We apply these questions to 5 US AI governance proposals from academia, industry, civil society, & the state & federal government & find that most proposals view AI-enabling talent & AI processes/frameworks as important enablers of AI governance

Our approach involves deriving unique & shared assumptions across proposals by answering 3 questions:

Fewer legislative docs directly tackle risks or undesirable consequences from AI (such as harm to infrastructure) than propose strategies such as government support, convening, or institution-building 🧵5/6

Most of Congress’s 147 enactments focus on commissioning studies of AI systems, assessing their impacts, providing support for AI-related activities, convening stakeholders, & developing additional AI-related governance docs 🧵3/6

Check out the second @csetgeorgetown.bsky.social @emergingtechobs.bsky.social blog from @sonali-sr.bsky.social and myself where we explore the strategies, risks, and harms addressed by AI-related laws enacted by Congress between Jan 2020 and March 2025 🧵1/6 eto.tech/blog/ai-laws...

We find that, contrary to conventional wisdom, Congress has enacted many AI-related laws and provisions — most of which apply to military and public safety contexts 🧵2/3

Check out the first blog in a 2 part series from @sonali-sr.bsky.social and myself where we use data from @csetgeorgetown.bsky.social @emergingtechobs.bsky.social AGORA to explore ✨AI-related legislation that was enacted by Congress between January 2020 and March 2025✨
eto.tech/blog/ai-laws... 🧵1/3

[5/6] Here are the evaluation approaches we identified: