Attitudes‚ Imagined Roles‚ and Governance Boundaries for AI in Decentralized Social Media

Abstract

Decentralised social media (DSM) platforms such as Mastodon offer community-governed alternatives to corporate social networks but place substantial governance burdens on volunteer operators. As interest grows in applying artificial intelligence (AI) to support this work, little is known about whether DSM operators want AI, what roles they consider appropriate, and what governance boundaries they require. We conducted semi-structured interviews with 20 operators across Mastodon, Pixelfed, PeerTube, Lemmy, Pleroma, and Funkwhale, using generative feature probes and speculative scenarios to explore their perceptions of AI. Operators rejected AI as an autonomous actor, instead envisioning it as governance infrastructure that provides contextual intelligence, supports cross-instance coordination, and sustains community and moderator well-being. They also articulated strict boundaries rooted in DSM values, including human accountability, reversibility, transparency, community-centred configuration, and strong data-governance constraints. We contribute empirical insights and design implications for AI compatible with decentralised, federated social media.