For most of last year, Dario Amodei was one of Silicon Valley’s most prominent doomsayers on AI and employment. The Anthropic CEO said publicly and repeatedly that AI could eliminate half of entry-level, white-collar knowledge work within years — the kind of stark projection that made him the rare tech founder willing to say out loud what many of his peers only whispered.
So it was notable, at Anthropic’s briefing to the press on financial services in Lower Manhattan, sitting onstage alongside JPMorgan Chase CEO Jamie Dimon for the first time, when Amodei reached for a very different intellectual framework: the Jevons Paradox.
“If you automate 90% of the job,” he said, recalling recent arguments by University of Chicago economist Alex Imas and Apollo Global Management’s Torsten Slok, “then everyone does the 10% of the job. And the 10% kind of expands to be 100% of what people do and kind of 10xs their productivity.”
It’s a more comfortable theory. It’s also one he immediately complicated.
Amodei is shifting the story from jobs disappearing to jobs transforming and multiplying. His own caveat that AI is moving faster than past technologies suggests that aggregate optimism may not arrive quickly enough to spare workers displaced in the meantime.
In a single exchange, Amodei invoked two competing laws of physics-meets-economics to describe what AI might do to human labor. The first was the “Jevons Paradox” — the 19th-century observation that efficiency gains expand demand rather than contract it, suggesting AI will ultimately create more work than it destroys. The second was “Amdahl’s Law,” a principle from computer science holding that the speed of a system is limited by its slowest component — implying that even if AI automates most of a job, the remaining human bottleneck becomes the binding constraint. “Many things in this technology that I’ve seen over the last few years have this feeling of kind of an unstoppable object,” he said. Usually when people talk about unstoppable objects, they also refer to an immovable force, standing in its way. In this metaphor, the immovable force would be the entire history of modern work.
“You know, when technology kind of increases the pie, like the economy is very good at kind of – again, it’s related to kind of the Amdahl’s Law, Jevons’ Paradox,” Amodei said. “Like ,things are flexible. Things are fungible. They tend to move.”
What Jevons actually said
William Stanley Jevons was a 19th-century British economist who observed something counterintuitive about coal: as steam engines became more efficient and coal cheaper to use, total coal consumption went up, not down. Efficiency, he argued, stimulates demand rather than reducing it.
Applied to AI and labor, the logic runs like this: if AI makes a lawyer 10 times more productive, legal services become cheaper; cheaper legal services mean more people and businesses use them; more demand for legal services means more lawyers, not fewer. Apollo’s Torsten Slok has been repeatedly arguing about examples of this as the “Jevons employment effect” — the argument that AI, like the steam engine before it, will expand the pie rather than shrink anyone’s slice.
Dimon made the same argument in blunter terms, invoking agriculture, electricity, and the internet. “The capitalist society is very good at recreating jobs and recreating things,” he said. “And life is better. Not always if that town loses a factory, but in general better.”
The caveat Amodei buried
The problem is that Amodei, almost in the same breath, described precisely the condition under which Jevons stops working.
“AI is moving faster than all these previous technologies,” he said. “And so when you strain a system more than, you know, than it’s usually strained, it’s possible you get these weird behaviors and this big disruption.”
This is not a minor qualification. The Jevons mechanism depends on time — time for markets to recognize new demand, for workers to retrain, and for employers to expand rather than simply contract. The ATM is the classic cautionary example: it didn’t eliminate bank tellers immediately, but over two decades, teller employment fell sharply as branch activity shifted. AI is not operating on a two-decade timeline. The Anthropic CEO who once warned of a white-collar bloodbath is now open to Jevons — but his own analysis suggests the rebalancing may not arrive fast enough to matter for the workers caught in the transition.
The distribution problem nobody solved
Even the optimists acknowledge that Jevons operates at the aggregate level, not the individual one. If AI expands demand for legal services globally, that’s good for BigLaw partners and bad for first-year associates, whose document-review work no longer exists. The pie gets bigger; the slices don’t redistribute automatically.
Amodei gestured at this problem but didn’t resolve it. “Companies have a choice,” he said. “They can do the same thing with less resources — and that leads to things like layoffs — or they can do more with the same amount of resources. But that requires creativity.” He and Dimon both endorsed some form of wage-reassurance programs and government-funded retraining. Dimon pointed to trade adjustment assistance after NAFTA as a model — before acknowledging that it was a pretty bad example.
“It didn’t work [with NAFTA] because it wasn’t set up right, because it made it too hard to get the benefits. So it’s solvable, but only with collaboration in government and business.”
Amodei’s evolution on this question is worth tracking closely. When the CEO of the company building the technology starts invoking optimistic economic theory, there are two possible explanations. Either he has genuinely updated his view based on new evidence, or the social and political cost of the bloodbath framing — particularly as Anthropic navigates a Pentagon lawsuit and a fraught regulatory environment — has made it more useful to suddenly sound a bit more optimistic.
Which side you come down on may come down to whether you believe most humans—and most bosses—prize creativity over layoffs. What do you think?
