Conference item
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 crossinstance 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.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Version of record, pdf, 603.6KB, Terms of use)
-
- Publisher copy:
- 10.1145/3772318.3790295
Authors
- Publisher:
- Association for Computing Machinery
- Host title:
- CHI '26: Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
- Article number:
- 330
- Publication date:
- 2026-04-13
- Acceptance date:
- 2026-01-15
- Event title:
- ACM conference on Human Factors in Computing Systems (CHI 2026)
- Event location:
- Barcelona, Spain
- Event website:
- https://chi2026.acm.org/
- Event start date:
- 2026-04-13
- Event end date:
- 2026-04-17
- DOI:
- ISBN:
- 9798400722783
- Language:
-
English
- Keywords:
- Pubs id:
-
2396282
- Local pid:
-
pubs:2396282
- Deposit date:
-
2026-03-28
- ARK identifier:
Terms of use
- Copyright holder:
- Zhang et al.
- Copyright date:
- 2026
- Rights statement:
- Copyright © 2026 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution 4.0 International License.
- Licence:
- CC Attribution (CC BY)
If you are the owner of this record, you can report an update to it here: Report update to this record