Raise a pint of Guinness to William Sealy Gosset on his birthday! theconversation.com/the-geni…

Spotted on the Circle line - a shoutout to Baltic snake cults (a reference to Diarmaid MacCulloch’s review of my ‘Silence of the Gods’ in the @LRB lrb.co.uk/the-paper/v48/n09/…

Hockney dead at 88. Smoking kills.

British artist David Hockney has died aged 88, his publicist has said 🔗: telegraph.co.uk/news/2026/06…

In the dead of night the Scots arrived at the Airbnb across the street. Decked out and playing the pipes at 6:30 am. So it begins…

You have noticed it. ChatGPT feels dumber than it used to. Your prompts that worked six months ago produce worse results now. The writing sounds flatter. The ideas sound safer. The internet itself feels like it is shrinking. Every article reads the same. Every email sounds the same. Every answer sounds like it was written by the same voice. You thought it was you. It is not you. Researchers at Oxford and Cambridge published a paper in Nature proving what is happening. They call it Model Collapse. Here is the mechanism in one sentence. AI trained on AI-generated data gets dumber every generation until it forgets what real human data looked like. The internet is filling with AI-generated content. Blog posts. Articles. Reviews. Comments. Social media. AI companies scrape the internet to train the next generation of models. Which means the next generation of AI is being trained on the output of the current generation. Each cycle loses information. Not randomly. It loses the rarest, most unusual, most creative parts first. The researchers call these the "tails of the distribution." The weird ideas. The unexpected perspectives. The things that made the internet feel human. Those disappear first. What remains is the average. The safe. The expected. The bland. Then the next generation trains on that. And loses more. And the next generation trains on that. And loses more. The researchers proved this is not a slow decline. Major degradation happens within just a few iterations. Even when some of the original human data is preserved. They tested it on large language models. On image generators. On statistical models. The pattern was the same every time. The output converges toward a narrow, flattened version of reality that looks nothing like the original data. The lead researcher put it plainly. "Large language models are like fire. A useful tool. But one that pollutes the environment." The pollution is invisible. You cannot see which sentence on the internet was written by a human and which was written by AI. Neither can the AI that is about to train on it. And once the tails are gone, they do not come back. The damage is irreversible. This is not a prediction anymore. It is a diagnosis. The internet you grew up on was built by humans writing things no algorithm would have written. Strange, personal, imperfect, alive. That internet is being diluted. One generation of AI at a time. And the models trained on what remains are learning a smaller and smaller version of the world. Model Collapse is not a technical problem. It is a cultural one. The thing that made the internet worth reading is the thing that disappears first.

Yesterday, the government published its ‘AI Adoption Plan’ for the creative industries. Somewhat incredibly, it says we should be pushing AI adoption before the government resolves the issues around copyright. This would be great for the AI industry, and terrible for creatives. Important for people to know what the government is pushing here. Short thread on its contents ⬇️ 1/n

A social media ban should be extended to those aged 16 and 17, the children’s commissioner has proposed. Keir Starmer is considering whether to ban under-16s from social media sites, but Dame Rachel de Souza has said that any ban must apply “equally to all children” up to 18. 🔗: telegraph.co.uk/news/2026/06…

How do we have better tech conversations with our kids? Episode 2 of Screen Sense, a new podcast on parenting in a digital world: with me and Andrew Przybylski, available now! Apple: podcasts.apple.com/gb/podcas… Spotify: open.spotify.com/episode/1yi… Substack: screensensepodcast.substack.…

You absolutely know that this ‘AI assistant to help people find work’ will use an AI model built by stealing people’s work.

Breakthrough ovarian cancer drug offers patients more time and better quality of life bbc.in/4ofq5Lm

The Pope is making exactly our point. LLMs “may imitate or even simulate, but they do not understand.” This is the core epistemic fault line. Most AI evaluation is still based on one assumption: if a system statistically approximates human behaviour, then it is close to human intelligence. But approximation is not intelligence. Simulation is not understanding. LLMs can produce the right answer without knowing why it is right. They can simulate empathy without feeling. They can imitate judgment without responsibility. They can generate coherent explanations without having a world to which those explanations are accountable. Stop confusing behavioural similarity with cognitive equivalence. Human understanding is embodied, affective, relational, motivational, and normative. It is not just the production of plausible text. * Full paper in the first reply