This article explores how advances in artificial intelligence, especially generative AI and deepfake technologies, are changing the landscape of truth, accountability, and political communication. It builds on the concept of the “liar’s dividend” — a term coined by scholars Robert Chesney and Danielle Citron — which describes how the existence and rising plausibility of synthetic media make it easier for those accused of wrongdoing to simply deny authenticity by claiming something is fake.
One central point is that AI doesn’t just enable false claims (i.e., fake videos or audio), it also empowers real actors to shift responsibility: when evidence of their actions appears, they may deflect by saying “that was generated by AI” or “it’s a deep-fake,” even if the evidence is genuine. This erodes traditional accountability mechanisms because the burden shifts to proving authenticity rather than disproving fabrication.
The article also argues that political figures like Donald Trump may use this dynamic strategically. For instance, by invoking AI as the cause of disinformation or confusing media environments, they can cultivate doubt around damaging evidence and rally supporters under the banner of “unfair targeting.” The broader impact is a democratic risk: when public trust in media, evidence and institutions declines, it becomes harder to hold powerful actors to account.
Finally, the piece suggests potential responses and safeguards: improving media provenance (how to verify whether content is authentic), educating the public about the liar’s dividend and synthetic media risks, and creating norms or legal frameworks that discourage misuse of AI for denial and deflection. Without such measures, the combination of AI-enabled fabrication and blame-shifting may undermine not only truth in media, but the foundation of transparency in governance.
