What if AI doesn't take your job - but quietly removes the first rung of the ladder?
The conversation about AI and work is often dominated by extremes: either AI will transform everything, or the fears are wildly overblown.
But what does the evidence actually tell us?
In this episode of HardWired: The Human Algorithm, Lena Chauhan sits down with Bouke Klein Teeselink, Assistant Professor in Economics at King's College London and Chief Economist at the AI Objectives Institute, to look beyond the headlines and into the data.
They explore a much more complicated story about the future of work: not necessarily a dramatic wave of mass layoffs, but changes in who companies hire, which skills remain valuable, what happens to salaries, and how people build expertise in the first place.
And one of the most important questions is about the next generation.
If AI increasingly performs the junior tasks through which young people traditionally learn a profession, what happens to the pathway from graduate to expert?
Could we eventually face a shortage of experienced professionals because the opportunities that once trained them have disappeared?
Lena and Bouke also unpack a counterintuitive finding: AI's impact isn't simply about how much of a job it can perform. What matters is which tasks it performs. Automating expertise-heavy work and automating repetitive grunt work can have very different consequences for the people doing those jobs.
The conversation goes beyond employment statistics to ask what conventional economic data may be missing altogether: trust, relationships, informal commerce, entrepreneurship and the parts of economic life that remain profoundly human.
This episode is for parents wondering what future their children are entering; students and young professionals deciding what to learn; teachers preparing young people for work; and leaders trying to understand what AI actually means for their organisations.
Because perhaps the question isn't simply:
“Will AI take our jobs?”
It's:
“What happens to the way humans learn, earn, build expertise and become valuable when AI can do more of the work?”
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