RealBehavior: A Framework for Faithfully Characterizing Foundation Models' Human-like Behavior Mechanisms

• URL: http://arxiv.org/abs/2310.11227v1
• Date: Tue, 17 Oct 2023 12:58:17 GMT
• Title: RealBehavior: A Framework for Faithfully Characterizing Foundation Models' Human-like Behavior Mechanisms
• Authors: Enyu Zhou, Rui Zheng, Zhiheng Xi, Songyang Gao, Xiaoran Fan, Zichu Fei, Jingting Ye, Tao Gui, Qi Zhang, Xuanjing Huang
• Abstract summary: We introduce a framework, RealBehavior, which is designed to characterize the humanoid behaviors of models faithfully. Our findings suggest that a simple application of psychological tools cannot faithfully characterize all human-like behaviors.
• Score: 45.97077960079147
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Reports of human-like behaviors in foundation models are growing, with psychological theories providing enduring tools to investigate these behaviors. However, current research tends to directly apply these human-oriented tools without verifying the faithfulness of their outcomes. In this paper, we introduce a framework, RealBehavior, which is designed to characterize the humanoid behaviors of models faithfully. Beyond simply measuring behaviors, our framework assesses the faithfulness of results based on reproducibility, internal and external consistency, and generalizability. Our findings suggest that a simple application of psychological tools cannot faithfully characterize all human-like behaviors. Moreover, we discuss the impacts of aligning models with human and social values, arguing for the necessity of diversifying alignment objectives to prevent the creation of models with restricted characteristics.

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