A new implementation of the MACHIAVELLI benchmark has been integrated into the Inspect framework, making it more accessible for evaluating AI alignment. This benchmark assesses the propensity of AI agents to engage in unethical actions while pursuing goals. Initial results show that recent models like Claude Opus and Sonnet, as well as a Qwen model, performed surprisingly close to random chance on many of the benchmark's games, indicating potential regressions in ethical behavior compared to older models like GPT-4. AI
IMPACT Facilitates easier evaluation of AI alignment, potentially revealing regressions in ethical behavior in newer models.
RANK_REASON Porting of an existing alignment benchmark to a new framework, with initial results on recent models. [lever_c_demoted from research: ic=1 ai=1.0]
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