In a column in January in regards to the paradox of labor, I recalled the immortal Douglas Adams joke about working circumstances: the hours are good, however “many of the precise minutes are fairly awful”. The joke is again already — and generative AI has flipped the script.
Lecturers at UC Berkeley’s Haas College of Enterprise have been doing ethnographic analysis into how expertise employees are utilizing generative AI. Some will inform you that ethnographic enterprise analysis is each the worst form of enterprise analysis and the worst form of ethnography, however I admit to a delicate spot for these things. What the researchers discovered was the alternative of Adams’ morose Vogon guard: the minutes are wonderful however the hours are horrible.
“In micro moments of prompting, iterating and experimenting, folks talked about momentum and a way of expanded functionality,” researcher Xingqi Maggie Ye defined. “However once they stepped again and mirrored on their broader work expertise, a unique tone typically emerged. They described feeling busier, extra stretched, or much less capable of absolutely disconnect.”
These tech employees felt that generative AI was making them dramatically extra productive and succesful — however they had been additionally attempting to do extra, voluntarily working longer hours, and hurtling in the direction of burnout.
Are these ethnographic observations a glimpse of the long run for the remainder of us?
Little question we will discover out, however whereas we wait, each financial idea and the historical past of expertise have some issues to show us.
Principle first. Contemplate a contract programmer, paid by outcomes, who used to work 10 hours a day and out of the blue finds that they will obtain the identical leads to two. Frequent sense may counsel that the coder will begin to benefit from the pleasures of a two-hour workday, however financial idea is extra ambiguous: the “earnings impact” means that the employee ought to work fewer hours as a result of they will obtain a lot by working so little. The “substitution impact” says that employees ought to work longer hours, as every additional hour yields bountiful rewards.
Then there’s the query of what the brand new equilibrium will likely be as soon as everybody masters the expertise. As an analogy, think about that just a few alchemists uncover methods to flip lead into gold, however their methodology is quickly being copied. They need to make and promote as a lot gold as doable, as quick as doable, earlier than the collapse within the gold market. Coders armed with good AI brokers could also be in the identical place: code as a lot as you’ll be able to when you can nonetheless cost cash to take action, as a result of code might quickly grow to be as low cost as mud.
There’s additionally a company dynamic to contemplate. It could be that 9 out of 10 in-house programmers are about to be sacked, leaving a handful in cost to handle the coding brokers. In that case, the crucial is evident: to maintain your job, display which you can out-code everybody else within the constructing. Winner-take-all dynamics will not be a recipe for lengthy lunch breaks and lengthy weekends.
That’s the speculation, however historical past has just a few classes for us, too. Visible aids had been as soon as produced by graphic designers and used on particular events solely; the invention of PowerPoint meant that extremely paid and expert professionals began losing time making their very own slides, badly. E-mail is vastly faster and cheaper than a letter, however that merely means a profusion of low-quality, low-value messages bleeding into the evenings and weekends. The library photocopier allowed a technology of scholars to repeat educational articles at a pace their dad and mom might hardly have imagined — nevertheless it didn’t make studying, considering or studying any sooner.
In every case there was an astonishing improve in a slender measure of productiveness, however the total impact was to distract from the true job at hand, to create a bloated pile of busywork, and to accentuate the sense of productiveness debt, with the listing of duties folks felt responsible about not doing getting longer, not shorter.
What the UC Berkeley ethnographers discovered is unusually acquainted. “Staff more and more stepped into duties that beforehand belonged to others,” they wrote. That’s the dangerous slide downside over again.
“As a result of AI made starting a job really easy . . . employees slipped small quantities of labor into moments that had beforehand been breaks.” Everyone who lived via the rise of smartphones will nod in recognition.
“Extra multitasking. AI launched a brand new rhythm during which employees managed a number of energetic threads directly . . . This created cognitive load and a way of all the time juggling.” Nicely, sure — what number of browser tabs do you’ve got open proper now?
I don’t imply to counsel that AI is ineffective or trivial, however there’s a lengthy historical past of time-saving digital applied sciences that at greatest make us extra productive but overwhelmed — and at worst, simply make us really feel overwhelmed.
Digital instruments don’t must work this fashion. The Nobel laureate economist Claudia Goldin coined the phrase “grasping jobs” to explain roles comparable to these in company regulation or funding banking the place disproportionate rewards are paid to these prepared and capable of work lengthy hours and be on name each time required. She contrasts these with well-paid positions in pharmacy, paediatrics, major care and veterinary drugs, the place the roles and the IT programs that assist them have been designed to permit extremely certified practitioners to work restricted hours after which hand over to an equally certified colleague.
It’s not not possible to think about AI brokers getting used to facilitate this handover course of, however the discourse for the time being is of good, idiosyncratic human conductors overseeing a frenetic orchestra of AI brokers. Handover protocols sound much less enjoyable however could also be much more helpful.
And what are the remainder of us to do whereas we watch for the wizards of Silicon Valley to stoop to constructing such prosaic instruments? Todd Brown, a efficiency advisor and managing associate at Subsequent Motion Associates, has lengthy espoused holding an “Agenda” listing for colleagues and necessary purchasers — working via the listing face-to-face moderately than firing off emails each time one thing pops up. Now he does the identical for ChatGPT, “with concepts for prompts”.
It could sound like an odd follow, on condition that generative AI — not like a colleague — is all the time out there. But it surely is smart. Simply because you’ll be able to flip to AI at a second’s discover doesn’t imply you must. There’s something to be mentioned for planning forward earlier than interacting with the AI, and for blocking out time with out it — leaving area for the human within the loop to cease, to replicate and to breathe.
Written for and first revealed within the Monetary Occasions on 4 March 2026.
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