Does anyone like A.I.? podcast

Artificial intelligence has a weird problem right now. It is everywhere in spending, everywhere in marketing, and increasingly everywhere in daily use — but people still talk about it like a product category they resent. That is basically the point of Slate’s May 10 What Next: TBD episode, where Lizzie O’Leary talks with Verge editor in chief Nilay Patel about the gap between AI’s giant rollout and the public’s pretty thin affection for it. The episode’s blunt premise is that people might hate AI less if the upside felt obvious. ### What changed here? The new thing is not that critics dislike AI. That has been true for a while. The new thing is that skepticism has become the mainstream framing even as adoption accelerates. Slate packaged that mood into a direct question — does anyone actually like this stuff? — and used Patel as the guide because he has spent the last year watching tech companies force AI into products people did not ask to be remade. (podcasts.apple.com) ### Is the public really that sour? In the U.S., yes — or at least very mixed. Stanford’s 2026 AI Index pulls together recent survey data and shows a huge gap between experts and the public. On jobs, 64% of Americans expect AI to mean fewer jobs over the next 20 years, while only 5% expect more. On broader impacts like the economy and work, experts are much more upbeat than ordinary people. Trust is also weak — the U.S. posts the lowest trust in its own government to regulate AI responsibly among countries in that survey set. (podcasts.apple.com) ### But aren’t people using it anyway? They are. That is the twist. Edison Research at SSRS said in March that 52% of Americans were using AI platforms every week as of February 2026. ChatGPT led at 36% weekly use, followed by Google’s Gemini at 26% and Microsoft Copilot at 14%. So this is not a story where the public rejected AI and went home. It is more like people are using AI pragmatically while still feeling suspicious, annoyed, or unconvinced. (hai.stanford.edu) ### Why does that mismatch matter? Because it changes what “success” means. During the boom phase, companies could point to funding rounds, bigger models, and new data centers. But once half the country is touching these tools every week, the standard gets harsher. People stop grading on novelty. They ask whether the thing actually saves time, avoids mistakes, and earns a place in their routine. The podcast’s argument is that too much of AI still feels like a demo stapled onto products, not a clear improvement. (ssrs.com) ### Why do people dislike it so specifically? Because the failures are personal. Hallucinations waste time. AI summaries flatten nuance. Forced chatbot buttons make software feel cluttered. And a lot of “AI features” arrive as mandates from executives, not solutions to a user problem. That creates a familiar consumer-tech irritation — like being handed a Swiss Army knife when what you needed was a screwdriver. The tool may be impressive, but the moment feels wrong. (podcasts.apple.com) This is an inference from the episode’s framing, but it fits the broader survey picture of rising use without rising comfort. ### So what are companies missing? They keep selling the category when they need to prove the task. “AI” is too abstract. A product that drafts a clean email, speeds up coding, or handles a boring admin step can win people over. A product that asks users to care about the model, the infrastructure, or the future of intelligence usually will not. The catch is that narrow wins are less glamorous than world-changing rhetoric. But they are easier to trust. (podcasts.apple.com) ### Does liking AI even matter? Yes — because mainstream technologies do not survive on investor enthusiasm alone. They survive when people feel the trade is worth it. AI has clearly crossed into mass usage. What it has not won, at least yet, is broad warmth. That is the real story under the podcast episode: the buildout is ahead of the consent. (ssrs.com) (podcasts.apple.com)