Labeling AI-generated media online
Chloe Wittenberg; Ziv Epstein; Gabrielle Péloquin-Skulski; Adam J. Berinsky; David G. Rand · 2025 · PNAS Nexus
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract
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 c
Abstract by Chloe Wittenberg; Ziv Epstein; Gabrielle Péloquin-Skulski; Adam J. Berinsky; David G. Rand, PNAS Nexus (2025) — licensed CC BY 4.0.
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Metadata source: OpenAlex · DOI 10.1093/pnasnexus/pgaf170