People in decentralized social media set conditional limits on generative AI use
"Okay, I've Actually Softened My Take on This": How People in Decentralized Social Media Reason about the Appropriateness of Generative AI
Human-Computer Interaction
Summary
Generative AI tools are becoming more common in social media, but people wonder when and how they should be used, especially on platforms without a central authority. The authors spoke to users, developers, and moderators from Mastodon and Bluesky to learn how they decide if generative AI is appropriate. They found that people draw careful boundaries based on the technology, how it’s integrated, and how it’s used. Showing these boundaries clearly can help design better rules and tools for managing generative AI on decentralized platforms.
What this means in practice
- •For decentralized social media developers: Design platform features that reflect community-drawn boundaries around generative AI use for better governance.
- •For social media moderators: Create moderation guidelines informed by diverse user perspectives on when generative AI content is appropriate.
Authors
Romina Mahinpei, Manoel Horta Ribeiro, Andrés Monroy-Hernández, Sohyeon Hwang
Abstract
Generative AI (GenAI) is increasingly integrated into social media, raising questions about whether, where, and how it belongs. In decentralized social media (DSM), these decisions are distributed across users, developers, moderators, and administrators, making GenAI a collective governance challenge. At the same time, public discourse often flattens arguments to broad pro- or anti-AI positions that offer little insight into what people actually find (in)appropriate and why. Through 20 semi-structured interviews with people from Mastodon and Bluesky, structured around seven GenAI scenarios, we examine how people reason about GenAI's appropriateness in DSM. We find that participants drew conditional boundaries around particular GenAI configurations through distinct, salient, and weighted considerations spanning technology, integration, and use. We conceptualize this as boundary drawing and show how making such boundaries visible can support more grounded design, policy, and collective deliberation around GenAI in DSM.