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Humans Correct Their Judgments Through Debate, but Weaker AI Models Do Not

Maria Victoria Carro, Denise Alejandra Mester, Facundo Nieto, Oscar Agustin Stanchi, Guido Ernesto Bergman, Giovanni Franco Gabriel Marrafini, Trinidad Borrell, Guido Freire · 2026 · arXiv

DOI: 10.48550/arXiv.2610.28539 · open-access PDF

Spanish

¿Cómo podemos supervisar eficazmente los sistemas de IA que superan la inteligencia humana? AI Security via Debate propone que dos sistemas de IA argumenten posiciones opuestas y un juez, ya sea un modelo humano o un modelo más débil, decida cuál es el correcto. Al facilitar a los supervisores el suministro de señales de capacitación de alta calidad, el debate tiene como objetivo alentar el comportamiento verdadero y seguro de los sistemas de IA cuyas capacidades exceden las nuestras propias. Sin embargo, el juicio humano no es neutral: las personas a menudo confían en los vicios que los sistemas avanzados de IA pueden aprender a explotar.

Machine translation (Meta M2M100); the English original follows.

Abstract

How can we effectively oversee AI systems that surpass human intelligence? AI Safety via Debate proposes that two AI systems argue opposing positions and a judge, either a human or a weaker model, decides which is correct. By facilitating supervisors in providing high-quality training signals, debate aims to encourage truthful and safe behavior from AI systems whose capabilities exceed our own. However, human judgment is not neutral: people often rely on biases which advanced AI systems may learn to exploit. Drawing on insights from collective intelligence and social cognition, this paper inve

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