This could be an interesting research paper by Google ML & AI researchers!
"... To understand AI capabilities across these cognitive abilities, we propose a three-stage evaluation protocol that benchmarks system performance in relation to human capabilities:
- Evaluate AI systems across a broad suite of cognitive tasks covering each ability, using held-out test sets to prevent data contamination
- Collect human baselines for the same tasks from a demographically representative sample of adults
- Map each AI system’s performance relative to the distribution of human performance in each ability
..."
From the 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."
Measuring progress toward AGI: A cognitive framework (blog post) "We’re introducing a framework to measure progress toward AGI, and launching a Kaggle hackathon to build the relevant evaluations."
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