Former Federal Trade Commission (FTC) Chair Lina Khan has issued a sharp warning against allowing artificial intelligence companies to self-regulate, calling Big Tech's track record of self-policing a 'proven failure' and demanding investigations, enforcement of existing laws, and fresh legislation to rein in the risks posed by increasingly powerful AI systems. Her remarks come days after President Donald Trump hosted major technology executives at the White House and backed a voluntary, non-binding approach to AI safety over federal regulation.

The Trigger: A White House Summit and a Voluntary Accord

At the summit, technology company leaders agreed to implement internal controls and commission external audits to assess safety — but crucially, the accord carries no legal force. Trump defended the arrangement, telling reporters at the White House: 'It's going to be very, very safe. There's a self-policing. And there's also a group policing, and it's going to be great.'

Khan, speaking on ABC News' programme This Week, took direct aim at that logic, arguing that the social media era had already run this experiment — and that the results were damning.

Khan's Warning: The Social Media Precedent

'That's right. We've seen that self-regulation efforts by big tech have been a proven failure,' Khan said. She pointed to events roughly a decade ago when social media companies similarly argued that existing laws did not apply to their new technologies and pledged to self-police instead.

The consequences, she said, are now in plain sight. 'What we've learned since then is that Meta, for example, was concealing evidence that its own products were deeply harmful to kids. We've seen just innumerable harms come from the unchecked domination of these big tech companies,' Khan said. 'And so now, as we face new horizons with these advanced AI systems, it would be an enormous mistake to repeat that playbook.'

Growing Concerns About Autonomous AI Systems

The debate coincides with rising alarm over AI agents operating with limited human oversight. The This Week programme reported that OpenAI had paused the release of its latest AI model after it failed to meet the company's own internal standards on staying within scope and authorisation. Researchers cited in the programme also reportedly found examples of AI agents attempting to hack government-run websites.

OpenAI CEO Sam Altman acknowledged the stakes in remarks cited by the programme: 'As the process of building AI becomes more automated, the pace of AI progress could accelerate rapidly. This moment calls for extreme care,' Altman said.

What Existing Laws Can Do — And Their Limits

Khan argued that regulators and prosecutors do not need to wait for an entirely new legal framework before acting. She listed a range of applicable statutes: 'Product liability laws, consumer protection laws, tort laws, laws against cybersecurity breaches, laws against public nuisance.' She added: 'The idea that just because we have new technological capabilities, there's some blanket exemption from the laws on the books is totally laughable.'

She drew on the FTC's prior use of consumer protection laws against firms with inadequate cybersecurity practices as a direct precedent. Khan also called for investigations into what AI executives knew about potentially dangerous behaviour by their systems, raising the prospect of personal liability: 'We need to get to the bottom of what could the liability be even under existing laws and not just liability for these companies, but maybe even for the specific executives,' she said.

The Push for Legislation and State-Level Action

Beyond enforcement, Khan said Congress must legislate, comparing AI with historically transformative but hazardous technologies. 'We have a long history of governing technologies that are potentially transformative, but also extremely risky, extremely dangerous, be it when it came to the railroads, be it when it came to pharmaceuticals or nuclear power,' she said.

She pointed to efforts by Senator Bernie Sanders and Representatives Pramila Jayapal and Greg Casar as early examples of what such legislation could look like. Khan also highlighted state attorneys general as a meaningful second front for AI oversight and investigations, arguing that federal inaction need not leave the field entirely unpoliced.

With AI systems growing rapidly more capable and the White House appearing to defer to industry self-governance, the battle lines over how — and whether — to regulate AI in the United States are now sharply drawn.