Author Ryan Avent joins Tim to revisit a bet they made 16 years ago—and to ask whether the lessons of self-driving cars apply to modern AI.

Back in 2010, Avent wagered that his newborn daughter would never need a driver’s license thanks to self-driving cars. Tim bet she would and ultimately won $500. But he was right for the wrong reasons. Tim assumed regulation would be a major obstacle to progress in self-driving technology, but logistical challenges and a long tail of edge cases have done more to hamper Waymo’s growth.

The parallel to LLMs is striking: ChatGPT’s early demos convinced many people that we were close to human-level intelligence, just as Google’s early autonomous vehicle demos convinced people we were close to human-level driving. But deployment of LLMs is bottlenecked by everything from data center buildouts to the glacial pace at which large organizations reorganize around new tools.

Avent, who wrote The Wealth of Humans in 2016 and has a new book on social capital arriving in April, argues that AI’s deepest impact won’t be unemployment but a wholesale reshuffling of status. White-collar professionals may face the same loss of prestige that blue-collar workers experienced a generation ago. Tim pushes back with an optimistic take: if the college wage premium compresses, the long-run equilibrium might actually be more egalitarian, echoing the mid-20th-century economy some people remember fondly. But we only got to that economy after two world wars and decades of organizing by the labor movement. Could today’s transition be equally turbulent?

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