What the Study Found
- Identical fake nudes were removed within 25 hours when reported as copyright, but stayed up for 3+ weeks when reported as abuse.
- Copyright (DMCA) claims carry legal force; X’s own non-consensual nudity policy had no enforcement and got ignored.Accounts hit with copyright claims were suspended and notified; accounts reported for abuse faced no consequences at all.
- The DMCA route only works if you own the photo’s copyright—excluding most deepfake victims, who never took the image.
The 50 images went up on X over two days, scheduled at random hours between noon and midnight, tagged with the crudest hashtags the platform’s adult content trades in. Every one was a lie. The women in them didn’t exist, conjured instead by a generative model and checked against facial-recognition tools to make sure no real face had leaked through. Then the researchers waited, and reported, and watched the clock.
What they were testing wasn’t the images themselves but the machinery behind them: the two front doors X gives you for getting intimate content taken down. One is marked privacy. The other is marked copyright. They lead to very different places.
Half the images, 25 of them, were reported through X’s own non-consensual nudity policy, built expressly for this kind of abuse. The other half were reported as copyright violations under the Digital Millennium Copyright Act, the same federal law that pulls down bootleg films and leaked albums. Identical pictures, identical removal requests, near-identical wording. The only real difference was which legal scaffolding sat behind the complaint.
The copyright reports worked. All 25 of those images were gone within 25 hours, the fastest in roughly 13, with a mean around 20. The privacy reports didn’t work at all. Three weeks on, every one of the 25 images flagged as non-consensual nudity was still sitting there.
A law gets answered. A policy gets ignored.
“The contrast is stark,” says Qiwei Li, the University of Michigan doctoral candidate who led the audit. “Reports filed through a law got fast action, and reports through the internal channel got nothing. X responds to legal pressure, not to their own stated policies. Legal pressure works; platform goodwill doesn’t.”
There was a second tell, in what happened to the accounts doing the posting. The five accounts caught by copyright claims were all temporarily suspended and sent an email spelling out the complaint against them, the full DMCA notice included. The five accounts reported for non-consensual nudity? Nothing. No suspension, no warning, no acknowledgement that anything had been reported at all. One framework comes with teeth and a paper trail; the other, on this evidence, comes with a shrug.
The design itself was a careful piece of ethical tightrope-walking. Instead of touching a single real survivor’s image, the team manufactured the whole scenario from synthetic faces. “The idea came from watching AI-generated nude imagery enter mainstream public consciousness and recognizing it could let us study a real, urgent problem without risking survivor content,” she says. That choice, posting fabricated abuse to study how abuse is handled, is the sort of thing an ethics board might balk at; the work was classed as not involving human subjects, which tells you something about how slowly the rules have kept pace.
The law arriving now, and the hole it leaves
The timing here isn’t incidental. The audit lands as the TAKE IT DOWN Act comes into force, the new federal law (the clunky acronym unpacks to Tools to Address Known Exploitation by Immobilizing Technological Deepfakes on Websites and Networks) that from 19 May requires platforms to pull non-consensual intimate imagery, deepfakes included, within 48 hours of a valid report. It’s enforced by the Federal Trade Commission, and the penalty for ignoring it runs to more than $53,000 a violation.
In other words, it does to privacy reporting roughly what copyright law already did: it puts a law behind the request. Li’s data suggests that is exactly the lever that moves platforms.
But she is wary of reading the result as simple good news, and here the argument gets more interesting. “Our audit suggests that platforms will remove when there’s legal pressure behind a report. That’s the part of TAKE IT DOWN that could work,” she says. “The more challenging question is what else might come down along with it. A law that mandates fast removals on the internet risks creating collateral damage.” A 48-hour clock and a five-figure fine are a strong incentive to take things down fast; they may also be an incentive to take things down first and ask questions later.
And there’s a deeper gap the law barely touches, which is who does all the labour. The mandate tells platforms to act on valid reports, but somebody still has to find the content, prove it’s them, file the paperwork, and then keep watching. “The law still leaves survivors doing the work, searching for their own abusive content, documenting it, submitting reports, monitoring after submission and doing it all again when the content reappears on a new website,” Li says. The copyright route, the one that actually functions, has its own cruel catch built in: you can only file a DMCA claim if you own the copyright, which generally means you have to have taken the picture yourself. The abuse most easily removed, then, is the abuse the victim happened to photograph.
Roughly one in eight American adults, by the figures the researchers cite, have had intimate images shared without consent or been threatened with it, and around nine in ten of those harmed are women. Against numbers like that, a single audit of a single platform is a small thing, and Li knows it. What it offers is a clean before-and-after of a system that, until a law showed up, simply wasn’t listening.
“TAKE IT DOWN might better address the platform-side failure our audit documented,” she says. “But it does not fix the survivor-side burden, and that gap is where policy attention needs to go next.” The front door marked privacy may finally be opening. Whether anyone is waiting on the other side to do the searching, the filing and the endless watching is still very much an open question.
- Study type: Qualitative interview study; trauma-informed, semi-structured interviews analyzed via hybrid deductive–inductive thematic analysis
- Intervention / focus: Victim-survivors’ lived experiences reporting non-consensual intimate imagery (NCII) to online platforms
- Analytic framework: Institutional Betrayal Questionnaire-2 (IBQ-2) as deductive coding scaffold, extended for the first time to platforms as institutions; researcher-coded, not participant-administered
- Comparator: None (no control condition); cross-case comparison across platforms and participants
- Sample size: 13 U.S.-based adult victim-survivors, recruited across gender, sexual orientation, race, and age; 5 were minors at time of incident
- Duration: Single interview per participant, averaging 106 minutes (range ~90–240 min), conducted April–August 2025
- Funding / conflicts of interest: National Science Foundation (Grant 2311102); no conflicts of interest disclosed
- Study type / peer-review: Peer-reviewed; published in Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI ’26; 24% overall acceptance rate)
- Main limitation: Small, U.S.-only sample limited to those who at least partially engaged with a reporting process — excluding survivors deterred before reporting — so findings can’t capture the earliest points of disengagement or generalize cross-nationally
Reference
Qiwei, L., Kennon, K., Bedera, N., Eaton, A. A., Gilbert, E., & Schoenebeck, S. (2026). Platforms as Crime Scene, Judge, and Jury: How Victim-Survivors of Non-Consensual Intimate Imagery Report Abuse Online. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1–19). ACM. CHI 2026: CHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/3772318.3791115
Frequently Asked Questions
Why did reporting a fake nude as copyright work when reporting it as abuse didn’t?
Because copyright complaints are backed by federal law and privacy policies, until very recently, were not. The DMCA legally obliges platforms to remove infringing content promptly, with real consequences for ignoring it, while a platform’s internal non-consensual nudity policy is just a self-imposed rule with no outside enforcement. In the Michigan audit, that difference showed up as removal within a day versus no removal at all over three weeks.
What is the TAKE IT DOWN Act and what does it actually require?
It is a US federal law, in force from 19 May 2026, that requires online platforms to remove non-consensual intimate images, including AI-generated deepfakes, within 48 hours of a valid report. The Federal Trade Commission enforces it, and non-compliance can bring civil penalties of $53,088 per violation. In effect, it gives privacy reports the kind of legal weight that copyright reports have had for years.
Is it true that you can only get a deepfake removed if you took the photo yourself?
Under the copyright route, largely yes, which is one of its deepest flaws. A DMCA claim generally requires you to own the copyright, and for a photo that usually means being the person who pressed the shutter. That leaves anyone whose abusive image was created or captured by someone else, which is most deepfake cases, without access to the one mechanism that reliably worked before the new law.
How did researchers study this without using real victims’ images?
They generated entirely synthetic nude images of people who do not exist, then checked each one against facial-recognition and reverse-image tools to confirm it did not resemble any real individual. Posing as the fictional depicted women, they filed the takedown reports themselves. The approach let them measure platform behaviour on realistic material while keeping any actual survivor’s content out of the experiment.
What problem does the new law still leave unsolved?
The burden on survivors. Even with faster removals mandated, victims are still the ones who have to discover the content, document it, file each report, and monitor for it reappearing elsewhere, often over and over. The audit’s lead author argues this survivor-side labour is where policy attention most needs to go next.
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