Labeling AI-generated media online.

ABSTRACT: Recent advancements in generative AI have raised widespread concern about the use of this technology to spread audio and visual misinformation. In response, there has been a major push among policymakers and technology companies to label AI-generated media appearing online. It remains unclear, however, what types of labels are most effective for this purpose. Here, we evaluate two (potentially complementary) strategies for labeling AI-generated content online: (i) a process-based approach, aimed at clarifying how content was made and (ii) a harm-based approach, aimed at highlighting content's potential to mislead. Using two preregistered survey experiments focused on misleading, AI-generated images (total n = 7,579 Americans), we assess the consequences of these

SUBMITTER: Wittenberg C 

PROVIDER: S-EPMC12166545 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature