Import AI 468: 23 RSI ideas; PostTrainBench+; and how trust and transparency interplay with AI racing
23 policy ideas for managing AI racing risks — what regulators actually need to do
Why it matters
As AI labs race toward frontier capabilities, policymakers are moving beyond abstract safety concerns to concrete governance frameworks. This collection of 'low-regret' policy recommendations from think-tank experts signals the transition from debate to implementation — directly affecting how practitioners navigate compliance, deployment timelines, and competitive positioning.
The key facts
9 to know23 actionable RSI (responsible scaling initiatives) policy ideas published by IFP
Focus on 'low-regret' policies — recommendations designed to be robust across multiple AI futures
Newsletter also covers PostTrainBench (post-training evaluation framework) and trust/transparency dynamics in competitive AI environment
Published August 2026 — emerging regulatory posture as frontier labs scale
IFP (think tank) published 23 policy recommendations for RSI (Racing-related Safety Issues)
Framed as 'low-regret' policies — actionable across political and international contexts
Published Aug 2026; import AI newsletter coverage suggests policy is gaining practitioner/enthusiast attention
Touches trust, transparency, and competitive dynamics — not just safety
No specific numbers on adoption or government endorsement yet in excerpt
Go to the source
Import AI (Blog)jack-clark.net
Publisher excerpt: Welcome to Import AI, a newsletter about AI research. Import AI runs on arXiv, cappuccinos, and feedback from readers. If you’d like to support this, please subscribe. Subscribe now Want to be able to deal with RSI? Here are 23 actionable policy ideas:…IFP serves up some “low-regret” policy…