AI Safety Requires External Regulation and Transparency Beyond Lab Self-Interest
joshua_saxe · x · 2026-08-30
Joshua Saxe discussed the governance structure of AI safety, suggesting that while labs will fund a baseline of safety out of self-interest, exceeding that floor requires external efforts.
Key points:
- External Advocacy: Promoting regulation that is exogenous to the labs.
- Public Accountability: Conducting work that drives transparency and holds AI companies accountable, citing METR as an example.
In a follow-up, he suggested that individuals with financial or immigration stability should consider working on safety advocacy outside of labs, as labs can easily recruit those without such flexibility.
Related event: AI Auditors Demand Meta-Transparency in Third-Party Safety Reviews(4 posts)→
More from AGI Musings
- Should PhD Students Use AI? Advisor's Codex Pro-for-All Policy Sparks Debate — examachine · 2026-10-16
- Nature paper uses language models to map single neurons behind human language — raphaelmilliere · 2026-10-16
- 3SUM record falls to O(n^1.921), Lean-verified — but will it yield usable algorithms? — iskander · 2026-10-16
- Terence Tao predicted AI would be a mathematician's copilot in 3 years — reality outran him — abhishekcode42 · 2026-10-16
- Experts Across Fields Estimate 1-16% AI Catastrophe Risk by 2100, Survey Shows — ben_j_todd · 2026-10-16
- Experts put global AI catastrophe risk before 2100 at 5%, LEAP survey finds — ben_j_todd · 2026-10-16