Elon Musk's xAI is asking a court to force four anonymous plaintiffs suing over non-consensual deepfake nudes to reveal their identities, potentially forcing them to choose between going public or dropping their case.
The move marks an escalation in legal disputes surrounding xAI's Grok AI tool, which was used to generate explicit fake images of real people earlier this year.
Four individuals filed suit under pseudonyms to protect themselves from identification risks. xAI's request to strip their anonymity puts them in a precarious position: disclose personal details or abandon legal action.
The Grok Deepfake Wave
In January, non-consensual sexualized images created with Grok flooded X, the social media platform owned by Musk. Labour MP Jess Asato became the public face of the issue, launching a test case against xAI after seeing herself depicted in fake bikini images without consent.
Asato's lawsuit prompted additional claimants to step forward. Her lawyer reported that multiple people contacted them after the MP's case received media coverage, signaling broader harm from the tool.
Parallel Development: Grok Imagine 1.5
While defending deepfake-related lawsuits, xAI released an updated version of Grok Imagine this month—version 1.5—which adds image-to-video generation at 720p resolution. The tool can convert still images into cinematic videos based on text prompts and stitch multiple clips into longer scenes.
The timing underscores tensions between xAI's product expansion and growing legal accountability for misuse of its generative AI capabilities.
What's at Stake
For the anonymous plaintiffs, revealing their identities could expose them to harassment, recognition, or further misuse. For xAI, the anonymity request appears designed to complicate the case by removing protections that would allow accusers to proceed safely.
The court's decision will likely influence how similar AI-related harassment cases proceed and whether victims can pursue legal remedies without public exposure.
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xAI released Grok 4.7, claiming enhanced self-verification and extended context handling. The model is priced at $2 per million input tokens and $6 per million output tokens.