AI & ML
Relational Complexity: Making Sense of Social Companion AI Use
arXiv cs.HC0 views
arXiv:2610.27419v1 Announce Type: new Abstract: The adoption of social companion AI (SCAI) is often framed in terms of the positive features it offers users, including its nonjudgemental nature, agreeableness, and availability. Here, we argue the appeal of these features primarily arises from the difficulties inherent in human sociality. SCAI reduces what we term relational complexity, or the demands and risks inherent in human relationships. Drawing insights from studies of human cognition, communication, and human-computer interaction, we identify six distinct sites of relational complexity that we posit are integral to understanding SCAI adoption. These include: (i) relationship formation and dissolution; (ii) achieving mutual understanding; (iii) interpersonal motives and strategic uncertainty; (iv) social partner evaluation and self-presentation; (v) social embeddedness and information flow; and (vi) reciprocity and relationship maintenance. By attenuating relational complexity, SCAI offers users some of the experiences associated with companionship while reducing the demands intrinsic to obtaining such experiences from another person. However, the lower interpersonal risk and diminished cognitive load that attracts users to SCAI may contribute to myriad negative impacts, including relationship displacement, social demotivation, social deskilling, and risks to privacy. The concept of relational complexity thus provides a framework for studying both the appeal of artificial companionship and its implications for human wellbeing.
Source:https://arxiv.org/abs/2610.27419PreviousInspectable LLM-Simulated Participants for Qualitative Interview RehearsalNextBias and Reliability in Learning-Style Inference from Student--AI Dialogues: An Evaluation of GPT-4o and Gemini 2.0 Flash
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