According to Business Insider, London Business School professor Ekaterina Abramova warns that AI advances are creating a historic labor shock. She argues that a single AI model can displace thousands of cognitive jobs across multiple industries almost overnight, a sharp break from past, more gradual waves of automation. Abramova expects layoffs to outstrip new job creation over the next five to ten years, especially without aggressive retraining. She points to vulnerable entry-level roles like junior developers and analysts, and cites historical examples like the UK’s Enclosure Acts and 1980s pit closures where rapid displacement fueled riots and upheaval. Leaders are split, with figures like Anthropic’s CEO warning of white-collar displacement, while others like Nvidia’s Jensen Huang say AI will transform, not erase, work.
The Speed Is The Problem
Here’s the thing that really worries me about this analysis. It’s not the idea that AI will change the job market—we all know that’s coming. It’s the pace. Peter Orszag nailed it with his quote: labor markets can handle small-fast problems or big-slow problems. But a big-fast problem? That’s a recipe for crisis. We’re talking about a technology that can, in theory, make a whole department’s worth of cognitive tasks obsolete with a software update. That’s not like a factory slowly automating over a decade. That’s an existential threat to someone’s career that appears on a Tuesday morning. How do you retrain for that at scale, and fast enough?
Divided Leaders, Muddled Future
And look at the leadership split. It’s stark. You’ve got doomers like Dario Amodei and optimists like Jensen Huang basically describing two different futures. Huang’s point is classic: AI is a tool, and the person using the tool wins. But that’s cold comfort for the “person” who becomes the tool. It assumes a level of mobility and adaptability that, frankly, our current systems don’t support. The retraining gap Abramova mentions is huge. You can’t turn a laid-off customer support manager into a prompt engineer or AI ethicist with a six-week bootcamp. So where does that leave people? Probably in that “long-term underemployment” Orszag mentions, which is just a polite term for a broken economic engine.
History Is Not On Our Side
The historical parallels are chilling because they’re so logical. When change outpaces a society’s ability to absorb it, things get ugly. Riots. Strikes. Political collapse. Abramova’s warning about eroding democratic norms isn’t hyperbole; it’s a playbook we’ve seen before. The push for more surveillance to “manage” discontent feels like a terrifyingly predictable next step. And let’s be real: are governments and corporations showing any sign of preparing for this at the required scale? I don’t see it. We’re still in the magical thinking phase where everyone hopes the new jobs will just… appear. But hope isn’t a strategy.
A Fork In The Road
So is the dystopia inevitable? Abramova says no, and she points to the path of “worker-augmenting AI.” This is the good version, where AI handles the grunt work and humans focus on judgment, ethics, and relationships. But here’s the catch: that path requires deliberate choice. It needs regulatory incentives that reward companies for augmenting their workforce, not just slashing it for quarterly gains. It requires investment in real, substantive retraining. Basically, it needs us to be smart and compassionate. Given our track record with previous economic shocks, I’m skeptical we’re up to the task. We might just take the path of least resistance—mass layoffs, social strain, and a whole lot of turmoil. The technology is here. Our preparedness, clearly, is not.
