A CEO With $100M in Revenue Says AI Job Loss Is Overhyped. Geoffrey Hinton Disagrees, and So Does the Math.

A post from @Seanfrank on X this week opened with exactly the confidence the optimist camp has been waiting for. He runs a company doing over $100 million in revenue, he wrote, and has fired zero people because of AI. The people who got fired were fired for refusing to do their jobs or doing them badly. The subtext was clear: stop catastrophizing. The post collected 240 likes and kept circulating in {{beat:ai-job-displacement|AI job displacement}} conversations as a kind of evidence for one side of a debate that refuses to settle. The problem is that Geoffrey Hinton is making the opposite case at the same volume. An X post summarizing Hinton's recent remarks — that big tech CEOs are racing toward {{entity:agi|AGI}} for power and profit without thinking through what mass unemployment actually does to an economy — was getting nearly as much traction. The post flagged the circular logic that tends to get ignored in productivity arguments: when enough people stop getting paychecks, they stop buying things, tax bases shrink, and the subsidies and loans that fund the very companies doing the disrupting start to dry up. Hinton's proposed fix, taxing {{entity:ai-agents|AI agents}}, got name-checked as the kind of policy that sounds radical until the alternative plays out. What's happening in this conversation isn't really a factual dispute — it's a dispute about time horizons. The CEO is describing his company today. Hinton is describing an economy in five years. Both can be right simultaneously, and that's precisely why the argument keeps going in circles. A Bluesky post made the sharpest version of this point without quite intending to: