New peer-reviewed research shows political deepfakes can shift how people perceive a candidate — even when viewers are explicitly told the video is fake and correctly identify it as fake. That finding cuts straight at the policy tool most states are currently betting on.

AI-generated (NotebookLM) audio overview. Source: HexLocal in-house research — The 2026 Deepfake Election Problem: When Voters Know It's Fake and It Still Works (Dr. Priya Nair). Primary external sources include Clark and Lewandowsky (Communications Psychology, 2026), Gallegos et al. (PNAS Nexus, 2026), Resemble AI's Q3 2025 Deepfake Report, and NCSL state legislation tracking.

- The "continued influence" effect: warned viewers who correctly identified a deepfake as fake still showed significantly elevated guilt ratings compared to a no-video control

- The Clark and Lewandowsky finding is real and peer-reviewed but carries important limits — single lab, ~673 participants, fictional stimuli, measuring guilt perception rather than vote choice

- A separate text-based study (Gallegos et al.) reaches a directionally consistent result, making the case converging evidence rather than a single outlier

- The 2026 political landscape is a bipartisan arms race, not a one-sided story — the Cornyn vs. Paxton Senate primary traded AI attack ads for weeks

- Verified scale: 2,031 deepfake incidents in Q3 2025, up 317% quarter-over-quarter, per Resemble AI's primary report

- The regulatory gap: 28 states require disclosure only, and there is no comprehensive federal rule — precisely the fix the research suggests may not be enough