AI Governance as scale work: synthetic journalism across scalar collisions

2025/12/05 by Mike Ananny · 1 voice
Social Sciences · #Ethics and Social Impacts of AI #Computational and Text Analysis Methods #Media Studies and Communication

paper · doi:10.1080/1369118x.2025.2597508

openalex created_date 2025/12/05 · openalex publication_date 2025/12/05 · openalex updated_date 2026/06/15

Abstract

Governing Artificial Intelligence (AI) is difficult, in part, because AI systems never stand still in any one place. They are usually made by private companies, hidden within proprietary infrastructures, spanning jurisdictions, behaving in ways that are difficult to predict, and talked about in messy discourses of hype and panic. I suggest here that all this dynamism and uncertainty could be tackled by understanding AI and its governance as multi-scalar phenomena. Drawing on DiCaglio’s idea of a ‘scalar view,’ defining AI as a scalar media technology, and tracing journalism’s encounters with Generative AI as scalar collisions – across practices, organizations, data, audiences, and engineering – I argue that AI governance is ‘scale work’, and that multi-scalar governance offers new ways to understand Generative AI and its stakes.

Citations

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Discussions

• #OutNow in #iCS In this article, Mike Ananny argues that governing generative AI is “scale work”, using synthetic journalism to show how AI collides with news practices, infrastructures and audiences [bsky, 0 points, 0 comments]