Generative Propaganda
Authors: Madeleine I. G. Daepp, Alejandro Cuevas, Robert Osazuwa Ness, Vickie Yu-Ping Wang, Bharat Kumar Nayak, Dibyendu Mishra, Ti-Chung Cheng, Shaily Desai, Joyojeet Pal
Published: 2025-09-23 15:27:00+00:00
AI Summary
This research paper investigates the real-world use of generative AI in shaping public opinion, focusing on interviews with creators and defenders of information in Taiwan and India. The study finds that the emphasis on deceptive deepfakes overshadows the broader use of AI for persuasion and distortion, revealing efficiency gains as a primary concern.
Abstract
Generative propaganda is the use of generative artificial intelligence (AI) to shape public opinion. To characterize its use in real-world settings, we conducted interviews with defenders (e.g., factcheckers, journalists, officials) in Taiwan and creators (e.g., influencers, political consultants, advertisers) as well as defenders in India, centering two places characterized by high levels of online propaganda. The term deepfakes, we find, exerts outsized discursive power in shaping defenders' expectations of misuse and, in turn, the interventions that are prioritized. To better characterize the space of generative propaganda, we develop a taxonomy that distinguishes between obvious versus hidden and promotional versus derogatory use. Deception was neither the main driver nor the main impact vector of AI's use; instead, Indian creators sought to persuade rather than to deceive, often making AI's use obvious in order to reduce legal and reputational risks, while Taiwan's defenders saw deception as a subset of broader efforts to distort the prevalence of strategic narratives online. AI was useful and used, however, in producing efficiency gains in communicating across languages and modes, and in evading human and algorithmic detection. Security researchers should reconsider threat models to clearly differentiate deepfakes from promotional and obvious uses, to complement and bolster the social factors that constrain misuse by internal actors, and to counter efficiency gains globally.