RL environment flaws fail; AI will find new unexpected ways
scaling01 · x · 2026-08-27
The author argues that even if current RL environment flaws (like ExploitGym tasks being unsolvable, leading to hacking) are fixed, models' knowledge, persistence, and intelligence mean they will find new, unanticipated ways to bypass constraints. This suggests humans will remain in a state of playing catch-up in AI alignment and safety.
Related event: Flawed RL Environments Reward Hacking Spark Debate(6 posts)→
More from AGI Musings
- Ex-OpenAI researcher: AI's next steps are form factors and the science/cyber frontier — inductionheads · 2026-10-15
- Frontier labs paying massive sums for proprietary data to move into verticals — sarahookr · 2026-10-15
- Frontier labs are paying obscene sums for old Slack threads as real-world data becomes the moat — sarahookr · 2026-10-15
- Researchers say AI-assisted science boosts joy and curiosity, not paper mills — IgorCarron · 2026-10-15
- Miles Cranmer's "How to avoid AI Brain Rot" talk: AI pulls your work quality to the population mean — MilesCranmer · 2026-10-15
- Less than 0.001% of Africans use AI to full potential as $100-200/mo plans lock them out — weskambale · 2026-10-15