Seeing the Goal, Missing the Truth: Human Accountability for AI Bias
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This research explores how human-defined goals influence the behavior of Large Language Models (LLMs) through purpose-conditioned cognition. Using financial prediction tasks, we show that revealing the downstream use (e.g., predicting stock returns or earnings) of LLM outputs leads the LLM to
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美国国家经济研究局创建时间:
2026-05-01



