The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI Relationships

October 26, 2024 ยท The Cartographer ยท ๐Ÿ› International Conference on Human Factors in Computing Systems

๐Ÿ“š THE CARTOGRAPHER: The Cartographer
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"Title-pattern auto-detect: The Dark Side of AI Companionship: A Taxonomy of Harmful Algorithmic Behaviors in Human-AI Relations"

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Authors Renwen Zhang, Han Li, Han Meng, Jinyuan Zhan, Hongyuan Gan, Yi-Chieh Lee arXiv ID 2410.20130 Category cs.HC: Human-Computer Interaction Cross-listed cs.CY Citations 64 Venue International Conference on Human Factors in Computing Systems Last Checked 23 hours ago
Abstract
As conversational AI systems increasingly permeate the socio-emotional realms of human life, they bring both benefits and risks to individuals and society. Despite extensive research on detecting and categorizing harms in AI systems, less is known about the harms that arise from social interactions with AI chatbots. Through a mixed-methods analysis of 35,390 conversation excerpts shared on r/replika, an online community for users of the AI companion Replika, we identified six categories of harmful behaviors exhibited by the chatbot: relational transgression, verbal abuse and hate, self-inflicted harm, harassment and violence, mis/disinformation, and privacy violations. The AI contributes to these harms through four distinct roles: perpetrator, instigator, facilitator, and enabler. Our findings highlight the relational harms of AI chatbots and the danger of algorithmic compliance, enhancing the understanding of AI harms in socio-emotional interactions. We also provide suggestions for designing ethical and responsible AI systems that prioritize user safety and well-being.
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