This podcast interviews two researchers who studied cooperation among different Large Language Models (LLMs) in a simulated society using a "donor game" experiment. The researchers found significant differences in cooperation levels between LLMs like Claude 3.5 (high cooperation, improving over time), Gemini 1.5 (low cooperation, no improvement), and GPT-4.0 (very low cooperation, slight decline). This highlights the blind spots in current AI evaluation methods, which don't adequately assess social interaction capabilities. The researchers suggest that future research should incorporate human participation and explore more complex social scenarios to better understand the societal impact of LLMs. The study's code is open-sourced, encouraging broader participation in this crucial area of AI research.
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