Conversational Agents to Facilitate Deliberation on Harmful Content in WhatsApp Groups
May 30, 2024 Β· Declared Dead Β· π Proc. ACM Hum. Comput. Interact.
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Authors
Dhruv Agarwal, Farhana Shahid, Aditya Vashistha
arXiv ID
2405.20254
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CY
Citations
13
Venue
Proc. ACM Hum. Comput. Interact.
Last Checked
4 months ago
Abstract
WhatsApp groups have become a hotbed for the propagation of harmful content including misinformation, hate speech, polarizing content, and rumors, especially in Global South countries. Given the platform's end-to-end encryption, moderation responsibilities lie on group admins and members, who rarely contest such content. Another approach is fact-checking, which is unscalable, and can only contest factual content (e.g., misinformation) but not subjective content (e.g., hate speech). Drawing on recent literature, we explore deliberation -- open and inclusive discussion -- as an alternative. We investigate the role of a conversational agent in facilitating deliberation on harmful content in WhatsApp groups. We conducted semi-structured interviews with 21 Indian WhatsApp users, employing a design probe to showcase an example agent. Participants expressed the need for anonymity and recommended AI assistance to reduce the effort required in deliberation. They appreciated the agent's neutrality but pointed out the futility of deliberation in echo chamber groups. Our findings highlight design tensions for such an agent, including privacy versus group dynamics and freedom of speech in private spaces. We discuss the efficacy of deliberation using deliberative theory as a lens, compare deliberation with moderation and fact-checking, and provide design recommendations for future such systems. Ultimately, this work advances CSCW by offering insights into designing deliberative systems for combating harmful content in private group chats on social media.
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