Human-AI Complementarity: A Goal for Amplified Oversight

작성자

카테고리:

← 피드로
arXiv cs.AI · Rishub Jain, Sophie Bridgers, Lili Janzer, Rory Greig, Tian Huey Teh, Vladimir Mikulik · 2026-06-26 AI

[Submitted on 30 Oct 2025 (v1), last revised 25 Jun 2026 (this version, v2)]

View PDF HTML (experimental)

Abstract:Human feedback is critical for aligning AI systems to human values. As AI capabilities improve and AI is used to tackle more challenging tasks, verifying quality and safety becomes increasingly challenging. This paper explores how we can leverage AI to improve the quality of human oversight. We focus on an important safety problem that is already challenging for humans: fact-verification of AI outputs. We find that combining AI ratings and human ratings based on AI rater confidence is better than relying on either alone. Giving humans an AI fact-verification assistant further improves their accuracy, but the type of assistance matters. Displaying AI explanation, confidence, and labels leads to over-reliance, but just showing search results and evidence fosters more appropriate trust. These results have implications for Amplified Oversight — the challenge of combining humans and AI to supervise AI systems even as they surpass human expert performance.

Submission history

From: Rishub Jain [view email]
[v1] Thu, 30 Oct 2025 14:11:52 UTC (6,508 KB)
[v2] Thu, 25 Jun 2026 13:34:02 UTC (3,407 KB)

원문에서 계속 ↗

추출 본문 · 출처: arxiv.org · https://arxiv.org/abs/2510.26518

코멘트

답글 남기기

이메일 주소는 공개되지 않습니다. 필수 필드는 *로 표시됩니다