Measuring Human-Like Bias in LLMs? A Critique of Human-Derived Bias Constructs in LLM Evaluation
Researchers use human psychological constructs like implicit bias to study Large Language Models (LLMs). This paper critiques this approach by showing a gap between human psychology and model outputs. It introduces a framework to clarify that model evidence can support different claims, requiring researchers to distinguish between simple associations and true cognitive analogies.