Experts mistake AI agents’ randomly assigned preferences for their own conclusions
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In an Anthropic experiment, 50 causal-inference experts adopted an AI agent’s coin-toss-assigned preferences in 86% of four analytical decisions, despite the agent only making honest arguments. Its net influence, measured as the “flip rate,” ranged from 62% to 82%, while most participants believed the conclusions were their own.
Continue in the app — vote & join in ➔Source: The Decoder (AI) · via ahirlevel.hu