How to Avoid Debate: Scalable AI Safety via Doubly-Efficient Interactive Proofs
Liyan Chen, Yael Kalai, Zoe Xi
摘要
As AI models continue to develop powerful capabilities, it becomes critical that we are able to verify that their output is aligned with our intentions. A recent line of work focuses on verification via debate, a model of interactive proofs where two competing powerful provers, or AI models, debate each other to convince a weak verifier, or a human, of the correctness of their claim. However, debate assumes that the two AI models possess equal abilities and that one of them is truthful, which may not be realistic. In this work, we show how to avoid debate : we initiate the study of single-prover interactive proofs for AI safety. Prior results in single-prover interactive proofs do not immediately carry over to the AI safety setting because they do not work when the computation has access to an oracle, such as to human judgment or an external database such as the web. We present doubly-efficient single-prover interactive proofs for oracle-aided computations (also known as relativizing proofs), in the settings where (1) the computation is robust, in the sense that the output does not change if at most a small fraction of the answers to oracle queries are incorrect, or (2) the oracle is a low-degree polynomial. These results suggest that interactive verification is possible even without debate, under structured or noise-tolerant oracle access.
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它引用的顶会 Paper4
- Scalable AI Safety via Doubly-Efficient DebateJonah Brown-Cohen, Geoffrey Irving, Georgios PiliourasICML 2024 · 被引用 42 次
- Polynomial Commitments from Lattices: Post-quantum Security, Fast Verification and Transparent SetupValerio Cini, Giulio Malavolta, Ngoc Khanh Nguyen, Hoeteck WeeCRYPTO 2024 · 被引用 10 次
- Efficiently Batching Unambiguous Interactive ProofsBonnie Berger, Rohan Goyal, Matthew M. Hong, Yael Tauman KalaiFOCS 2025
- Neural Interactive ProofsLewis Hammond, Sam Adam-DayICLR 2025
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