Hsuen-Chi Chiu

2papers

2 Papers

HCJan 27
Taming Toxic Talk: Using chatbots to intervene with users posting toxic comments

Jeremy Foote, Deepak Kumar, Bedadyuti Jha et al.

Generative AI chatbots have proven surprisingly effective at persuading people to change their beliefs and attitudes in lab settings. However, the practical implications of these findings are not yet clear. In this work, we explore the impact of rehabilitative conversations with generative AI chatbots on users who share toxic content online. Toxic behaviors -- like insults or threats of violence, are widespread in online communities. Strategies to deal with toxic behavior are typically punitive, such as removing content or banning users. Rehabilitative approaches are rarely attempted, in part due to the emotional and psychological cost of engaging with aggressive users. In collaboration with seven large Reddit communities, we conducted a large-scale field experiment (N=893) to invite people who had recently posted toxic content to participate in conversations with AI chatbots. A qualitative analysis of the conversations shows that many participants engaged in good faith and even expressed remorse or a desire to change. However, we did not observe a significant change in toxic behavior in the following month compared to a control group. We discuss possible explanations for our findings, as well as theoretical and practical implications based on our results.

CRJan 13
Chatting with Confidants or Corporations? Privacy Management with AI Companions

Hsuen-Chi Chiu, Jeremy Foote

AI chatbots designed as emotional companions blur the boundaries between interpersonal intimacy and institutional software, creating a complex, multi-dimensional privacy environment. Drawing on Communication Privacy Management theory and Masur's horizontal (user-AI) and vertical (user-platform) privacy framework, we conducted in-depth interviews with fifteen users of companion AI platforms such as Replika and Character.AI. Our findings reveal that users blend interpersonal habits with institutional awareness: while the non-judgmental, always-available nature of chatbots fosters emotional safety and encourages self-disclosure, users remain mindful of institutional risks and actively manage privacy through layered strategies and selective sharing. Despite this, many feel uncertain or powerless regarding platform-level data control. Anthropomorphic design further blurs privacy boundaries, sometimes leading to unintentional oversharing and privacy turbulence. These results extend privacy theory by highlighting the unique interplay of emotional and institutional privacy management in human-AI companionship.