The New York Times' Hard Fork podcast examines growing regulatory pressure on prediction markets in the United States, as policymakers grapple with repeated insider trading scandals tied to these platforms. The episode explores whether current regulatory frameworks can effectively oversee prediction markets, which have surged in popularity but raised concerns about market manipulation and information asymmetries. The discussion highlights the tension between maintaining open markets for forecasting and protecting against illicit trading activity. In related segments, the episode features journalist Joanna Stern's retrospective on a year spent experimenting with artificial intelligence tools, examining how AI has integrated into daily workflows and creative processes. Additionally, a Hard Fork producer participates in "attention school," an exploration into managing focus and cognitive resources in an increasingly AI-saturated digital environment. Together, these segments paint a picture of AI's expanding role both in markets and personal productivity.