Anthropomorphic Behaviors of AI
For AI developers and policymakers, this provides a foundational taxonomy for detecting anthropomorphism, though it is an observational study without quantitative results.
This paper systematically categorizes anthropomorphic behaviors in AI outputs, developing a taxonomy to detect human-like expressions in ChatGPT responses, which aids developers and policymakers in balancing benefits and risks.
Anthropomorphism in artificial intelligence (AI) is a growing area of interest, as AI systems increasingly exhibit human-like expressions, behaviors and interaction styles. This research serves as a systematic observation and categorization of anthropomorphic behaviors in AI outputs. Anthropomorphic behavior refers to the deliberate or emergent manifestation of human-like expressions or linguistic cues in system outputs, such as demonstrating empathy. Using a behaviorally driven taxonomy, our study identifies key forms of anthropomorphic behaviors in the responses of ChatGPT and examines their implications for the theory, practice and ethics of AI systems. The taxonomy enables more nuanced detection of anthropomorphism, offering value to developers and policymakers in balancing the benefits with the potential risks. This work contributes to the academic discourse by providing a foundation for future efforts to refine, expand, and automate the detection of anthropomorphic behavior across diverse AI applications.