple tasks take forever, and you find yourself rereading the same paragraph or tweaking the same line of code over-and-over again. Things that would have not have bothered you earlier in the day become more irksome as you tire out. You might find yourself impatient with colleagues or friends. Left unchecked, ongoing mental fatigue can result in burnout.

Let's dig a little deeper into some the underlying causes of human lag.

What is the cause of Human Lag?

There is more information available now than ever before in human history . This is unchartered territory. This abundance of information exacerbates the most fundamental constraint of humanity – the limits of our human cognition and comprehension. Organisational theorists David A. Nadler and Michael L. Tushman summised that information overload happens when information processing requirements exceed information processing capacity . Put simply:

If IPR > IPC = ⚠️Information Overload ⚠️

Too much information, not enough time, and poor quality of information are all significant contributors to information overload (often synonymised with cognitive overload). When we’re overloaded, we’re less effective. We might seek out easy, low-value tasks, in an effort to feel productive. We may find ourselves paralyzed, not knowing where to begin with a task. Or we might accidentally overlook important detail while overwhelmed.

Our hunger for new information can be insatiable but our ability to focus on a single task for a meaningful amount of time has become more fragile. As Nobel laureate economist Herbert Simon put it:

As our attention span continues to dwindle, we are losing our ability to focus. We are nowhere and everywhere all at once.

Multitasking is also taking its toll on our ability to focus and damaging our productivity. According to Meyer, Evans and Rubinstein , converging evidence suggests that our executive control processes have two distinct, complementary stages. The first stage is goal shifting ("I want to do this now instead of that"), and the second stage is rule activation ("I'm turning off the rules for that and turning on the rules for this"). Meyer has estimated that even brief mental blocks created by shifting between tasks can cost as much as 40% of someone's productive time.

What are the consequences of human lag?

1. Cognitive Offloading

Anyone who has ever made a grocery list, taken meeting notes, or used a calendar to keep track of their daily schedule has engaged in cognitive offloading: the process of externally recording thoughts and things to remember in order to reduce cognitive demand. Although it may seem intuitive, cognitive offloading is perhaps one of the most vital techniques used by human memory. The fallibility of our human memory has been well-documented , and offloading can be a very effective coping strategy in a noisy world, expanding the amount of information that is readily accessible to us.

Although recent technology has made offloading easy and we have become symbiotic with our smartphones and other devices, there are some drawbacks to offloading. For example, Sparrow, Liu, and Wegner (2011) had participants study trivia questions and led them to believe that the studied information would either be saved (offloaded) or would not be stored for later access (not offloaded). Participants who thought they would have access to the stored information later demonstrated worse memory for the trivia questions than participants who did not rely on technology to store the information.

2. Learned Helplessness

What happens when technology doesn’t operate as expected? Do you prise open your smartphone to replace the battery or pore over lines of code to track down a software bug? Like many, you might opt to seek expert help. The sleek design of today’s digital devices no longer encourages us to get curious about what lies beneath, while new software rarely comes with instructions never mind access to the underlying code.

Modern technologies signal to us not to tinker. As we internalise these signals, we move from conscious thinking to unconscious acceptance. Searching for a solution becomes too much effort and trying to fix it takes too much time. Eventually, we lose

the connection between the problem we’re facing and how to approach a potential solution. It’s not that we don’t know how to solve the problem; the challenge is that we no longer know which questions to ask, what outcome we’re expecting or how to get moving.

Learned helplessness can present in several different ways:

Having tried and failed yet watched others succeed, we lose confidence.
Feeling incompetent and unconfident because of failures, we give up trying.
Accustomed to instant gratification when asking for help, we can’t motivate ourselves to figure it out on our own.

This phenomenon poses challenges not only for users but also for companies who are implementing new tools and services that require more investment from employees as they grow in complexity. The more complex infrastructure gets, the

greater the threat posed by learned helplessness.

3. Impaired Decision-Making

In 1964 American social scientist Bertram Myron Gross coined the expression information overload in his two-volume work, The Managing of Organizations: the Administrative Struggle . Significantly, Gross highlighted the impact that information overload can have on the quality of decisions we make when under pressure:

“Information overload occurs when the amount of input to a system exceeds its processing capacity. Decision-makers have fairly limited cognitive processing capacity. Consequently, when information overload occurs, it is likely that a reduction in decision quality will occur.”

These days, we have coined a new phrase for this human fallibility - Infoxication . Infoxication refers to the difficulty or impossibility of taking a decision or keeping informed about a particular subject, due to the endless amount of data and content that exists on the web.

When we're unable to process the full scope of relevant factors required to make a decision, we risk making mistakes. Working with a depleted brain can cause lack of attention, increased impulsivity, and make it more effortful to combine information and understand the implications. A brain running on low energy makes worse decisions.

In the face of mounting inputs and limited time, we often revert to sub-optimal decision-making strategies:

Impetuous decision-making - making instinctive decisions too quickly without the full facts
Procrastination - taking too long to make a decision, to the point it is no longer optimal or the inflection point has passed
Decision paralysis - failure to take any action of decision due to mental exhaustion and overwhelm.
Outsource it - we avoid making the decision altogether and instead outsource it - to friends, colleagues, apps, or discussion boards.

4. Reduced Capacity for Learning

Our brains are cleverly adapting to information overload by quickly scanning information to determine if it is is important enough to pay attention to. We speed-read through blogs and articles hunting for a quick nugget to satisfy our thirst for knowledge. Rather than read a book, we snack on soundbites and other digital fast-food. This form of shallow engagement with information not only impacts our ability to think deeply, but also contributes to the illusion of knowledge.

In the world of learning, it's well understood that overloading our limited processing capacity reduces the effectiveness of learning. In the same way that having too many tabs open in your browser can slow down your computer's processing, our working memory struggles to process inputs effectively when we're overwhelmed or confused.

To learn effectively, we need to be able to think clearly - that means our attention, focus, processing speed, and memory are all working effectively. A fractious attention span, poor focus, and a cluttered mind impedes our ability to pass information through to long term memory.

What can we do about Human Lag?

While technological lag is being addressed by upgraded 5G networks, humans are not so easily upgraded (yet!). An unfocused, overwhelmed and fatigued generation could have potentially catastrophic consequences. If we fail to address the underlying causes of human lag, the capacity gap between technology and humanity will only continue to deepen.

As technology expands and accelerates at a tremendous pace, so do the risks we face. Our human limitations need to be addressed with awareness because they will continue to cause problems if they are ignored, or worse, when they are not accounted for in our design planning. The capacity gap between what we are capable of doing and what we need to do has to be bridged . We need innovative design thinking that anticipates what is coming next. This is essential for our competitive advantage today, and for our future tomorrow.

I'm excited about starting a conversation about human lag and helping our technology amplify humanity so we don't fall further behind. Connect with me on LinkedIn to continue the conversation!

Managing Stakeholders Using the SCARF Neuroscience Model

joannegriffin (Joanne Griffin) — Thu, 11 Aug 2022 18:39:41 GMT

When you think of stakeholders, what comes to mind? If you answered ‘ HIPPO s’ or ‘ people who love acronyms ’, you wouldn’t be entirely wrong. Stakeholders are usually senior-level people in organisations like function leaders, directors, and the C-Suite. Because they may be time-poor and less accessible, it can be easy to forget that they are people with unique needs and desires. Stakeholders are your customers, regardless who pays for the service, ignore them at your peril. Never underestimate the degree of influence and impact your stakeholders can have on your success!

Broadly, we can group stakeholders in three categories: those who are impacted by the initiative, those who can influence or affect the initiative, and those who perceive themselves to be impacted by the initiative. Each group may have the ability to make or break the success of your product. In Humology , we outline how to identify, assess, engage, and manage stakeholders. In this article, we’ll discuss how understanding what makes each stakeholder tick, and identifying their individual needs as well as their commonalities with other stakeholders, are they keys to effective stakeholder engagement. The SCARF model can help you do just that.

Read on to find out more...

"Resistance is thought transformed into feeling.

Change the thought that creates the resistance, and there is no more resistance"

Robert Conklin

What is the SCARF Model?

Neuroscientist Dr David Rock co-founder of the Neuroleadership Institute, developed the SCARF model almost 15 years ago. Based in neuroscience research, the model implies that five key social domains activate the same threat and reward responses in our brain that we rely on for physical survival. Based on how we perceive ourselves to be impacted in each domain, we interpret an initiative as either a threat, or a reward. If we feel threatened, we will pull away from the initiative, whereas when we detect a reward we move towards the initiative. Think of these opposing forces like magnets pulling your stakeholders in either direction.

The first initial of each domain makes up the acronym S, C, A, R and F of the model.

Status: How we see ourselves and how others see us. How do we perceive our relative importance in relation to others.
Certainty: How confident we are about the future. Can we see the outcome(s) clearly? Do we feel in control of our destiny?
Autonomy: How much control do have over the situation or outcome(s). Do we agency to make meaningful choices?
Relatedness: How connected do we feel to others. Do we feel psychologically safe?
Fairness: How reasonable do we feel we have been treated, or how fair do we perceive the situation to be in general?

Threat or Reward?

When the brain detects a threat, our sympathetic nervous system is activated, triggering a ‘fight or flight' response. Cortisol ( the stress hormone ) is released – this hormone increases blood sugar and suppresses the immune system so energy can be redirected to address the perceived threat. When cortisol gets pumping, our creativity and productivity are negatively impacted. We literally can't think straight and act on instinct.

Adrenaline also kicks in to increase our heart rate, dilate the bronchial passages, and restrict blood vessels - this is to increase oxygen to the lungs and blood flow to muscles to prepare for the fight. When we feel our mouth go dry and our palms become sweaty, our sympathetic nervous system is hard at work! Our reactions can be emotional, instant and often uncontrollable – a twitch, a snide remark, an eye-roll, or a sigh before we’ve had enough time to moderate our behaviour!

Research has shown that a threat response can stimulate the same region of the brain as physical pain. Being left out of a group, or treated differently from our peers might be interpreted as a threat to our status, social standing and relatedness. We are literally hurting!

On the flip side, when we feel accepted, secure, confident and involved, our brains process these feelings as rewards, triggering the release of dopamine ( the happy hormone ). As we digest a proposed change, we run through a script on our head that determines (or even triggers) our immediate and primal reaction:

The five domains of SCARF affect us all differently, but almost every stakeholder will have some level of sensitivity to one or more of these factors.

The SCARF model can help you to identify which stakeholders may be sensitive to a particular factor so that you can manage their needs appropriately.

Managing Stakeholder Groups with SCARF

The SCARF Model is a useful tool to help us to reflect on the ways we might unintentionally threaten and undermine important stakeholder relationships, and to think intentionally about how to maximise psychological safety and reward for healthy working relationships. It's certainly worth becoming familiar with the wide range of potential psychological and social threats that create avoidance behaviors in others. Learn to spot threats early. Become sensitive to them so that you’re less likely to unintentionally create threats that demotivate others and cause unnecessary roadblocks for yourself.

Let’s walk through an example. Our latest product, and AI-enabled automated Applicant Tracking System (ATS), is being implemented at a medium-sized organisation. The identified stakeholder groups might be as follows:

Taking the time to consider and understand how each stakeholder group might react to a new initiative will greatly increase your products chance of success and adoption. Looking at each group individually through the lens of the SCARF model will likely uncover silent objections, attitudes and challenges you hadn't even considered. Stakeholder management is vital to your core success, as stakeholders who feel safe and supported are more likely to be effective and influential.

For each stakeholder group identified above, capture (or anticipate) their reaction and perspective across each of the five key domains of SCARF. For example, the CHRO’s profile may look like this:

Based on the positive interpretation of the initiative from the perspective of the CHRO, a visual SCARF profile for the CHRO (Project Sponsor) might look like this:

At work, this person will show up as enthusiastic and engaged. In their eyes, they have much to gain and little potential downside.

Now let’s take a look at how another stakeholder group might react to the proposed initiative. How might Hiring Managers feel about using a new system?

While this stakeholder group may not appear visibly resistant to change, scratching the surface of how they might perceive this proposed initiative shows us that we may need to consider their needs a little more to ensure they are motivated to move towards the change.

This is where the SCARF model really shines when combined with stakeholder management. At a very early stage you can anticipate, and plan for, concerns and objections from each stakeholder group. If we look at the hiring manager perspective, we can plan to add more clarity to what’s expected of this group. We might decide to involve some early adopters in the process, and plan some training based on their experiences. We could increase the feeling of autonomy by creating a feedback loop, or inviting early questions and concerns. Lastly, it might also be beneficial to reassure hiring managers that the purpose of this initiative is to improve their experience and relationships with their TA partners by removing admin, providing visibility, and freeing up time to add more value to internal customers.

Stakeholder Heat Map

When this exercise is completed for all stakeholder groups, the output provides a comprehensive picture of what challenges may lie ahead on this particular project or initiative. Now that we know the obstacles to avoid, we can begin to address them one by one. We've developed a handy SCARF workbook to help you navigate the process with ease - you can access it here

Even a cursory glance at the heatmap highlights potential resistance from the Hiring Manager stakeholder group, as well as some potential dissatisfaction within the Prospective Employee groups. Being aware of potential pitfalls ahead of time means you can adjust course slightly to accomodate and address the individual needs of each stakeholder group.

Summary

The SCARF model is a useful and effective tool for managing stakeholders. Whenever you have multiple stakeholders that can influence the success of your product or project, it’s easy to forget that they’re individuals with their own needs and desires. Using the SCARF model can help you to better understand what makes each stakeholder tick, and identify their individual needs as well as their commonalities with other stakeholders. The Stakeholder Heatmap can help you turn potential detractors into advocates – removing blockages and noise from sales channels and paving the way for the successful adoption of any technology product.

What Can Change Management Learn from Behavioural Economics?

DeclanFoster (Declan Foster) — Sun, 31 Jul 2022 13:36:15 GMT

Change management is a discipline that has borrowed quite successfully and rightly from other disciplines, including psychology, coaching, management consulting, project management, counselling and data analytics. I believe change management can also learn a lot from behavioural economics. If change management and behavioural economics were to meet at a party, they'd have a lot to discuss!

I want to share my thoughts on how you can use fundamental theories and wisdom from behavioural economics to sharply increase your success rate when making significant changes in your organisation. As part of our research for our book, my co-author and I completed a course in Behavioural Economics from Rottman University in Canada. The course provided me with fascinating insights into the behavioural economics theories that explain the difference between what people should do and what they end up doing when making economic decisions. I was struck by how many of these insights we could apply to change management.

Behavioural economics combines economic and psychological principles for understanding how people behave. It differs from neoclassical economics, which assumes that most people have well-defined preferences and make selfless decisions based on those preferences.

Humans are complex and multifaceted, and the field of behavioural economics is devoted to revealing our vulnerabilities and strengths. Behavioural economists ask us to think laterally about how we could influence behaviour through the right combination of incentives, processes and strategies. By understanding our cognitive biases and other psychological quirks, we can improve our decision-making and benefit from more effective and efficient use of our time and resources.

Before we get into the details, I think it is helpful to explain the distinction between behavioural economics and behavioural science, as these two terms are often conflated or misunderstood. We can consider behavioural science an umbrella term covering all biological and social studies of human behaviour. This discipline includes psychology, sociology and cultural anthropology. Behavioural economics is commonly seen as a sub-science under behavioural science because it uses methodologies typically derived and influenced by behavioural science studies like social psychology.

Richard Thaler is considered by many to be the grandfather of behavioural economics. He received the Nobel Memorial Prize in Economic Sciences in 2017.In Nudge, the bestselling book he wrote with Cass Sunstein, the authors introduced us to econs, choice architecture and nudge theory.

Central to behavioural economics, and what sets it apart from traditional economics, is the concept of econs. Thaler's criticism of conventional economics is that it sometimes assumes that humans are entirely rational creatures, or econs, who always make logical choices in their best interest. By contrast, when making decisions, ordinary people are influenced by many factors when they make economic choices, including biases and defaulting to heuristics or shortcuts.

How often do we assume that stakeholders will always react rationally in change management? Individuals don't decide in a vacuum; their response to change is determined by the nature and consequences of the change, the organisation's history with changes, the type of individual, and their experience of previous changes. Perhaps when we encounter what we perceive to be resistance to change, we should consider if the person's response is entirely rational for them, given their context.

What is Choice Architecture?

Choice architecture Is 'organising the context in which people make decisions' ¹ . We can see examples of choice architects in our everyday lives. A doctor outlining possible treatments to a patient, a personal trainer describing different exercise options to a client, and an HR professional designing a form to enrol new hires into the company pension scheme are all examples of choice architects.

Similarly, change managers often fulfil the role of the choice architect. When we discuss or present our change initiative, we provide a choice to our stakeholders, whether we realise it or not, to either engage or disengage with the change. We present options to stakeholders, so we need to organise the context in which stakeholders make decisions. Thaler has listed six principles of good choice architecture:

Incentives
Understanding mapping
Defaults
Give feedback
Expect error
Structure complex choices

Intro to Thalers Nudge Theory

Nudge theory is based on a book of the same name, written by Cass Sunstein and Richard Thaler. It focuses on how positive reinforcement and social norms can be used to influence people's behaviour. For example, rewarding someone for something they do can encourage them to repeat the same behaviour in the future. Behavioural economics uses choice architecture to nudge people towards desired behaviour without the use of law or monetary incentives. The fundamental principle is that design decisions can influence decisions even in the absence of heavy-handed regulation. Nudges are subtle ways of getting people to take action. We can consider them "softbargains" because they're not edicts or demands. A significant reason nudging is so compelling is that it encourages people to think for themselves. You're giving them the tools to critically examine the choices presented to them and make the best decisions possible.

Social Nudges

Thaler has highlighted three social nudges that we can also utilise in our change management activities. These are peer pressure, information and priming.

Humans are social creatures, and those around us influence us. We can leverage this by informing our stakeholders about what their peers are doing ,e.g., how many people in the organisation are using the new procedure or have logged into the new IT system. I like to present these details visually in an interactive dashboard on the change initiatives I lead. Change champion networks can also lead the way when leveraging peer pressure. Introducing a social element to your change via Slack or MS teams channels can also help.

Invest the time to ensure that your stakeholders have access to all the information they need and that it is easily accessible. While the change may be the key focus for the change or project team, it will probably be just one of several priorities for most of your stakeholders.

Priming occurs when an 'individual's exposure to a particular stimulus subconsciously influences their response to a subsequent stimulus'. Studies have shown that we are greatly influenced by what we hear, see and read. Change professionals and leaders must be mindful of our language when discussing a change initiative. We should craft key messages carefully, acknowledging that we need to be upfront and honest. When we veer into spin it is easy to lose the trust of our stakeholders.

As humans, we have limited cognitive resources. Every day, we make thousands of different decisions, and our brains conserve energy by using shortcuts to respond quickly. This means that the world is perceived through pre-set lenses rather than a clear one in some cases.

The term "cognitive bias" refers to systematic errors in thinking people make when processing and interpreting information around them, which affects their decisions. A heuristic can be defined as a shortcut or rule of thumb that simplifies decisions. They are used in scenarios where there's an uncertainty, and they involve substituting difficult questions with easier ones.

The Cognitive Bias Coda , available online, lists almost 200 biases affecting our actions and thoughts. While I am not suggesting we need to consider all of these, it can serve as a valuable checklist for significant biases we may want to consider when designing our change interventions.

In their 1974 paper 'Judgement Under Uncertainty: Heuristics and Biases', Amos Tversky and Daniel Kahneman highlighted three critical heuristics; anchoring, availability and representativeness.

Anchoring is the human tendency to first rely on and assimilate new information with whatever they have been exposed to, often setting the tone for all subsequent decision-making. I leverage the anchoring bias on my change initiatives by utilising Simon Sinek's Golden Circle model. When presenting a change or developing key messages, I start with the 'why' of the project before explaining the 'how' and the 'what'. This ensures that stakeholders are anchored to the why before hearing about the how and the what

The availability heuristic is a cognitive bias in which you form opinions based on recent or readily available examples, even if they are not representative of the topic. Suppose you read several reports in a newspaper about burglaries. In that case, you might assume that burglaries are far more common than is the case in your locality. Similarly, a stakeholder might hear a few negative comments about your change initiative and conclude that there is a widespread negative view of the change within the organisation.

The representativeness heuristic is a mental shortcut that we use when estimating probabilities. We often assess how likely something is by determining how similar it is to a prototype that already exists in our minds. For example, a stakeholder might evaluate your project based on their experience of the most recent change they have gone through.

Kahneman has pointed out three biases that are also useful for a change management professional to consider; optimism/overconfidence, loss aversion and the status quo bias.

As change management professionals, how often do we underestimate the duration or complexity of a task? Or perhaps we have worked alongside project management peers who can sometimes underestimate the costs and duration of projects. In addition, I think we all are aware of or have seen first-hand circumstances where a change sponsor has overestimated how enthusiastic stakeholders will be to a particular change initiative.

Loss aversion is a cognitive bias that makes individuals feel the pain of loss twice as intensely as they do the pleasure of gain. As a result, people often try to avoid losses in any way they can.

As change management professionals, we need to acknowledge the losses people may feel about a change initiative and articulate and emphasise the positive or gains. One way of doing this is to effectively communicate the WIIFM (What's in It for Me) to all of our stakeholder groups.

The status quo basis is arguably the most critical bias that change management professionals need to be aware of and address. This bias explains our strong preference for the current state and can manifest as resistance to change. Occasionally, I needed to nudge my impacted stakeholders out of their status quo bias on some of the change initiatives I led. Sometimes I have been fortunate enough to have a burning platform to point to, and other times, I have used a combination of various change interventions and coaching to move people out of this bias. This bias also underlines the importance of sustaining or reinforcing activities to prevent impacted stakeholders from slipping back into old processes or systems after the focus and excitement of the change have elapsed.

If we choose to apply choice architecture or nudges on our change initiatives, we need to pay extra attention to being empathetic and respectful of our impacted stakeholders. Without this we are in danger of straying into manipulation.

Practical Steps

So, what are the practical steps change managers can take to start to leverage the principles discussed in this article? I recommend you start by taking a deep dive into the works of Thaler, Kahneman and others, as I have only scratched the surface in this article. Then download the Cognitive Bias Coda and determine which of these resonate with your current change initiative challenges. After that, you are ready to start designing nudges for your change initiative. The Rotman School of Management at the University of Toronto have produced an excellent practitioner's guide to nudging . The guide takes you through a detailed process for developing nudges that include four steps; map the context, select the nudge, identify the levers for nudging, and experiment and iterate. I particularly appreciated their process for identifying bottlenecks for your nudges.

Change management is an ever-evolving discipline which is one of the reasons that I find working in it so exciting and rewarding. I hope you will find that you can add the concepts discussed in this article to your change management toolkit.

References
Thaler, R. H. and Sunstein, C. R. (2008). Nudge: Improving Decisions About Health, Wealth and Happiness. Caravan Books.

Sponsorship: Conducting Your Change Initiative

Sun, 31 Jul 2022 13:02:12 GMT

“No one can whistle a symphony. It takes a whole orchestra.”
H.E. Luccock

It takes an entire orchestra to play a symphony, under the leadership and guidance of a conductor. This is much like the need to have a cohesive and effective team to implement a change initiative into an organisation. This team too needs leadership and this is where effective sponsorship is brought to the fore.

The role of change sponsorship is often misunderstood, both by those who support the sponsor and by those who take on the mantle of the sponsor. In this article, I will define what a sponsor is, why the role is so important, the keys to being an effective sponsor, and the WIIFM for a sponsor.

What is a Sponsor

In Prince2 project management methodology, we have the role of the Executive, whose role is to “ensure that the project is focussed throughout its life on achieving its objectives and delivering a product that will achieve the forecasted benefit.” The MSP (Managing Successful Programmes) methodology includes the role of Senior Responsible Owner, who is “accountable for the programme, ensuring that it meets its objective and realises the expected benefits. The individual who fulfills the role should be able to lead the programme board with energy and drive and must be empowered to direct the programme and take decisions. They must have enough seniority and authority to provide leadership to the programme team and take on accountability for delivery.”

Agile projects have the role of Business sponsor, who is “the most senior project-level business role. The Business Sponsor is the Project Champion who is committed to the project, the proposed solution, and the approach to delivering it.” Prosci refers to the Primary Sponsor as “typically the senior manager or executive that initiated the project.”

What is common among all these definitions is that we are talking about one person. In my opinion, the role of the sponsor cannot be shared by two people or by a committee, nor can it be delegated. There ultimately has to be one person who is accountable for the success of a change initiative. Confusion sometimes occurs when we talk about sponsorship or guiding coalition, where we are referring to local sponsors whose role is to assist the sponsor or primary sponsor. They are there to assist the sponsor and are not accountable for the success of the initiative.

Why It Is Important

In Prosci’s benchmarking report Best Practices in Change Management participants consistently place active and visible executive sponsorship at the top of their list of contributing factors for a successful change initiative. Participants in these studies also state that although executives were willing to step up to this role, many did not fully understand and appreciate the expectations.

How to Be an Effective Sponsor

Vision : Have a clear and articulated vision of how the future will be different from the past and the impact on each stakeholder group.
Active and Visible participation : A good sponsor will be visible throughout the change initiative; you can’t just make an appearance at project kick-off and then not be seen again until the go-live celebration! Commit to being visible e.g. agree to attend one project stand-up meeting per week.
Build a Guiding Coalition : For any significant change to be successful you will need the support of your peers and colleagues throughout the organisation. Identify who these key stakeholders are, whether they support, are neutral, or oppose your change and how you can either influence their opposition or leverage off their support.
Communicate Directly & Consistently with Impacted Employees : They will want to hear from the sponsor on how the change aligns with the organisation’s strategic goals and culture. In my recent LinkedIn survey, communicating consistently was voted as the top focus for a sponsor.
Team : Surround Yourself with an effective team. This includes having appropriate project management and change management expertise to support you. I quite like how Prosci’s Project Change Triangle (PCT™) model illustrates how change management, project management, and leadership/sponsorship are three elements that are equally important and need to be given an equal focus for a change initiative to be successful.

A project manager should manage the day to day activities of the project on behalf of the sponsor. A change manager will ensure that the people side of the change is not neglected and the change is accepted, adopted, and embedded into the organisation. A change manager can also support the sponsor by assisting with identifying, mapping out, and managing of the sponsorship coalition. Also, the change manager can prepare a sponsor roadmap for the sponsor which outlines all of the expected activities for a sponsor e.g. events, communications, etc.

Top 5 Common Mistakes

Bandwidth : Sponsor takes on too many projects, underestimating the time commitment and effort required to be an effective sponsor.
Delegation : Sponsor delegates responsibility to a project team, project manager, or even an external consultant.
Understanding of Role : The sponsor doesn’t fully understand the role e.g. might feel that it means being a figurehead for the project.
Skills : The sponsor may not have the required experience or skills for the role. In this case, they should lean on the project manager, the change manager, peers, or a mentor for support and guidance.
Influence : The sponsor is reluctant to use influence to help manage resistance.

The WIIFM for a Sponsor

When an executive is asked to step into the role of a sponsor, they may ask themselves, what’s in it for me? Stepping into the role of a sponsor can be a great career move, especially for those new to executive or leadership positions. You often get the opportunity to communicate and engage with employees at every level throughout the organisation. Those peers that have supported you as part of your guiding coalition will in turn look to you to assist them in their sponsorship roles, helping the sponsor to build up their network. Being a sponsor also often gives you exposure to the senior leadership team and CEO.

As the pace of change in organisations will only increase in the coming years the importance of effective sponsorship will increase. Just like our conductor, sponsors need to practice these skills so effective sponsorship becomes a core competency.

Change Managers and Project Managers: Two Sides of the Same Coin

Sun, 31 Jul 2022 12:50:09 GMT

If you are a change manager and you have ever found yourself in a role where the scope and focus of your role was confused or overlapped with a project manager role, or vice versa, then this article is for you. Change managers and project managers regularly have to work side by side to deliver a project or achieve a successful transformation. Problems can, and do, arise where this is misunderstanding or confusion about their roles and responsibilities.

This can happen for various reasons including; when there is a lack of understanding about the role of the change manager, where the organisation assumes that a project manager can perform both sets of tasks, where there is a significant disparity in seniority or experience of those in the roles or where a sponsor doesn’t understand how to get the most out of both roles. I quite like how Prosci’s Project Change Triangle (PCT™) model illustrates how change management, project management and leadership/sponsorship are three elements that are equally important and need to be given equal focus for a change initiative to be successful.

To achieve this, we first have to have a clear understanding on the difference between the roles and skill sets of change managers and project managers. In this article I will explain the key differences between the two roles under the headings of; expertise, reward, how they influence, the ideal environment for them and how they view an organisation. I will also have a look at what they have in common and how they can best work together.

In order to flesh out the differences between the two roles I have inevitably had to make some generalisations. The intent of the article is to provide my perspective and to stimulate conversation on the subject.

Expertise

Project Managers have expertise in facts and figures. They deal with ROI, risks and issues, the business case and the project deliverables. The change manager will have expertise in perceptions and emotions i.e. how are impacted stakeholders perceiving the change and how it affects them and how are they responding emotionally to the change. The change manager may use consultation, interviews and surveys to identify these perceptions and emotions.

Reward

Project managers are generally recognised and rewarded for delivering the project on time, to budget and to the agreed scope whereas the change manager will be rewarded for the change being accepted, adopted and embedded into the organisation. This difference can manifest itself clearly at project closure where a project manager will, quite rightly, be expected to close down a project as quickly as is practical after project go live and a period of go live support. This allows resources to be freed up to be returned to the business and for contracts for external resources to expire i.e. for the business not to incur any additional unnecessary costs. Ideally, the change manager will stay with the impacted business unit for a period of time after go live to ensure the change is embedded. In my experience, this tends not to happen when this additional time is not factored into a project budget at the outset.

Influencing

The project manager will rely more on authority to influence whereas a change manager will rely more on building coalitions to influence and achieve a change. A project manager might have authority over business analysts or subject matter experts who report into them in a project organisation structure. A change manager might assist a project sponsor to identify, develop and manage a guiding or sponsorship coalition. They might also manage a network of change champions or agents to assist in achieving a change.

Ideal Environment

Project managers will tend to shine and perform at their best in an environment where there is predictability and certainty. For example, they may underperform where the goalposts are moved i.e. where there is change and uncertainty on the project deliverables. On the other hand, a change manager should excel in an environment of unpredictability and ambiguity by providing a steady hand on the tiller. This is particularly useful where an impacted group is not used to the inevitable ups and downs of the change or project lifecycle.

How They View an Organisation

A project manager will tend to adopt a hierarchical view of an organisation e.g. by relying on organisation charts. While this is a valid perspective, the change manager will also view the organisation as a network of intersecting groups and individuals who are impacted by and can influence the change effort.

What They Have in Common

While there are distinct differences between the two roles, they also certainly have quite a lot in common. Both change management and project management are professions but also can be considered both a body of knowledge and, arguably, a leadership and management competency. Both professions are represented by professional organisations. For project management these include the PMI (Project Management Institute) and the APM (Association for Project Management). For change management these include The Change Management Institute and the Association of Change Management Professionals. Both roles are accustomed to the temporary nature of projects or change initiatives. In contract roles, they both will be accustomed to moving from organisation to organisation. In permanent roles they will be accustomed to moving from business unit to business unit or project to project.

When we recognise, appreciate and leverage these different skill sets, I believe that both project managers and change managers can add more value for their clients. Then organisations will see that the whole is greater than the sum of its parts.

The Capacity Challenge

joannegriffin (Joanne Griffin) — Fri, 29 Jul 2022 14:18:49 GMT

A Growing Infodemic

In 2009, the New York Times reported on a study that found that the average American consumed around 34GB of data and information each day, representing an increase of 350% over nearly three decades. That's the equivalent of consuming around 100,000 words every single day (about 2 books per day, or 2 words per waking second!). Back in 2009, information was predicted to grow at 6% per annum - that was before iPads, Kindles, Chromebooks, iMessage, Minecraft, Instagram, Snapchat, Twitch, Slack, Alexa, TikTok and many more technological developments of the noughties were even in our sights.

Since that report was issued, scientists estimate we consume an average of 74GB a day (the equivalent of 16 movies), internet users have more than doubled from 2.18 billion to 4.95 billion (or 62.5% of the world's population), and social media has seen explosive growth. Today's total of 4.62 billion social media users is 3.1 times higher than 10 years ago and continues to grow at 13 new users every single second !

Research from the GWI reveals the a 'typical' global internet user now spends almost 7 hours each day online, of which 50% is spent on a smartphone. Assuming we spend 8 hours per day sleeping, that's 44% of our waking time spent online - a statistic that has increased by 4 minutes per day (1%) over the past 12 months. 4 minutes per day across 4.95 billion internet users amounts to 5 billion additional hours spent online in 2022. When we're online we spend around 2 and a half hours engaging in social media - watching videos on YouTube, catching up on our social feeds and sending messages. (Interestingly, we spend over 52 hours per month across Meta platforms).

We still have only 24 hours in every day, and largely the same brains we've always had. How do human brains deal with this challenge?

Thankfully, our brains are built to learn and adjust to a changing world. We learn to tune out unimportant details and focus our attention spotlight on the things we deem important and relevant to us. It's how we deal with background noise while we work, or tune out other voices to focus on a single conversation in a crowded room. This impressive filtering system is working overtime to tune out the myriad of alerts and notifications vying for our limited attention.

Yet even after we've managed to filter through the noise to find something worth paying attention to, our working memory acts like a gatekeeper to accessing the long term storage capacity in our brains. Our working memory can only process so much information at any one time - essentially creating a bottleneck in our cognition process. A large part of the exhaustion we feel at the end of the day is due to how slowly we absorb information. We process less than a fraction of 1% of the information we take in each day. And it gets worse when we multitask.

Data, data everywhere, but not a minute to think

Every day 333.2 billion emails are sent, 867 million Tweets are tweeted, and 23 billion text messages are sent. A relatively new phenomenom, machine-generated data accounted for 40% of all internet data created in 2020. The only way for us to deal with information overload is to process these inputs simultaneously. How many of us listen to music while working, answer IM's while on a Zoom call, or scroll through social media while watching television? In an effort to keep up with the deluge of information, we have become a nation of multitaskers. We snack on quick bytes all day long, and yet never feel satiated. And yet, we're always hungry for more - our eyes are bigger than our bellies. How many bookmarked articles go unread, how many books gather dust on our shelves, and how many of our best ideas get relegated to the end of our to-do lists?

Between new technologies and our daily media consumption, the volume of information is expanding way beyond our brain’s capacity to process it. Our appetite for knowledge far exceeds our ability to digest it.

"A Wealth of Information Creates A Poverty Of Attention" ~ Herbert Simon

At what cost?

When we multitask, we tend to consume from a firehose of data via multiple sources. Like scrolling through Instagram while watching Netflix, and snacking at the same time — our attention systems grow weary. In a fatigued state, we can no longer separate the trivial from the important. We might remember the details of JLo's latest wedding, but forget the essence of an important meeting we just attended. As we continue to consume simultaneous streams of inputs from the world around us, we tell ourselves we're getting better at multitasking. However, neurosciencists now understand that when we multitask we're not actually doing two things at once, we're actually switching our attention back and forth between each task. Constant context-switching damages our focus and erodes our productivity.

At work, our productivity is further eroded every time we switch between apps, or search for a document . Industry research conducted by firms such as McKinsey & Company, in its report “The social economy: Unlocking value and productivity through social technologies,” and Gartner, in “Improving the Employee Experience Improves the Customer Experience,” has revealed that that the average employee spends an estimated 6 to 25 hours per month searching for information. Often times it can feel like we're running to stand still!

Daniel J. Levitin , cognitive neuroscientist and author of The Organized Mind: Thinking Straight in the Age of Information Overload explains what's happening biologically as we fragment our attention in an effort to keep up: “Making decisions is incredibly labor-intensive for the brain. Neurons are living cells that require oxygenated glucose to function. We burn up that glucose when we ask the attention systems of the brain to rapidly shift from one thing to the next.” We're burning energy just to keep pace in a noisy world.

Once we use up our mental energy, the tank is empty. Pushing through this neural fatigue and running on empty has become a norm is modern society. Leaving little opportunity to refuel through rest and recharge has a significant impact on our cognitive abilities. Is it any wonder that many of us feel exhausted or overwhelmed. Our attentional filter is under attack for most of our day.

The Capacity Gap

As technology's evolution continues to march on unfettered, we're busy addressing the emerging consequences of the rapid technological evolution of the past two decades. Just when we need the full power of our brains to solve our planet's most complex and pressing challenges we are experiencing a burnout epidemic. Meanwhile the tech world is racing forward with the next iteration of the Web.

When technological evolution continues to outpace human evolution, the result is ‘human lag’. We experience lag when we feel overwhelmed and unable to keep up with the impact emerging technologies has on our lives.

Left unaddressed, the gap between humans and technology could quickly widen to form a chasm. We need to increase the human curve to meet the technology curve. To do so, we must protect the human capacity to adapt and acquire new skills. The design of digital solutions can optimise for learning and information diffusion, while promoting flow and replenishment. Technologists can also help eliminate unnecessary change and disruption by creating digital solutions to human problems in a more thoughtful manner. Will you join us on the journey towards Humology ?

In a world where technology empowers rather than disrupts humanity – we all win.

The Productivity Paradox

Tue, 08 Mar 2022 15:32:00 GMT

“You can see the computer age everywhere but in the productivity statistics”
Nobel Laureate in Economics, Robert Solow (1987)

For all of the headlines about technology’s ability to make us more productive, we seem to be working more hours — not less. And while we feel busier than ever, it’s hard to avoid the feeling that we’re not getting very much done. How can that be? Why is it that in spite of all these advances, we end up working harder than ever?

Could it be that technologies have increased efficiency in many areas, pushing more and more information at us? However, we only have 24 hours in a day and we can only deal with so much information — are we becoming a bottleneck?

When email was introduced on a wide scale in the mid-1990s, we anticipated a productivity boon from replacing phone calls, faxes and even paper memos. But as email use became more widespread, the volume of our communications exploded. We ‘talked’ more than we ever had before, we embraced email like playing a game of tennis, desperate to keep the ball in play. Instant messaging made it even easier to communicate in ‘real-time’— we now play tennis at the speed of ping pong — costing us 10 valuable IQ points as we try to keep up.

In ‘ A World Without Email ’, Cal Newport poses the question:

While we’re adopting new technologies faster than ever before, the promise of productivity has not, yet, materialised. So what’s really going on?

Frequent disruptions from incoming messages have taken a toll on our ability to focus - having a bigger impact on our ability to produce valuable output than we may realise. In fact, unnecessary meetings cost business $37bn in the US alone ! News headlines tell us everyday that we are becoming increasingly distractable and inattentive — with social media shouldering much of the blame. I don’t think it’s that simple. As with most complex problems, there’s rarely a single root cause.

The Lag Effect

Traditional structures, processes and mindsets create friction when introducing new technologies. Many organisations are rebuilding the plane while flying it, leaving many of us doing the ‘day job’ alongside implementing new tools and technologies. Faced with a Pandemic and accelerated digital transformation, is it any wonder we have an overwhelming sense of can’t even!

Hammer, Meet Nail

To a man with a hammer, every problem resembles a nail. Choosing the wrong tool for the job is perhaps one of the more significant drains on corporate and employee productivity. If we want to derive enormous value from the technologies at our disposal, we need to improve our matchmaking skills. We need to spend more time understanding the needs of the nail and pairing it with the right hammer for the job ( you get the gist! )

A recent study found that a lack of managerial and ICT skills, along with ‘poor matching of workers to jobs’ was hampering digital technology adoption. What use are these great new tools when we neither have the skills, time, or attention span to deploy them for our own benefit?

Free Falling

Platforms like YouTube, Facebook (and even Medium!) offer us unlimited shelf space for our content — so we fill it up because these days free means we are no longer using traditional currency to measure value. These days, you can make money giving things away. There really is such thing as a free lunch, and sometimes you can even get even more than you pay for.

Not only does this mean we have more stuff vying for our attention, but our current productivity measures do not take into account the gargantuan market of ‘bartering’ human attention for free content. We might reasonably argue then that economic measures of productivity need to be updated to properly represent today’s realities.

Improving organisational transformational capabilities, smarter matchmaking between technology solutions and corporate challenges, and a fresh look at how we measure productivity might provide us with some much-needed room to breath.

What is the cost of all that distraction? In 1971 the psychologist Herbert A. Simon presciently wrote, “ The wealth of information means a dearth of something else . . . a poverty of attention .” Research tell us that attention and focus are the raw materials of human creativity and flourishing. In the age of increased automation, the most sought-after jobs are those that require creative problem-solving, novel solutions, and the kind of human ingenuity that comes from focusing deeply on the task at hand.

When we’re distracted, we deplete one of our most valuable uniquely-human skills: our ability to think profoundly, solve puzzles, make connections, and do deep work. Not convinced? Take a look at how distractions enabled by technology can impact ourcognitive capacities:

Over to you — has technology delivered on its promise to save us from burnout and overwork? What can we do to capture the benefits that technologies have to offer us, and what will we do all that extra cognitive downtime?

References:
[1]Erik Brynjolfsson: The Productivity Paradox of Information Technology: Review and Assessment

[2] Cal Newport, A World without Email, 2021, Penguin Random House LLC

Hacked, Hooked or Harvested? Change is coming…

Wed, 20 Oct 2021 17:48:00 GMT

I’ve been fascinated with how our relationship with technology is evolving over the past 20 years. By far the most intriguing aspect of this relationship is the power we willingly hand over to technology companies. Throughout the debate about ethical AI and tech, we cry foul at Zuckerberg and his kin for abusing the power we gave them, dishonouring the trust we so freely offered, and making huge amounts of money without so much as a token offered to us for our loyalty.

BJ Fogg coined the term ‘Captology’ as an acronym based on the phrase ‘ C omputers A s P ersuasive T echn ologies ’ — Captology focuses on the design, research, and analysis of interactive computing products created for the purposes of changing people’s attitudes or behaviors.

The essence of a persuasive technology is in its interactivity — the ability to adjust the psychological influence tactics along the user journey. These days we call this personalization, or my preferred term individualized curation.

The Cost of Curation

The world is becoming increasingly noisy with millions of shiny objects vying for our limited attention every minute. Curation is simply a coping mechanism in a world where our eyes and attention have become a currency all of their own. In an effort to prevent overwhelm, we have drafted in outsourced help offered by Netflix recommendations, Amazon ads, Facebook suggestions, recommended Tweets, LinkedIn newsfeeds and TikTok trends, without costing us a cent. Sounds like a good deal, right?

Assuming these platforms have our best interests at heart, we confidently hand them over a spare key to our headspace so they can come and go as they please. Even if they rummage around while we’re not there, there’s nothing of real value to steal, nothing to hide, and they won’t tell everyone how messy the place is. They even offer me cookies to bring with me as I go about my daily chores!

A perfect storm of cloud storage capabilities, data availability and machine learning competencies has fuelled the Internet of Behaviours . In this model, we provide the data in return for ‘free’ services. We have turned something previously worthless (our likes, thoughts, intentions) into something of great value — an incredible innovation story! However, as we arrive today at a point of digital-dependence, with technology deeply entwined in our everyday lives, we must examine how much we value trust and how much we value the services provided by this industry. A recalibration needs to happen urgently before trust is eroded for good.

Forty-one percent of U.S. consumers regularly delete cookies, and 30% have installed an adblocker. And, while regulation has been slow to react, many new regulations are well under way. One of the most well-known pieces of legislation was the 2018 General Data Protection Regulation (GDPR), which substantially expanded data privacy requirements in the EU. More recently, European regulators have begun to call for a complete ban on ad targeting , both the states of Virginia and California have passed comprehensive privacy bill s, and Google Chrome announced plans to end its support of third-party cookies altogether by 2022.

Forging the Road Ahead

As third-party cookies are phased out, you’re likely hearing more and more talk about first-party data. And if you’re in the marketing and publisher worlds, then you’ve also probably heard of zero-party data .

Consumers remain in need of curation and our interest in personalized content is higher than ever. In fact, a recent survey of more than 5,000 global respondents found a 33% year-over-year increase between 2020 and 2021 in the number of consumers interested in personalized offers. Zero-party data makes it possible to offer much better personalization than cookies ever could (without the privacy issues).

Customers are happy to receive ads and product offers that have been effectively matched to their needs — we just don’t want their data to be collected in an opaque, insecure manner and then sold to the highest bidder. Zero-party data puts customers in control of what information they share and who they share it with, enabling both greater transparency and more effective personalization. For consumers, it holds the promise of a personalized and more relevant experience with brands. In return, brands and businesses receive better insight and a longer-term relationship

Zero-party data represents a new foundation for a relationship built on trust and a value exchange.

Motivation in the Age of Technology Moving from Algorithmic Work to Heuristic Work

Fri, 07 May 2021 20:53:00 GMT

Reward & Motivation in the Age of Technology

Until recently the majority of workers performed algorithmic work — that is, the type of work that follows set procedures to accomplish a determined outcome. In a world dominated by algorithmic work, the traditional measure of success is productivity and the primary motivational reward is cash. This profit equation is simple and well understood in business — higher levels of productivity per $ cost of labour creates more value (profit) for shareholders.

Flash forward to 2021 - around 70 percent of the workforce in developing countries now perform heuristic work — the type of that work requires conceptual or creative thinking. Heuristic work is the ‘higher-value’ work that cannot be automated or performed by robots or machines. It involves skills like innovation and analytical thinking — the very skills that a worker will need to succeed in 2025 according to the World Economic Forum’s latest Future of Jobs Report.

The world of work is changing — and so are our expectations. Job loyalty is a dying concept, flexible work is gaining traction, and despite on-site baristas and free lunches, more than half of employees would prefer to work from home. Something is missing from the equation lately and it has less to do with demanding millennials and GenZ’ers than you think!

As the fabric of work is shifting, how do we evaluate performance and compute appropriate rewards when the outputs are not as tangible as they once were? Read on to find out.

The conventional motivate-the-unmotivated method of the carrot-and-stick is founded on the assumption that if you give an employee a carrot, they will exert more of the behaviours you reward, and if you hit them with a stick, you’ll get less of those behaviours. Consequently, workers are rewarded for productivity — the more widgets you produce throughout your shift, the more money the business makes and you’ll be rewarded with a small slice of the action. Smart managers then devised tiered reward structures like commissions and bonuses to incentivise employees to work even harder — the greater the output, the bigger the reward.

Despite the shift from manual work to knowledge work, motivating people using cash-based rewards ( extrinsic motivation ), is deep-rooted in the workplace, particularly among older employees who are accustomed to it. Traditional approaches to motivation are outdated, and do not adequately address the needs of the creative and innovative workplaces of the 21st century.

In this video, Dan Pink outlines various studies that tested the carrot and stick approach. As expected, for algorithmic tasks workers were motivated to keep working and improving. However, researchers came across a very surprising result — when even a rudimentary level of cognitive skill is required to complete a task, larger cash rewards actually lead to poorer performance �� Let that sink in for a moment — not only did larger rewards fail to motivate these workers — it actually caused their performance levels to drop!

The Candle Experiment is a clear example of how a monetary compensation can practically kill creativity, while at the same time making mechanical tasks work faster. In this study, participants were presented with a book of matches, a box of thumbtacks, and a candle. They were tasked with fixing the candle to a wall, then lighting it without dripping wax onto the table below. During the study, participants were separated into two groups. One group were told they were just doing pilot work to establish the norms on the times needed to solve. The second group were offered a cash incentive based on how quickly they could solve the puzzle. You guessed it — the latter group performed worse than the first group. The study found that the pressure to perform a problem-solving challenge in a competitive environment invoked a stress response in the participants— once triggered, this ‘fight or flight’ mechanism shut off the creative zones in the brain hindering the performance of the second group.

Assuming everyone is paid fairly to begin with, Pink outlines three elements of the motivation formula when heuristic work is involved — these are Autonomy, Mastery & Purpose.

AUTONOMY is the need to direct your own life and work .

To be fully motivated, you must feel in control of your work to some degree — what you do, when you do it, and who you do it with. Autonomy allows workers to be make decisions and be creative. The more meaningful those choices are, the more we feel in control. It’s an easy recipe for job satisfaction ( unless you are a control freak manager )

To test this theory, the team at Atlassian, an Australian software company, introduced ‘ ShipIt ’ days, where team members were given an entire day and a half to work on whatever company project they wanted. The practice proved highly successful and consistently led to many innovations for the organization.

By rethinking traditional ideas of control — the location of work, regular office hours, dress codes, expectations, targets, and so on — organisations can boost autonomy, build trust, and foster greater innovation and creativity.

MASTERY is the human desire for progress

If you are motivated by mastery, you’re probably keen to learn new skills and master new technologies. From professional athletes, to amateur hikers who climb Mt Everest as a vacation, the need for mastery is the driving force behind their continued motivation. Open-source communities, non-profits and B-corps around the world are powered by individuals seeking nothing in return for their efforts only a sense of progress and achievement.

However, not all challenges are created equal, or indeed equitable to everyone. To tap into the sweet spot we need to deliver Goldilocks challenges — tasks that are not too difficult, not too easy, but just right. Setting the bar too high can actually have the opposite effect and demotivate a capable team. The reward for mastery is simple — feedback and continued progress.

In his TED talk ‘ What Makes Us Fell Good About Our Work ’, Dan Ariely recounts a visit to a group of 200 engineers who had just been told their high-profile innovative project was being shuttered. “Ignoring the performance of people is almost as bad as shredding their effort before their eyes,” Ariely says. “The good news is that adding motivation doesn’t seem to be so difficult. The bad news is that eliminating motivation seems to be incredibly easy, and if we don’t think about it carefully, we might overdo it.” By far, the best book I’ve read on delivering feedback is Radical Candor by Kim Scott — if you squirm when giving or receiving feedback this book is the bible!

PURPOSE is the desire to be part of something larger than one’s self

Over the past few years we’ve witnessed an explosion of brands using purpose-marketing in an eager effort to appeal to Gen Z — the “woke generation”. Alongside new socially conscious brands like Tom’s, many older brands have adopted a purpose-driven approach in an effort to remain relevant. In 2019, Unilever chief executive Alan Jope boldly stated that the company will “ dispose of any brands in the portfolio that lack purposeful meaning ”.

Before that, the dis-loyal millennial job-hoppers had HR teams on the ropes. Workspaces were redesigned to make way for pool tables and soft seating, a smorgasbord of perks were rolled out in an effort to attract and retain the brightest talent — but they were never content. It turns out that millennials are not that unique after all, they simply want what everyone else does : meaningful work, autonomy, recognition, feedback and development opportunities.

Perhaps, if we think about workers as humans and not resources , we may get closer to a reward and recognition model that is less reactionary to the demands of the latest generation of talent, and centred around the core needs and desires of all humans.

That starts with enabling freedom : supporting the gig economy, remote working arrangements, and stepping back from micro-management. Freedom is built on a foundation of trust — when it comes to remote communications be on the right side of checking-in, rather than checking-up.

Offer the right challenges to the right people — that requires thoughtful consideration of your team’s capabilities and aspirations. The days of lengthy one-size-fits-all training courses are numbered. To drive engagement naturally, we need to meet the learner where they are. That means we need to invest time in understanding current competencies and aspirations, so that we can build a bridge from one to the other.

And lastly — start with why . The more businesses talk about purpose, the more it runs the risk of becoming just another corporate buzzword, and authenticity is paramount. Purpose answers an all-important question, “ Why does a company exist? ” — and the answer can serve as the beacon for all organizational decision-making. Having a team united around a common purpose is one of the most naturally motivational and engaging ways to work.

Motivation is not rocket-science, or a generational hack — humans are motivated by progress. Set the destination, create the right support, then step back and let the magic happen!

If you enjoyed this article, why not share it with a friend, or leave a clap behind on your way by!

Give My Brain A Break!

Thu, 22 Apr 2021 11:48:00 GMT

Back to back video calls have been a challenge for us to manage — not leaving enough time between meetings to grab a glass of water, take a bio break, or even stretch your legs! Many of us have resorted to multi-tasking our way through meetings, answering emails or messages, telling ourselves that we’ll be more productive and get more done by the end of the day. Multitasking is another fallacy — our brains don’t actually multitask, they switch from one thing to another. The end result of constant context switching and interruptions is a slow demise in our attention and focus. Many of us recognise this mid-state — we’re not quite flourishing, we’re not depressed, but we feel uninspired — just ‘meh’.

Adam Grant’s recent article gave us a name for it — he refers to this state as languishing . It’s not burnout — we still have energy. It’s not depression — we still hold hope. It’s a state where we feel somewhat joyless, stagnated and empty, and it’s the reason I took an 11-week sabbatical from my job in 2017. I knew there was something missing — an absence of motivation, creativity and joy, and growing cynicism. Not a great recipe for long-term resilience! Immersing myself in family, friendships, reading, gardening and travelling helped me replenish and return to my role with enthusiasm and energy.

We know this intense, sedentary lifestyle hasn’t been kind to our overall wellness, but new research just released from Microsoft’s Human Factors Lab provides the data we need to devote real attention to the health of our brains . Researchers from the lab, which examines how humans interact with technology, asked 14 people to take part in video meetings while wearing electroencephalogram (EEG) equipment — a cap to monitor the electrical activity in their brains. Participants in the study were monitored as they spent two hours in four 30 minute back-to-back meetings, and then again monitored with the same schedule of meetings interspersed with 10 minutes of meditation before the next meeting.

The results are interesting and have implications for how we think about the future of work, remote collaboration, and meetings in general.

1. Breaks between meetings allow the brain to “reset,” reducing a cumulative buildup of stress across meetings

Back to back meetings increase beta waves ( the brain waves associated with stress )over time. So, by the time you hit your 3rd or 4th meeting of the day, you are carrying the stress from the previous meetings!

Without a reset option, the brain continues to accumulate this stress and will eventually suffer. With 10 minute breaks between meetings, the results were clear — the antidote to meeting fatigue is to take short breaks.

2. Back-to-back meetings can decrease your ability to focus and engage

Without the intermittent breaks to reset, the study also showed that participants were less engaged in subsequent meetings (measured by levels of frontal alpha asymmetry), and therefore not as focused. To do our best work, we need to treat each meeting as a separate block of work that needs focus, rather than multitask or push through a meeting marathon.

Ask yourself, how would that work in the real-world ? In a previous company I worked at, we would often run between buildings to get to the next meeting room, stressed because we had to wrap the other meeting on time, and shameful that we were arriving late and frazzled to the next meeting. Despite agreeing to end meetings after 50 minutes to allow for transfer time, we still found ourselves apologising for finishing meetings ‘early’.

What would it take to change our learned behaviours for the long term?

3. Transitioning between meetings can be a source of high stress

Before we finish up at one meeting, we are checking in mentally to the next meeting — the competing messages add to an already-stressed brain and prevents us from winding down one meeting before switching gears to the next one. In fact, the activity in our brainwaves showed persistent stress levels with back-to-back meeting — this is contrasted by a significant fall in stress levels when we meditate between meetings.

So, what can we do about?

Think Differently — try to shift your thinking a little by focusing on presence above productivity. Powering through, at all costs, is adding liabilities to your wellness balance sheet — try offsetting those liabilities with activities that boost your mental assets, like breathing breaks, mindfulness activities (such as colouring), a short walk (or a dance!), or just stare out the window for a few minutes and let your weary mind rest.

Lead by Example — mindfully schedule meetings for 45 minutes, and stick to the time . Ensure the content or discussion is tailored for the shorter duration and indicate you are wrapping up after 35 minutes. Signalling the end of the meeting is approaching earlier sends a strong message to your team that you are committed to action rather than paying lip service to the research

Make it Count — we’ve all heard this advice before but here it goes again — question every meeting! Is it necessary? Could it be an email or a Slack conversation? Who needs to be there? Are you clear about the purpose and outcomes? Have you communicated them to the participants in advance?

Make it Interactive — there is nothing worse than webinars! Digital monologues and one-way conversations practically ensure your audience will get distracted. Think of ways to keep your meeting participants engaged — let them know why you need their time, and let them contribute. I’m not talking about forced-fun team building exercises — simply respect each others time and energy.Paragraph

For more information on the research check out the original article here: https://www.microsoft.com/en-us/worklab/work-trend-index/brain-research

Humans, Disrupted

The Future Where No One Works — Except the Billionaires Who Still Do

If a world without work is paradise, why are its architects still working?

The Quiet Collapse of Feeling

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What Happens When the Work Disappears?

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“AI and robots will replace all jobs. Working will be optional, like growing your own vegetables, instead of buying them from the store.” — Elon Musk

Meaning is how we interpret our experience. Purpose is the story we tell ourselves about why it matters.

Why Purpose Matters More Than Productivity

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“I can easily imagine a world where 30–40% of the tasks… will get done by AI in the not too distant future” — Sam Altman

When Everything Becomes Urgent, Nothing Feels Important

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The Age of Anomie

Reconstructing Purpose

A Rallying Call to Reawaken Purpose

Technological Narcissim

When Systems Love Themselves More Than Us

A simple story: Autoplay as a Business Model

What We Don’t Count, We Don’t Protect

Flattery, Outrage, Repeat: How Loops Hook the Brain

Spoiler: There’s no moustache‑twirling villain. Just a system doing what it was built to do.

A Failure of Metrics, Not Morality

But engagement does build human value. Time‑on‑platform isn’t human growth. Profit isn’t human progress.

Who Pays? What’s Measured? What’s Missing

The Pattern in Plain Sight

When we refuse to count cognitive and emotional costs, profits will look healthier than people do.

Technological Humility: What We Might Do Differently

A Human‑First North Star

Too Different to Belong, Too Ordinary to Stand Out

How online culture squeezes out experimentation, and how to reclaim the messy middle.

Fit in, or Be Phenomenal

That’s the paradox of the online world: it convinces us that we are both too different to belong and too ordinary to matter.

Not Normal enough to Belong

Too Normal to Matter

The same instinct that makes us conform — that hunger for belonging — also leaves us desperate to stand out. We don’t just want to be accepted by the herd, we want to be noticed and valued by it.

That’s the maddening trick the online world plays on us: it gives us infinite inspiration, then quietly robs us of the permission to try.

The Disappearing Middle

Between the urgency to join the herd and the pressure to be singular, the middle — the clumsy first steps and experiments- are deemed irrelevant. And that’s the real loss.

It’s easier to pick a side than to risk being misunderstood in the middle. But the middle — the place of curiosity, trial, and play — is exactly where progress happens.

Reclaiming the middle

The Cognitive Devolution

How Personalisation is Quietly Unravelling our Shared Reality

TL;DR

The Slow Unraveling

From Revolution to Devolution

The Seduction of the Easy Path

The Fragmentation of Shared Reality

The Rise of Cognitive Helplessness

From Collective Reason to Collective Resonance

Rebuilding Cognitive Strength

Reintroduce Friction

Practise Active Recall

Seek Counterpoints, Not Confirmation

Protect Deep Time

Reclaim the Narrative

The Quiet Renaissance

Epilogue — The Folie à Deux

Whose Thoughts Are They Anyway?

AI Persuasion, Impressionability, and the Fragile Mind

Impressionability: The First of the Five I’s

What’s Happening When We’re Being Influenced?

The Ethical Fork in the Road

Designing AI as a Cognitive Firewall

The Infinite To-Do List: AI Could End Busywork (But It Probably Won’t)

The AI Promise vs. The Reality of Work

Why Do We Keep Falling into This Trap?

The Brain Layer: Are we hard-wired for busyness?

The Identity Layer: Do we wear busyness as a badge of honour

The System Layer: Capitalism’s Relentless Pursuit of More.

The Hidden Cost: The ‘Infinite Scroll of Work’

Are We Losing Our Minds to Technology?

The Medium is the Message

The Cognitive Toll of Tech

The Cost of AI Dependency: Creativity at Risk

Protecting What Makes Us Human

AI and US: Collaborating for a Smarter World

Dublin Tech Summit: 29th May 2024

Seeing Humans Through 5 I's

Meaning is how we interpret our experience.
Purpose is the story we tell ourselves about why it matters.