Identifying, Evaluating, and Mitigating Risks of AI Thought Partnerships

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Authors: Kerem Oktar, Katherine M. Collins, José Hernández‐Orallo, Diane Coyle, Stephen Cave, Adrian Weller, Ilia Sucholutsky
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Abstract

AI systems have historically been used as tools that execute narrowly defined tasks. Yet recent advances in AI have unlocked possibilities for a new class of models that genuinely collaborate with humans in complex reasoning, from conceptualizing problems to brainstorming solutions. Such AI thought partners enable novel forms of collaboration and extended cognition, yet they also pose major risks—including and beyond risks of typical AI tools and agents. In this Commentary, we systematically characterize risks of AI thought partners through a novel framework that identifies risks at multiple levels of analysis, including Real-time, Individual, and Societal risks arising from collaborative cognition (RISc). We leverage this framework to propose concrete metrics for risk evaluation and finally suggest specific mitigation strategies for developers and policymakers. As AI thought partners continue to proliferate, these strategies can help prevent major harms and ensure that humans actively benefit from productive thought partnerships.

Fields of Study & Subjects

Ethics and Social Impacts of AI Explainable Artificial Intelligence (XAI) Embodied and Extended Cognition

Publication details

Journal / source
ACM AI Letters
Volume
1
Issue
2
Pages
1–6
Publication date
10 June 2026
Language
EN