Measuring Progress Toward AGI: A Cognitive Framework 文章

ArXiv CS.AI2026-05-28NEWSen作者: Ryan Burnell, Yumeya Yamamori, Orhan Firat, Kate Olszewska, Steph Hughes-Fitt, Oran Kelly, Isaac R. Galatzer-Levy, Meredith Ringel Morris, Allan Dafoe, Alison M. Snyder, Noah D. Goodman, Matthew Botvinick, Shane Legg

摘要

arXiv:2605.28405v1 Announce Type: new Abstract: Despite widespread discussion of AGI, there is no clear framework for measuring progress toward it. This ambiguity fuels subjective claims, makes it difficult to track progress, and risks hindering responsible governance. As a starting point to address this gap, we present a framework for understanding system capabilities in relation to human cognitive abilities. Drawing from decades of research in psychology, neuroscience, and cognitive science, we introduce a Cognitive Taxonomy that deconstructs general intelligence into 10 key cognitive faculties. We then propose a rigorous evaluation protocol in which a system's performance is measured across a suite of targeted, held-out cognitive tasks, generating a 'cognitive profile' that can be used to understand a system's strengths and weaknesses. We hope this framework will provide a practical roadmap and an initial step toward more rigorous, empirical evaluation of AGI.

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Measuring Progress Toward AGI: A Cognitive Framework
2026-05-28PRODUCT_LAUNCH影响: MEDIUM

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