How does AI-generated political content affect voter trust in official election information?

A competing interpretation is that the main danger is not simply exposure to fake content but the broader scaling and personalization of persuasion. Fluent AI-generated messages can influence political judgments without impersonating anyone or making a plainly false claim, while partisan audiences may interpret identical AI use in opposite ways. Blanket warnings or authenticity-focused rules may therefore miss subtler routes by which trust is reshaped.

• One analysis argues that regulation focused on fabricated authenticity captures only part of AI’s electoral impact because persuasive, psychologically calibrated text can influence judgment without false impersonation.
• AI use alone produced limited effects in one experiment; evaluations shifted sharply when voters learned whether their own or the opposing party used AI.
• Partisan identity can make identical AI-assisted messages appear more fair and authentic when attributed to one’s own party and less so when attributed to the opponent.
• Warning labels may have unintended effects: research on perceived label consequences examines whether warnings protect audiences or alter receptivity in undesirable ways.
• The observed trust decline may reflect perceived exposure and generalized media distrust rather than a direct effect of every AI-generated message; tolerance for synthetic material followed different predictors.

Featured sourceSynthetic Campaign Communication and Election Confidence in the Age of Artificial Intelligence | Public Opinion and Voting Behavior | APSA Preprints | Cambridge Open Engagepreprints.apsanet.org4 sourcesView sources