TechCrunch’s Equity podcast hosts—Anthony Ha, Kirsten Korosec, Sean O’Kane, and guest Amanda Silberling—discuss why AI executives keep making public comments that feel disconnected from ordinary life. Recent examples include Dazzle AI CEO Marissa Mayer asking an AI tool to write a school-assigned description of her daughter, OpenAI CEO Sam Altman suggesting parents create personalized podcasts for their kids’ drive to school and saying he couldn’t imagine parenting without ChatGPT, and Meta CEO Mark Zuckerberg saying it will become more acceptable to meet social and romantic needs through AI. The timing matters: the conversation opens with Anthropic expected to go public just as Wall Street’s appetite for heavy AI spending fades.

Kirsten asks whether the problem is marketing or product. Amanda says it is a little of both. The marketing problem: top executives sit in a room and talk about their own pain points—booking flights, making dinner reservations—and frame AI as the solution, but these are not the everyday challenges for most people. The product problem is more worrying: the industry is pushing a future where basic human interaction gets optimized out of actually occurring. She cites Bumble CEO Whitney Wolfe Herd’s idea of AI concierges going on dates with other AIs and only introducing the people if the AIs have a good date, and Mayer’s suggestion that her AI could coordinate with her husband’s AI. Silberling says that while dating is inefficient and a bad date can waste an evening, outsourcing the decision of whom to date to a computer that supposedly knows you better than you know yourself is not human. “Call me old school, but I think that humans being able to talk to each other is probably a net positive for society.”

Sean O’Kane jokingly asks about the ROI of a real-world conversation, and Amanda acknowledges the appeal of removing dating friction but rejects the replacement. The group also considers whether this is a product problem or just a messaging problem. Amanda’s conclusion is that high-up people at massively valuable companies focus on the wrong optimizations, while the value ordinary users get from ChatGPT or Claude is not the concierge-style life automation being pitched.

Anthony Ha draws a parallel to Uber, which was once seen as a tool for young urban millennials in San Francisco but eventually broadened its appeal. He notes that tech often succeeds by betting that it is the leading edge and that the consumer of the future will catch up. But in this case, the bet is not borne out: society is different, people are skeptical of the influence AI is having in their lives, and they want to live their own lives and parent their own children. Silberling sees a cultural tension in the simultaneous movement toward flip phones and CDs—people are tired of an algorithm telling them what to listen to and are looking for the right balance between useful optimization and preserving humanity. The episode suggests AI leaders need to understand both the product and the message if they want to build technology for everyone, not just themselves.