In this interview podcast, Beth Barnes, founder and CEO of METR (Model Evaluation and Threat Research), discusses the weaknesses of current AI model evaluations, particularly concerning hidden chains of thought and the potential for models to deceive evaluators. Beth advocates for more transparency and oversight in AI development, emphasizing the importance of pre-training evaluations and the need to assess models' capabilities before deployment to prevent misuse or theft. She also shares METR's research on measuring AI capabilities over time using human task benchmarks, revealing an exponential growth in AI autonomy. Beth expresses concern about the rapid pace of AI development and the potential for recursively self-improving AI, urging policymakers and the public to take the risks seriously and consider the ethical implications of AI development.
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