I was halfway through writing the next post in my AI data moat series when the verdict came in. A jury in Los Angeles found Meta and Google liable for the way they designed Instagram and YouTube. Not for what users posted on them, but for the products themselves. Infinite scroll, autoplay, beauty filters, recommendation algorithms tuned to maximise time on platform. Ten of twelve jurors agreed that those are design defects, and that the companies who shipped them are responsible.
The damages were $6 million, which is pocket change for companies that size. But the money is not the point. What matters is the legal theory that won. For years, Section 230 shielded platforms from liability for user-generated content. This case walked around that entirely by arguing that the product itself is defective, the same kind of product liability claim we apply to cars and medication, now applied to software design for the first time. I put down the draft I was working on and started writing this instead, because this verdict changes the conversation I have been having with you for the past six weeks.
Design choices are product decisions
When a product team adds infinite scroll, that is a design choice. When they tune a recommendation algorithm to maximise session length, or build memory features that make it harder to switch providers, or design an AI agent with undisclosed commercial relationships to the merchants it recommends, those are all design choices made by small groups of people inside private companies, optimising for engagement, retention, or revenue. None are reviewed by a regulator before they ship. They become the default for millions of people, and by the time anyone with oversight authority catches up, the behaviour is locked in.
The jury did not say social media is bad. It said the specific way these platforms were designed was negligent. That distinction matters, because it means the question is not "should social media exist" but "should this specific feature exist in this form without adequate safeguards." Product liability, applied to code.
Internal Meta documents reportedly showed the company's own researchers warned executives in 2020 that certain algorithmic features were causing measurable psychological harm to teenage girls. The features stayed to meet engagement targets.
The tobacco parallel holds up this time
The tobacco litigation in the 1990s succeeded not because smoking was dangerous, which everyone already knew, but because internal documents proved the companies had the data on the harm and kept marketing to young people anyway. The social media trial followed the same path: internal research showing harm to teenagers, continued deployment of the features causing it, testimony from executives who had seen the data. Two thousand similar lawsuits waiting behind this one, TikTok and Snap settling before trial, a New Mexico jury finding Meta liable for $375 million the day before, and Meta's stock dropping 6.8% in a single session.
The product was not defective by accident. It was defective by decision. And the people who made that decision had the research in front of them.
Now apply this to AI
This is where my data moat series and this verdict collide. If a jury can rule that infinite scroll is a product defect because it was engineered to be addictive, what happens when the same theory gets applied to AI? Memory systems that build behavioural profiles with no export function, recommendation engines that could steer users toward commercial partners, agentic systems making purchases with undisclosed incentives, personalisation features designed to deepen platform dependency. These are not content decisions. They are design decisions, the same category the jury just ruled on.
The companies that build portability, transparency, and user control into their products now will have a legal advantage, not just a moral one. The era of shipping first and dealing with consequences later just got more expensive.
I keep saying we have the memory of a goldfish when it comes to technology platforms. But juries remember longer than legislatures. The design choices AI companies make today will be examined in courtrooms years from now, under a legal theory that did not exist until this week. Whether they are building with that in mind or still optimising for the next quarter will determine which side of the verdict they end up on.