Stay informed with free updates
Simply sign up to the Artificial intelligence myFT Digest — delivered directly to your inbox.
One of my first jobs as a trainee reporter was to write a daily stock market report. It was the sort of task that wouldn’t trouble an experienced journalist, but for a novice like me, it was scary and hard.
I was lucky, though: after I filed my draft, my editor would have me stand behind his shoulder and watch his screen while he edited it. He would explain out loud what he was changing and why, which helped me learn how to do it a bit better the next day.
I thought of him when I read The Skill Code, a book published last year by the academic Matt Beane, which argues that the “working bond” between experts and learners has been “the bedrock of humanity’s transfer of skills and ingenuity for millennia”. But can it survive the age of artificial intelligence?
So far, the tasks for which generative AI seems most suited are also those that many white-collar trainees tend to do. When researchers at the Brookings Institution, a US think-tank, analysed data from OpenAI, they found the percentage of tasks at high risk of automation was five times higher for a market research analyst than for a marketing manager, for example. It was three times higher for a sales representative than a sales manager, and more than twice as high for a graphic designer than for an art director.
Investment banks are already reportedly mulling whether they need to recruit so many junior analysts in future. Even if you want to continue to hire trainees, the economics of that business model might become more difficult in a world in which you struggle to monetise their labour.
A senior lawyer told me it was already becoming harder to persuade clients to pay for the time of junior lawyers, because they thought AI could do the work instead. The juniors, meanwhile, were reluctant to use the new tools because they were concerned that they would reduce their billable hours, and they would miss out on the practice they needed to progress.
In The Skill Code, Beane argues that acquiring mastery in any profession requires challenge, complexity and connection. But he warns that “novices are becoming increasingly optional and distant participants in an expert’s daily tasks”. He cites a number of new technologies, not just AI. When he researched robotic surgery in hospitals, for example, he found the use of robots reduced the opportunity for junior surgeons to get involved.
I can imagine any number of ways in which this could all play out. On the optimistic side, companies might figure out new ways to train the next generation of senior professionals, using AI in a judicious way to accelerate their progression without compromising their acquisition of knowledge and opportunity for human connection.
That might require changes to some business models. Law firms may need to say goodbye to the billable hour, for example. But there is no need to romanticise the old way of doing things, especially in firms where juniors were expected to put in extremely long hours doing fairly dull work which was, at its worst, a kind of professional hazing.
In the gloomiest scenario, however, companies might stop hiring juniors in a rush for productivity gains. “Here’s the scenario that keeps me up at night,” wrote Molly Kinder, one of the researchers at Brookings. “A world of extremely capable AI agents learn to tackle most day-to-day white-collar tasks and are managed by a small cadre of experienced senior managers.”
In this scenario, how would anyone ever acquire the experience to reach the less-automatable upper rungs of the career ladder? The senior lawyer I spoke to wondered if we might one day see a return of the old apprenticeship system that existed in much of Europe before the industrial revolution, in which families who could afford it would pay for their offspring to be apprenticed to a master. The implications of this for social mobility — already not great in many professions — go without saying.
When it comes to the integration of generative AI into white-collar work, it is still very early days. No one really knows how it will go, and anyone who says they do probably has something to sell you.
But what the technology will or won’t be capable of is only one part of that question. The other part is what companies choose to do with it. And for my money, the corporate decisions with the most transformative power for white-collar work are going to revolve around how (and whether) people move up the career ladder. If you’re on the top rung and you want to look forward, the best thing you can do is look down.
Read the full article here
