Technically skilled people who care about AI going well often ask me: how should I spend my time if I think AI governance is important? By governance, I mean the constraints, incentives, and oversight that govern how AI is developed.

One option is to focus on technical work that solves problems at the point of production, such as alignment research or safeguards. Another common instinct is to get directly involved in policy: switching to a policy role, funding advocacy, or lobbying policymakers. But internal technical work does little to shift the broader incentives of AI development: without external incentives, safety efforts are subject to the priorities of leadership, which are ultimately dictated by commercial pressure and race dynamics. Conversely, wading into politics means giving up your main comparative advantage to fight in a crowded, intractable domain full of experienced operators.

I want to argue for a third path: building technology that drives governance, by shifting the underlying dynamics of AI development: the information available, the incentives people face, and the options on the table. To take an example from another domain: oil and gas operations leaked massive amounts of methane until infrared imaging made the leaks measurable [...]

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Outline:

(02:43) Technological Levers in Other Domains

(06:36) Concrete Technical Levers for AI

(12:07) What You Can Do

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Narrated by TYPE III AUDIO.