In Episode 2 of the Guardians of Data podcast Ibrahim Hasan spoke with Lynn Wyeth, an AI and data protection expert, about the Grok controversy and what it means for AI governance and equality. The following is an abridged transcript of the podcast:
What is Grok and what triggered this controversy?
Grok is the AI companion built into X, Elon Musk’s social media platform. It’s been around since late 2023 as a competitor to ChatGPT; a chatbot designed to give
real-time, unfiltered responses with, in Musk’s words, a “rebellious” tone.
The controversy began in May 2025 when users prompted Grok to alter photos of real women into sexualised images. By late 2025 it had escalated dramatically; users simply replied to public photos with requests like “put her in a bikini,” and Grok posted the generated images directly to X, publicly and instantly. Estimates suggest it produced around 4.4 million images in nine days, with 41 to 65 per cent sexualised. Worryingly, some of those images involved children.
What made Grok’s situation different from other AI tools?
The crucial difference is that Grok published the images as the answer, live on the internet, with no human review and no filter. With ChatGPT and similar tools, the user has to export and manually share what’s been generated. Grok skipped that step entirely. There was no sanity check; no moment where a person could pause and think, “maybe not.”
It also reflects Musk’s “free speech” philosophy. What’s acceptable to him clearly isn’t what’s acceptable to many others, and the platform’s algorithm appears to amplify certain content regardless of whether it’s truly neutral.
Is this a technology failure, a governance failure, or a regulatory gap?
All three. Technology moved faster than the safeguards. Governance failed because proper Data Protection Impact Assessments weren’t done or weren’t done honestly. And the legislation simply hasn’t kept pace. GDPR tried to modernise privacy law, but along comes AI updating on a daily basis. How can legislation possibly keep up? Our regulators, particularly in the UK, have also been disappointingly toothless; plenty of investigations and bland statements, very little meaningful action.
What are the GDPR issues the ICO will be examining?
The key question is whether AI-generated imagery of a real, identifiable person constitutes personal data. Almost certainly yes. After that, it’s about lawful basis; what legal justification does xAI have for generating and publishing these images? Consent? Definitely not. Legitimate interests? Possibly claimed, but has the balancing test actually been done? I doubt it.
More interesting for me is GDPR’s principle one. The requirement that processing be not just lawful, but fair and transparent. Even if xAI constructed a technical legal argument, is this what people expect when they post a photo? Is it fair? That’s where ethics enters data protection, and the ICO will have some very difficult arguments to navigate.
What about the legal gaps around deepfakes specifically?
Currently in the UK, sharing a non-consensual intimate deepfake is illegal but creating one isn’t. The government is working to close that through the Crime and Policing Bill and the Data Use and Access Act, making the creation or requesting of such images an offence too.
But definitions will matter enormously. What counts as “intimate”? What’s the threshold between causing upset and causing real harm? There’s a phrase I saw recently, “lawful but awful content”, which captures the problem perfectly.
Sometimes something can be technically legal and still completely unacceptable.
We need clear definitions, so people know their rights, and so the police aren’t swamped with every complaint about every post.
(More on the legal issues of filming and uploading images in episode 6 with Naomi Mathews.)
Is this fundamentally a women’s equality issue?
It’s hard to see it as anything else. The overwhelming majority of victims were women and girls. The images were sexualised, non-consensual, and designed to humiliate.
And when Musk himself was subjected to similar images, he laughed. That tells you everything about the power imbalance at the heart of this.
Lynn Wyeth is clear that this isn’t new: “It’s just a continuation of decades of the same.” The tabloid page-three culture of the seventies and eighties, the racism and misogyny peddled to sell newspapers; the medium has changed but the dynamic hasn’t. Now it’s clickbait and likes instead of print runs, but the underlying impulse to commodify and demean women remains. And what’s particularly troubling about Grok is that it industrialised that harm; turning what once required effort and skill into something anyone could do with a single reply.
The Equality Act 2010 protects women from harassment and discrimination, and human rights law guarantees dignity and private life. But as the government’s own language around the Online Safety Act and the Violence Against Women and Girls strategy makes clear, those protections have consistently failed to keep pace online. When a platform can generate 4.4 million sexualised images in nine days, a significant proportion of them of women who never consented, and face no immediate legal consequence, the gap between the law on paper and the protection it delivers in practice is stark.
This is why the framing matters. Grok isn’t just a data protection problem or a tech governance problem. It’s a discrimination problem. Any serious regulatory response needs to treat it as such.
Should organisations be reconsidering their presence on X?
Every organisation has to make that call for itself. Some have left e.g. Belfast City Council, and Sport England. There are still good people on X, and for many organisations it remains a vital communications tool. But you do have to ask: when does staying cross your ethical red line? When does it compromise your values? That’s a board-level conversation, and it needs to happen.
What are the practical lessons for organisations deploying AI?
Do your homework before you roll it out. Think about where it could go wrong. And do a proper DPIA; not a tick-box exercise, but an honest assessment of both the legal and ethical risks. The classic failure pattern is the tech team deploying something and then asking information governance to sign it off. By then it’s too late. Governance has to be embedded at the start.
AI oversight also can’t sit in one team. It needs technology, legal, data protection, and board-level leadership all working together. How many boards genuinely understand what AI is and how it works? Not enough. Someone needs to be educating them, because if the organisation is going to make decisions about AI, leadership needs to understand what they’re deciding.
More on making AI ethical in Episode 7 with Tahir Latif.
Has AI lost its way?
No. The genie is out of the bottle. You can’t put it back, and regulation alone won’t change that. AI will save lives, save time, and deliver real value. It will also cause harm if it’s deployed carelessly and regulated too slowly.
The responsibility doesn’t start when harm occurs. It starts at design, at deployment, and at the moment decisions are made about what a system should and shouldn’t be allowed to do.
The question isn’t whether to use AI. It’s whether we’re serious about using it well.
Listen to the full Episode 2 with Lynn.
Previous episodes of the Guardians of Data podcast have featured Jen Persson, a privacy campaigner, explaining the privacy implications of the Government’s new plans for children’s data and Olu Odeniyi analysing recent cyber breaches and discussing the lessons learnt.
