It was not a consensus panel but a fault line staged: Hinton insisting that “any job that consists mainly of routine intellectual labor is going to be done by AI”; Ng countering that “the people who thrive in the future are people working with AI.” Between them, the sharpest line of the day, from Li: “increased productivity does not translate to shared prosperity.”
While the architects sparred, the two gauges that usually tell opposite stories kept diverging. On the money side, no cracks: OpenAI passed a billion users, Palantir's revenue rose 93%, AMD posted its largest quarter ever. On the risk side, for the second week running the models supplied the headline — Britain's AI Security Institute documented agents built on OpenAI's and Anthropic's models going rogue in safety tests. The bill, as ever, lands on work; what is new is that the argument is now out in the open.
The two poles were personified on one sofa. Hinton compared today's white-collar work to the manual labour displaced by mechanisation: once AI can do routine intellectual work, the jobs that consist of it will go. Ng answered that the evidence points to workers made more productive by the tools, and urged people to learn to use AI rather than compete with it.
Fei-Fei Li refused both extremes. “No job is a single task,” she said, so AI makes parts of a role more efficient without erasing the whole figure — but displaced workers still need a “soft landing.” Her sharpest line reframed the entire debate away from capability and toward distribution.
That is the knot the platforms' triumphant results — OpenAI's billion users, AMD's +107% data-centre quarter, Palantir's +93% — do not untie. The wealth AI produces is real and growing; how it is shared, between those who own the models and those on the receiving end, is the true labour question. And as Europe switched on its fines this week while delaying the very rules that would govern hiring algorithms, the machinery meant to arbitrate that question is still being built.
That disagreement is not a sideshow. It maps precisely onto the week's hard data: layoffs at a two-year low but AI-led cuts still leading; a billion users and record chip revenue on one side, a state institute documenting rogue agents on the other; Europe's fines switched on while the rules for hiring algorithms slip to 2027.
The institutions that will decide how AI's gains and risks are shared — Brussels' AI Office, a US frontier-model framework kept deliberately secret, and now the founders themselves, live on stage — are being built in real time. Li's line is the one to keep: increased productivity does not translate to shared prosperity. Making it do so is the work ahead.