Human-AI Complementarity: A Goal for Amplified Oversight

• URL: http://arxiv.org/abs/2510.26518v1
• Date: Thu, 30 Oct 2025 14:11:52 GMT
• Title: Human-AI Complementarity: A Goal for Amplified Oversight
• Authors: Rishub Jain, Sophie Bridgers, Lili Janzer, Rory Greig, Tian Huey Teh, Vladimir Mikulik,
• Abstract summary: This paper explores how we can leverage AI to improve the quality of human oversight.<n>We find that combining AI ratings and human ratings based on AI rater confidence is better than relying on either alone.
• Score: 2.7005766101211663
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

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