Clarifying Anthropomorphism for Robots and AI: A Critical Review
摘要
‘Anthropomorphism’, broadly understood as associating humanness with nonhuman entities, has been widely studied in the context of human interactions with social robots and computers. However, despite its centrality in human-machine interaction studies, the idea remains confusing and requires further clarification. This paper provides a critical conceptual review of how anthropomorphism is essentially characterized or conceptualized by scholars for robots and artificial intelligence (AI) systems, which will be increasingly incorporated into social robotics. We identify key dimensions of anthropomorphism that have not been sufficiently unpacked, namely: ‘object-related’ anthropomorphism; three types of ‘subject-related’ anthropomorphism; alleged attributive processes linking human-like features to machines; and normative views about whether such attributions constitute epistemic errors. We then discuss vagueness, ambiguity, and disagreement surrounding characterizations of anthropomorphism which may generate confusion and impede clear communication. In a constructive provocation, we ask if the term itself might be too compromised to remain useful, before offering recommendations for more precise and clearer terminology. By analyzing fundamental characterizations of anthropomorphism, this paper offers insights to scholars in robotics and AI, Human-Computer Interaction, cognitive science, and social sciences, aiming to support more coherent discussions and effective investigations.