Tribal Truths: Reconsidering Public Deliberation in the Wake of Generative AI Imaging.

In contemporary western public spheres already permeated by disinformation, an urgent topic of study is how the rapid proliferation of generative AI imaging technologies is affecting public deliberation. The now widespread accessibility of tools capable of producing fictional yet photorealistic images with minimal efforts appears to intensify the circulation of misleading or fabricated visual content. To better understand how generative AI imaging reshapes - and potentially destabilizes - public discourse, this study integrates insights from debates on deliberative democracy, digitalization, neotribalization, and post-truth. More specifically, we examine the implications of generative AI imaging for public deliberation by bringing together two distinct yet related theoretical perspectives: Hans Boutellier’s notion of neotribalism and Byung-Chul Han’s theory of infocracy. Although emerging from different disciplinary backgrounds and emphasizing different dimensions of public sphere erosion, both highlight the central connection between the rise of new communication technologies and the gradual replacement of rational, shared public truth by affect-driven ‘tribal truths’. By combining Boutellier’s and Han’s approaches, we argue that the mass adoption of generative AI imaging significantly accelerates this slide from public truth to tribal truths. To substantiate this argument, we analyze both the communicative properties of generative AI images (infocracy) and the social dynamics of the tribe-like user communities that develop around these tools (neotribalization). We conclude by outlining the challenging times that lie ahead for exponents and patrons of deliberative democracy.