AIMay 27

Measuring Progress Toward AGI: A Cognitive Framework

arXiv:2605.2840588.85 citations
AI Analysis

This work addresses the lack of a standardized evaluation framework for AGI, which is a problem for researchers and policymakers tracking progress and ensuring responsible governance.

The authors propose a framework for measuring progress toward AGI based on a Cognitive Taxonomy of 10 key faculties and a rigorous evaluation protocol, aiming to replace subjective claims with empirical assessment.

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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