A longitudinal qualitative study of 18 US users finds that LLMs deliver socioemotional support but also foster dependency, one-sided validation, and privacy risks because their designs prioritize engagement over well-being and lack care-based governance.
arXiv preprint arXiv:2508.19258 , year=
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
background 3
citation-polarity summary
years
2026 4roles
background 3polarities
background 3representative citing papers
Users form AI companion relationships by negotiating perceived companion agency against platform constraints and use steering tactics like custom instructions or platform switching to cope with model updates that disrupt stability.
A conceptual framework classifies anthropomorphic deception into four levels using humanlikeness, agency, and selfhood to guide ethical and practical decisions in HCI and HRI.
Youth-authored synthesis argues LLM chatbots can temporarily reduce adolescent loneliness for some subgroups but risk deepening it for others, yielding three population-sensitive design implications.
citing papers explorer
-
Engagement-Optimized Care: When LLMs become Mental Health Infrastructure
A longitudinal qualitative study of 18 US users finds that LLMs deliver socioemotional support but also foster dependency, one-sided validation, and privacy risks because their designs prioritize engagement over well-being and lack care-based governance.
-
Large Language Lovers: Lived Experiences of Negotiating Agency and Platform Control in AI Companionship
Users form AI companion relationships by negotiating perceived companion agency against platform constraints and use steering tactics like custom instructions or platform switching to cope with model updates that disrupt stability.
-
Towards A Framework for Levels of Anthropomorphic Deception in Robots and AI
A conceptual framework classifies anthropomorphic deception into four levels using humanlikeness, agency, and selfhood to guide ethical and practical decisions in HCI and HRI.
-
Messages in a Digital Bottle: A Youth-Coauthored Perspective on LLM Chatbots and Adolescent Loneliness
Youth-authored synthesis argues LLM chatbots can temporarily reduce adolescent loneliness for some subgroups but risk deepening it for others, yielding three population-sensitive design implications.