The shock of seeing your body used in deepfake porn
Non-consensual intimate deepfakes remain a live harm category for Australian online safety regulators and eSafety rulemaking.
Key points
- Adult performers describe widespread non-consensual deepfake content, financial harm, and reputation damage from AI-generated likenesses.
- Australia's Online Safety Act and proposed mandatory standards for platforms are directly relevant to this harm category.
- Item is a human-interest feature focused on US performers - limited direct APS policy signal beyond existing awareness.
Implications for Australian agencies
- Monitor eSafety Commission and OAIC policy teams may want to monitor how US litigation on AI training data consent and deepfake liability develops, as outcomes could inform Australian regulatory approaches.
Implications are AI-generated. Starting points, not advice — see methodology for how they're framed.
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Weekly digest, 11 May 2026
"The shock of seeing your body used in deepfake porn"
Source: MIT Technology Review – AI
Published: 14 May 2026
URL: https://www.technologyreview.com/2026/05/14/1137161/ai-porn-nonconsensual-deepfakes-takedown-piracy-copyright/
An MIT Technology Review feature profiles adult content creators affected by AI-generated deepfake pornography, covering non-consensual use of likenesses, financial losses from impersonation scams, and reputational harm. Performers describe contracts signed before AI that now enable retroactive use of their content for model training, and platform takedown processes that fail to keep pace with AI-generated content spread. The piece contextualises AI deepfakes within broader debates about fair use, piracy, and consent - issues that intersect with ongoing litigation in the US and emerging regulatory responses in multiple jurisdictions.
Implications for Australian agencies:
- [Monitor] eSafety Commission and OAIC policy teams may want to monitor how US litigation on AI training data consent and deepfake liability develops, as outcomes could inform Australian regulatory approaches.
Retrieved from SIMS, 18 July 2026.