(Synthetic) stump speech: crafting generative AI disclosure regulations for political advertisements

Objective: to analyze the benefits and drawbacks of legal regulation of relations in the sphere of the US elections in the context of using artificial intelligence.

Methods: the article employs the dialectical method of cognition, as well as general scientific (analysis, synthesis, induction, deduction) and specific scientific (formal-legal) research methods.

Results: The article assesses the current regulatory landscape for synthetic media in political advertising to analyze the benefits and drawbacks of greater regulation. Based on current and emerging regulatory approaches, the author examines how governments and private actors have limited synthetic media usage within existing First Amendment jurisprudence. Although initial prohibitions served a necessary role, the author proposes that transparency enforcement is the best approach and should be built upon by creating a repository that contains information on an advertisement's synthetic content.

Scientific novelty: Synthetic media, or content generated using artificial intelligence, has begun to infect political advertising. Federal legislation has spent most of its time stalled in committees, but states and online platforms have rapidly implemented regulations. Although synthetic media may pose harms through voter manipulation and democratic distortion, it also can lower campaign costs and more vividly illustrate conceptions of a political choice's consequences. Some governments and commentators have sought to prohibit the most harmful forms, while others have focused more on transparent approaches to regulation. In the face of yet another contentious election cycle, the question of how to ensure choices are made based on belief and not manipulation looms large.

Practical significance: the main provisions and conclusions of the article can be used in scientific, pedagogical and law enforcement activities when considering the issues related to regulation of the US elections.

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