Why silicon valley can’t slow down AI on its own

Published on October 27, 2026 7:05 PM GMT By Luisa Rodriguez, Elizabeth Cox,  and Lou Moran   Watch on Youtube  |  Listen on Spotify  |  Read transcript Two-thirds of Americans think AI is moving too fast. So do the people building it. So why the hell isn’t anyone slowing down? We can’t tell when models are too dangerous. We mostly don’t know how they work. We don’t know how to make them do what we want. And our two main safety checks — testing behaviour and monitoring their ‘thoughts’ — are breaking down. Yet we’re racing to build more powerful AI anyway, faster every year. And it’s only going to accelerate as AI itself gets better and better at building the next generation of models. Earlier this year, OpenAI found its new model, Astra, was alarmingly good at hacking, and did something companies almost never do: paused its biggest training project. But it released Astra anyway, even though tests couldn’t prove if it was safe. That’s the problem with leaving it up to the companies. We can’t trust them to act in our best interest because the competitive pressures for them to race ahead are too strong. So what’s the solution? Luisa Rodriguez evaluates the likely candidates: Safety checkpoints when new models can hack, work unsupervised, or build bioweapons Restricting computing power as a speed limit on AI development Preventing AI from being used to create more powerful AI Pausing development altogether None of these will be easy. But with AI hacking increasingly widespread, we’re already seeing the consequences of doing nothing — and this is just the beginning. Slowing down could give us time to understand why models are so hard to control; secure hospitals, banks, and power grids against hacks; and help society adapt. Everyone should be a part of this conversation, not just CEOs and policymakers. The rules we end up with will be shaped by what voters ask for, and could determine the future we all live in. This episode was recorded on October 21, 2026. Our production team includes: Video editors: Josh Alward, Dominic Armstrong, Jasper Luithlen, Milo McGuire, Luke Monsour, Simon Monsour, Ollie Bignell, and Andrés Escobar Producers: Elizabeth Cox and Nick Stockton Coordination and support: Katy Moore, Lou Moran, Cody Fenwick, and Joseph Isaac Camera operator: Dominic Armstrong Transcript Everyone says AI is moving too fast [00:00:00] Luisa Rodriguez: I’ve been getting really freaked out by how quickly things are moving in AI. And it turns out I’m not alone: two thirds of Americans, across the political spectrum, think AI is moving too fast. And it’s not just the public. The people who are building AI, the people who are literally setting the pace, agree. And it’s about to get even faster. AI is now helping build the next generation of AI. One of Anthropic’s cofounders thinks it could be improving itself with no humans involved as soon as next year — so, 2027. Politicians are getting freaked out too, and that includes people on both sides of the aisle, which I find especially wild. The public wants to slow down. The people building AI want to slow down. Lots of politicians want to slow down. So why the hell aren’t we slowing down? You might feel like you personally don’t need to understand this issue. But I seriously believe this is a conversation everyone should be a part of, not just CEOs and a handful of policymakers. The rules we end up with will be shaped by what voters understand and ask for. So it matters that people like you and me actually understand the options. Let’s dig in. What exactly would we be slowing down? [00:01:28] First things first. When people hear “slow down AI,” a lot of them picture someone pulling the plug on ChatGPT. We could actually stop them building anything more powerful tomorrow, and you could still use ChatGPT or Claude or Gemini exactly like you do today. Businesses could keep finding new uses for them. Researchers could keep studying them. And honestly, we’re nowhere near making the most of the AI that we already have. Today’s models alone could still transform science, medicine, and the economy. We’ve barely scratched the surface. So the real question is how to slow down the race to build AI that is even more powerful than what we have now. Let the companies race ahead [00:02:13] Let’s start with what we’re doing now: basically letting the companies race ahead, and trusting them to hit the brakes if things get dangerous. The CEOs supposedly want to do this, so why not just let them? And to be fair, every so often, one of them does tap the brakes. A couple of months ago, OpenAI found that its new model, Astra, was extremely good at hacking. So it did something AI companies almost never do: it paused its biggest training run for a few weeks to tighten its security and run more safety tests. That was an expensive decision, which is admirable, but it’s not the end of the story. The researchers running the safety tests found that around half the time, Astra could tell