No one knows whether AI will trigger a white-collar jobpocalypse. The loudest warnings still come from people building and selling the technology, whose predictions often double as hype-mongering or cover for unrelated cost cutting with investor-friendly language. Think tank and analyst forecasts are no less vertiginous.
The honest answer is that current data gaps leave us all guessing.
But we do know the script that¡¯s already creeping up as displacement begins to trickle: ¡°retraining,¡± ¡°upskilling¡± and the hollow language used to make dislocation politically palatable. We cannot allow it to become the next comforting lie or a way to sell the future while abandoning the people forced to live through it.
Policymakers and tech leaders shouldn¡¯t wait for mass disruptions. They should also stop pretending retraining is much more than a slogan. America already ran this experiment after deindustrialization. Manufacturing losses were relatively concentrated, but the damage spread through families, communities and politics for generations. The payoff from the retraining policy during this era was weak at best.
The optimistic case is that AI will eventually create new jobs we can¡¯t yet imagine, just as past tech revolutions did. But we won¡¯t get there if policymakers ignore what Brookings Institution Senior Fellow Molly Kinder calls the ¡°messy middle¡±: the period between today¡¯s rocky AI adoption and the promised land of post-AGI abundance. Tech leaders love the utopian pitch, but the public may revolt long before it arrives. And retraining policy, Kinder notes, ¡°has been one of the worst-performing categories of labor market intervention.¡±
The scale of potential labor exposure, meanwhile, dwarfs deindustrialization. Bloomberg Economics says that 27% of workers in advanced economies, more than 120 million people, are likely to be ¡°meaningfully affected by AI.¡± That doesn¡¯t mean all will be displaced, but it points to vast potential disruption.
Business leaders are already reaching for retraining. Nearly a quarter of CEOs in a recent survey said that more than half of their workforce will need to be ¡°upskilled.¡± A banking chief went viral for his comments recently about AI replacing ¡°lower-value human capital.¡± After the backlash, he apologized and invoked the familiar promise of reskilling.
Yet what does that mean? Too often, the answer is maddeningly vague. A recent analysis from human-resources consulting firm Randstad describes the future skill set as ¡°AI fluency¡± plus ¡°uniquely human capabilities¡± such as emotional intelligence, creativity, problem solving, critical thinking and ethical judgment. The first part is obvious; workers need to know how to use AI tools. The second part sounds like a list of desirable traits, not a transition plan for laid-off workers.
Inside the tech industry, the brazenly arrogant default answers are ¡°universal basic income¡± or ¡°learn a trade.¡±...
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