The backlash against brainmaxxing

Steven Bartlett, why we are craving low value work and the "slow AI" movement

Steven Bartlett of The Diary of a CEO and Dragon’s Den fame recently complained that his life was ruined for 3 days after drinking two glasses of wine. This has spawned endless social media memes, but it also caused a backlash with endless articles reeling against his comments. The backlash against Bartlett’s three lost days tell us a lot more than we realise about AI adoption. The relentless pressure to optimise every waking hour is increasingly being engineered into the workplace by the very leaders deploying AI across their organisations. And that makes it a leadership problem not just a cultural trend.

Image source: The Independent

Brainmaxxing and AI

In the golden age of "brainmaxxing" we live in a hyper-optimized, bio-hacked, metric-driven existence where every calorie, every minute of sleep, and every ounce of cognitive output is tracked, measured, and judged.

The availability of powerful, frictionless AI tools means the friction of starting a task has vanished. But because we can do everything faster, the expectation is that we should do more.

How many of you relate to this pressure:

• To spin up one more prompt before closing the laptop?

• To squeeze in one more deck to prepare for the morning?

• To deploy one more autonomous agent to grind through data overnight while you sleep?

We were promised more free time yet we feel we have less than ever.

In their Harvard Business Review “AI Doesn’t Reduce Work—It Intensifies It” the authors Aruna Ranganathan and Xingqi Maggie Ye discovered that AI tools didn’t reduce work, they consistently intensified it. In their eight-month study of how generative AI changed work habits at a US based technology company with about 200 employees, they found that:

“…Employees worked at a faster pace, took on a broader scope of tasks, and extended work into more hours of the day, often without being asked to do so”

This is by no means just an AI problem. As the Steven Bartlett story shows, social media influencers are incentivized to peddle the latest tracker or wearable, earning them affiliate fees, and leaving the rest of us feeling like lemons, desperately squeezing out the last available drop of daily productivity just to keep up.

The KIMRA confession: the luxury of low-value work

Last week I was speaking at the KIMRA conference, which brings together professionals in the knowledge management, insights, research and thought leadership function. The room was packed with brilliant minds from elite law firms, global management consultancies, investment banks, and data vendors. These are people whose entire career value is predicated on high-level cognitive processing.

In a fireside chat one of the participants, a leader at a professional services firm, said “give me some low-value work!”

She got woops and cheers!

She went to explain how she felt that her brain was so maxed out, essentially fried from working at full capacity for months on end. So much so that she craved the dull, repetitive work that is now being automated by most organizations.

How can this make sense in the context of a promised productivity boom?

When the dominant tech narrative is about being freed from the drudgery of dull work and promising us liberation, why are we craving it?

And why are knowledge workers suddenly begging to have it back?

The healthcare parallel: destabilising the workday

An interesting parallel comes from healthcare. Recently, while researching my forthcoming book, I had a fascinating discussion with Sue Lacey Bryant, the former Chief Knowledge Officer for the NHS in England.

What I observed from our conversation, and what it helped me to realize about the broader workforce, is that leaders introducing AI often completely fail to consider the psychological ecosystem of the work being changed. We look at efficiency gains on a spreadsheet, but we don’t look at how automation disrupts the invisible balance of a human being’s day.

For example, if you only give a doctor the tough work, and give the other parts to a nurse practitioner, then what you end up with is a doctor whose day is full of acute illness, and dire circumstances. The balance is entirely destroyed. There are no longer any “easy” moments in the shift to catch one’s breath, as it’s one problem after another.

Earlier this week the American Medical Association at their Annual Meeting in Chicago this week stated in one of their adopted resolutions:

“The relentless focus on productivity metrics has been associated with physician burnout, emotional exhaustion, moral distress and workforce attrition, all of which may threaten patient access to timely, high-quality care.”

Healthcare is a fascinating example because the stakes are literally life or death. I recall when I was working at Accenture some years ago there was a time when new experienced recruits included doctors. Their ability to make decisions in high-pressure, chaotic environments made them phenomenal consultants. But the corporate world should view this as a warning, not an example to follow.

The Slow AI movement

Is the accelerated pace of change that so many people feel leading to a counter-movement towards slow AI?

Just as the frantic pace of fast-food culture birthed the "Slow Food" movement, we are beginning to see the early indicators of a "Slow AI" movement: a deliberate pushback against the expectation of instantaneous, infinite output. We are already seeing the emergence of dedicated spaces exploring this shift, most notably Professor Sam Illingworth’s popular Slow AI Substack, which advocates for critical AI literacy and cautions against blindly outsourcing human judgment to machines in the name of speed.

There is a more useful way for leaders to think about this than simply going slow. Research for my book showed that the leaders with the highest AI-Q deliberately build in positive friction: small, intentional pauses that let them stop and interrogate an output rather than wave it through or delegate at speed to their teams. It is the discipline of slowing down to apply critical thinking at exactly the moment AI seems to speed things up. Seen this way, Slow AI is not a brake on productivity, but rather positive friction designed into the organisation.

What might this look like in practice? How can you deliberately build in that friction?

• Human first. A standing rule that the thinking starts with you, not the prompt: form your own view, then bring AI in to challenge or extend it. This is positive friction in a single habit and one that came up repeatedly in my interviews.

• Depth over throughput. Stress-test one idea rather than generate ten reports. Reconsider success to be how well something was considered, not how much was produced. The metric of success shifts from how much you produced to how deeply you considered it.

• No-AI zones. Name the decisions where AI stays out of completely or stays advisory only, especially high-stakes judgment and the difficult human conversations. Our instinct is to avoid what’s hard, but that dilutes the impact those decisions have and our own accountability.

The New Leadership Obligation

I gave healthcare as an example earlier, of what happens when introducing AI makes the balance of work wonky. Now to be clear, I’m not saying you should waste doctors, or in fact any employee or individual’s workday, on repetitive work. But there is something about what people can work with, as the KIMRA director’s comment showed.

When you are thinking about a new AI tool, are you also showing a level of empathy with how the work is going to change? Are you able to understand how that balance of work in a person’s day is going to change, and whether they’re well placed to cope with that change?

You could argue that everybody just needs to get on with things and adapt, and that it is a matter of time. Of course that’s true. All of us are constantly adapting to the new world of work that is emerging and every transition has its challenges. Yet the job of a leader is by definition to lead. And to lead, whether you are already in that position or aspiring to be, you need to be thinking, not just about the present but also about the future state.

Some of this is about protecting your people and being a responsible employer. But there are further considerations.

Are you thinking about:

• The financial cost: What will the hidden cost to your company be in medical insurance claims, mental health leaves, and talent churn as burnout spikes across your workforce?

• The psychological shift: How is sustained, non-stop interaction with AI changing the way your employees think, feel, and behave in these hybrid human-machine environments?

• The duty of care: Is protecting your employees’ cognitive bandwidth and managing AI-related wellbeing about to become your primary leadership obligation?

If l leave you with one thought it is this:

The backlash against Bartlett’s three lost days tell us a lot more than we realise about AI adoption and the new leadership obligations that are emerging.

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