Bytes: Week in Review — Meta, YouTube’s social media addiction case, a new AI literacy course, and Kalshi’s prediction market self-regulation
March 27, 2026·11 min
Host Stephanie Hughes opens the Friday Bytes segment by previewing three stories: a landmark social media negligence verdict, a new government AI literacy course, and new rules from prediction market platform Kalshi. A Los Angeles jury found Meta and YouTube negligent for designing platforms with addictive features — including infinite scroll and autoplay — that harmed a young user's mental health. The jury voted 10 to 2 in favor of negligence, and the companies face $6 million in damages. Both Meta and YouTube have said they disagree with the verdict and are exploring legal options. Axios tech policy reporter Maria Curie explains that internal documents revealed Meta executives knew their products could harm young users and proceeded anyway, which was central to the jury's decision. Curie describes the case as a bellwether, with over 2,000 related cases pending in California involving Meta, YouTube, TikTok, and Snapchat. A separate New Mexico case has already produced a $375 million charge against Meta, and an upcoming hearing there will specifically address product changes such as real age verification and ending encrypted messages. Curie emphasizes that the more significant development is the legal theory treating social media companies as product manufacturers rather than speech platforms, which could set the stage for congressional action. The second story covers the Department of Labor's new AI literacy course, introduced by the Trump administration to make American workers 'AI ready.' The course is delivered entirely via text message, takes about 10 minutes a day for one week, and covers topics like prompting and large language models. Hughes enrolled in the course herself and found it straightforward, emoji-filled, and noticeably pro-AI in tone. Curie frames the course as the administration's response to widespread public anxiety about AI and jobs, noting it aligns with a broader innovation-first agenda that prioritizes demystifying AI over regulating it. When asked whether the course could prevent job losses, Curie says bluntly it cannot do much, pointing out that layoffs are already happening based on corporations' expectations of AI productivity gains rather than AI's current capabilities. She notes there are no substantial workforce development plans from the administration, Congress, or corporate America to accompany this initial step. The third story covers Kalshi's announcement that it will preemptively block political candidates from trading on their own campaigns and prevent athletes, coaches, and referees from betting on events they are involved in. Curie connects this move to bipartisan congressional legislation that would ban such practices at the federal level and return authority to states. She draws a direct parallel to self-regulation strategies used by social media and AI companies to forestall government intervention. Curie expresses skepticism about whether Kalshi can effectively monitor thousands of markets, citing suspicious highly accurate predictions on events like the Iran war as evidence of the challenge. She notes that Kalshi also faces business pressure from its own user base to prevent insider trading that could undermine trust in the platform.
