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20242026
most citedThe Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI Relationships

111 citations · 152 across the 14 of their papers we have counts for

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12 papers · 1 filter

cs.HC2026

Stereotypically Yours: Portrayal and Perception of Race-Coded AI Companions

Wang Claire, Jiayue Melissa Shi, Agam Goyal +4

AI companions can purportedly adopt racial personas, raising questions about how they represent identity and how users interpret these portrayals. We combined an algorithmic audit…

cs.HC2026

Disrupted Companionship: A Risk Assessment Framework and Cross-Platform Quantitative Analysis of Psychosocial Responses to AI Companion Disruptions

Chau Do, Yunhao Yuan, Koustuv Saha +2

AI companions can provide meaningful relationships, yet these relationships remain vulnerable to platform-initiated changes. We study AI companion disruptions: platform changes tha…

cs.HC2026

When AI Companions Disappear: Relational Continuity and Collective Contestation during China's National AI Regulatory Transition

Yunhao Yuan, Kejia Zhang, Yuqi Niu +3

AI model updates and service withdrawals can disrupt relationships with AI companions, but research has largely examined individual platform events. Less is known about users' resp…

cs.HC2026

Push and Pushback in Contesting AI: Demands for and Resistance to Accountability

Yulu Pi, Lucas Lichner, Jae Woo Lee +3

As AI becomes increasingly embedded in daily life, it has been shown to fail critically, cause harm, and spark public controversy, prompting affected communities, workers, and publ…

cs.HC2026

The Fragility of AI Companionship: Ontological, Structural, and Normative Uncertainty in Human-AI Relationships

Renwen Zhang, Lezi Xie

As generative AI chatbots become more personalized and emotionally responsive, they increasingly serve as companions, friends, and romantic partners. Yet these relationships are ac…

cs.HC2026

Designing Computational Tools for Exploring Causal Relationships in Qualitative Data

Han Meng, Qiuyuan Lyu, Peinuan Qin +4

Exploring causal relationships for qualitative data analysis in HCI and social science research enables the understanding of user needs and theory building. However, current comput…