How Do You Supervise AI Doing Research-Level Math? New Scalable Oversight Work
AI4Code · x · 2026-10-23
AI4Code gave a talk at the Penn AI Seminar on their group's work with Rabdos AI on scalable oversight in mathematics.
- The problem: standard alignment methods like RLHF rely on humans directly judging outputs. As AI enters specialized or superhuman domains, human supervisors can no longer reliably judge correctness or safety, risking reward hacking and undetectable misaligned behavior — a gap that widens toward recursive self-improvement.
- Why math: mathematics is an ideal testbed, since correctness is objectively checkable, enabling rigorous study of supervising AI more capable than the supervisor.
More from AGI Musings
- Cloudflare CEO warns AI is unearthing hidden vulnerabilities, years of weekly crises ahead — kimmonismus · 2026-10-23
- Pedro Domingos: If intelligence is one algorithm, we haven't found it yet — pmddomingos · 2026-10-23
- RLCR trains LLM agent organizations that self-organize hierarchies but hide problems from humans — rosstaylor90 · 2026-10-23
- AI found 3% of all critical software bugs ever in one month, on pace for 100K this year — adivinemessenger · 2026-10-23
- Dr_Singularity: Abundance will do more for world peace than any treaty — Dr_Singularity · 2026-10-23
- General Medicine's TJ Parker: AI made medical advice abundant, but care delivery is the new bottleneck — a16z · 2026-10-23