Problem
Research questions and friction points this paper is trying to address.
mind perception
human-AI companionship
lexical indicators
agency
experience
Lexical Indicators of Mind Perception in Human-AI Companionship
🤖 AI Summary
This study addresses the limitations of existing research that relies heavily on subjective self-reports to examine how humans unconsciously ascribe mental capacities to artificial intelligence in language. For the first time, it introduces linguistic markers of mind perception into the context of human–AI companionship by analyzing naturalistic discussions about AI companions on Reddit. Combining inductive and deductive textual analysis with lexical co-occurrence methods, the research identifies a reliable set of linguistic indicators that capture agency and experience—two core dimensions of mind perception. Findings reveal that certain markers are significantly associated with users’ critical reflections on the perceived authenticity of AI companions and their underlying ethical imaginaries, thereby uncovering a linguistic bridge between automatic mental state attribution and normative discourse.
📝 Abstract
Mind perception (MP) is a psychological phenomenon in which humans automatically infer that another entity has a mind and/or mental capacities, usually understood in two dimensions (perceived agency and experience capacities). Despite MP's centrality to many social processes, understanding how MP may function in humans' machine companionship relations is limited. This is in part due to reliance on self reports and the gap between automatic MP processes and more purposeful and norm governed expressions of MP. We here leverage MP signaling language to explore the relationship between MP and AI companionship in humans' natural language. We systematically collected discussions about companionship from AI dedicated Reddit forums and examined the cooccurrence of words (a) known to signal agentic and experiential MP and those induced from the data and (b) discussion topics related to AI companionship. Using inductive and deductive approaches, we identify a small set of linguistic indicators as reasonable markers of MP in human/AI chat, and some are linked to critical discussions of companion authenticity and philosophical and ethical imaginaries.
Innovation
Methods, ideas, or system contributions that make the work stand out.
mind perception
lexical indicators
human-AI companionship
natural language analysis
agency and experience
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