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As democracies prepare for elections increasingly shaped by artificial intelligence, the greatest challenge may not be detecting deepfakes, but preparing voters to recognize manipulation before it spreads. According to the article, Ukraine’s experience offers an alternative model that emphasizes resilience rather than reactive fact-checking.
The discussion follows several high-profile uses of AI-generated political content during U.S. election campaigns in 2026. Synthetic campaign advertisements have become increasingly sophisticated, while legal and regulatory responses remain fragmented. Similar cases have appeared in Europe, including Ireland and Moldova, highlighting that AI-generated political manipulation has become a global phenomenon.
The article argues that technological solutions alone cannot keep pace with rapidly improving generative AI. Watermarking, AI detectors, and post-publication fact-checking often arrive only after manipulated content has already reached millions of viewers. At the same time, widespread awareness of deepfakes creates what researchers describe as the “liar’s dividend,” allowing public figures to dismiss authentic evidence as fabricated.
Regulatory approaches have also proven contentious. The European Union is implementing transparency requirements under its AI Act, while broader initiatives aimed at countering foreign information manipulation have sparked debates over free speech and government involvement in moderating online content. The result is an ongoing tension between protecting democratic discourse and avoiding censorship.
Against this backdrop, the article highlights Ukraine’s approach as an alternative model. Following years of sustained information warfare, Ukrainian institutions shifted toward preventive communication—warning the public about expected disinformation campaigns before they appear rather than focusing solely on debunking them afterward. The failure of the 2022 deepfake video falsely depicting President Volodymyr Zelenskyy calling for surrender is presented as an example of how advance warnings reduced the effectiveness of the operation.
The article links this strategy to the concept of “prebunking” or “inoculation theory,” whereby exposing audiences to common manipulation techniques in advance helps build resistance to future disinformation. Rather than attempting to verify every individual piece of content, the objective is to strengthen public resilience so that voters can recognize manipulation independently.
At the same time, the author acknowledges the limitations of Ukraine’s wartime information policy. While distributed networks of government agencies, media organizations, and civil society have improved resilience, more centralized approaches—such as the wartime national television telethon—have drawn criticism over media pluralism and declining public trust. The article argues that these experiences offer lessons not only in what strengthens democratic resilience, but also in where emergency measures become counterproductive over time.
The central conclusion is that democracies should shift their focus from protecting every individual message to strengthening the audience itself. Media literacy, rapid official communication, institutional trust, and preventive public awareness are presented as more scalable long-term defenses against AI-enabled information manipulation than an endless race to detect increasingly sophisticated deepfakes.
Read the full article by Ihor Petrenko, Founder of the United Ukraine Think Tank and Doctor of Political Science.
