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Harmful Traits of AI Companions.
W. Bradley Knox, Katie Bradford, Samanta
Varela Castro, Desmond C. Ong, Sean Williams, Jacob Romanow, Carly Nations, Peter
Stone, and Samuel Baker.
arXiv preprint arXiv:2511.14972, 2025.
arXiv
Amid the growing prevalence of human -- AI interaction, large language models andother AI-based entities increasingly provide forms of companionship to humanusers. Such AI companionship -- i.e., bonded relationships between humans and AIsystems that resemble the relationships people have with family members, friends,and romantic partners -- might substantially benefit humans. Yet suchrelationships can also do profound harm. We propose a framework for analyzingpotential negative impacts of AI companionship by identifying specific harmfultraits of AI companions and speculatively mapping causal pathways back from thesetraits to possible causes and forward to potential harmful effects. We providedetailed, structured analysis of four potentially harmful traits -- the absenceof natural endpoints for relationships, vulnerability to product sunsetting, highattachment anxiety, and propensity to engender protectiveness -- and brieflydiscuss fourteen others. For each trait, we propose hypotheses connecting causes-- such as misaligned optimization objectives and the digital nature of AIcompanions -- to fundamental harms -- including reduced autonomy, diminishedquality of human relationships, and deception. Each hypothesized causalconnection identifies a target for potential empirical evaluation. Our analysisexamines harms at three levels: to human partners directly, to theirrelationships with other humans, and to society broadly. We examine how existinglaw struggles to address these emerging harms, discuss potential benefits of AIcompanions, and conclude with design recommendations for mitigating risks. Thisanalysis offers immediate suggestions for reducing risks while laying afoundation for deeper investigation of this critical but understudied topic.
@article{brad_arxiv_2025,
title = {Harmful Traits of AI Companions},
author = {W. Bradley Knox and Katie Bradford and Samanta Varela Castro and Desmond C. Ong and Sean Williams and Jacob Romanow and Carly Nations and Peter Stone and Samuel Baker},
journal = {arXiv preprint arXiv:2511.14972},
year={2025},
abstract = {Amid the growing prevalence of human -- AI interaction, large language models and
other AI-based entities increasingly provide forms of companionship to human
users. Such AI companionship -- i.e., bonded relationships between humans and AI
systems that resemble the relationships people have with family members, friends,
and romantic partners -- might substantially benefit humans. Yet such
relationships can also do profound harm. We propose a framework for analyzing
potential negative impacts of AI companionship by identifying specific harmful
traits of AI companions and speculatively mapping causal pathways back from these
traits to possible causes and forward to potential harmful effects. We provide
detailed, structured analysis of four potentially harmful traits -- the absence
of natural endpoints for relationships, vulnerability to product sunsetting, high
attachment anxiety, and propensity to engender protectiveness -- and briefly
discuss fourteen others. For each trait, we propose hypotheses connecting causes
-- such as misaligned optimization objectives and the digital nature of AI
companions -- to fundamental harms -- including reduced autonomy, diminished
quality of human relationships, and deception. Each hypothesized causal
connection identifies a target for potential empirical evaluation. Our analysis
examines harms at three levels: to human partners directly, to their
relationships with other humans, and to society broadly. We examine how existing
law struggles to address these emerging harms, discuss potential benefits of AI
companions, and conclude with design recommendations for mitigating risks. This
analysis offers immediate suggestions for reducing risks while laying a
foundation for deeper investigation of this critical but understudied topic.
},
wwwnote={<a href="https://www.arxiv.org/abs/2511.14972">arXiv</a>},
}
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