Making Generative Artificial Intelligence a Public Problem. Seeing Publics and Sociotechnical Problem-Making in Three Scenes of AI Failure

Abstract

Although Generative Artificial Intelligence (GenAI) has rapidly gained popular attention as something to worry about or be excited by, it is less clear if or how it is a public problem, and what ideals of publicness it illustrates, challenges, or invents. By developing the idea that GenAI is simultaneously an object and agent of public life, by describing how its failures are constructed and animated in three sociotechnical scenes, and by examining those scenes of failure for evidence of publicness, I trace how GenAI might be made into a public problem, and a problem for different ideals of publicness. Tracing how GenAI failures are narrated by charismatic figures, indexed by activists and policymakers, and avoided and repaired by journalists, I suggest that GenAI’s public significance stems from its dual identity as both an ontological and epistemological concern and show how that duality plays out in failures that illustrate, combine, and extend ideals of the public.