Hard Fork

Can the U.S. Rein in Prediction Markets? + Joanna Stern on Her Year of A.I. Experiments + Our Producer Goes to Attention School

Hard Fork hosts
8 May 2026 9 min read 45m 30s
TL;DR

Prediction markets face regulatory uncertainty in the U.S. despite their potential as information aggregation tools, while Joanna Stern's year-long AI experiment reveals both the promise and pervasive nature of artificial intelligence in daily life. The episode also explores how attention has become a scarce resource manipulated by technology platforms.

Key Moments
[No transcript — approximate]
“[No transcript — approximate] Every other day there's a massive insider trading scandal involving prediction markets”
Opening discussion about regulatory challenges facing prediction markets
[No transcript — approximate]
“[No transcript — approximate] Prediction markets could be incredibly valuable for forecasting if properly regulated”
Discussing the potential benefits of prediction markets as information aggregation mechanisms
Joanna Stern
“[No transcript — approximate] AI is everywhere now, and I wanted to understand what it actually means for our daily lives”
Explaining her year-long experiment living with AI tools
[No transcript — approximate]
“[No transcript — approximate] Attention is the real commodity being traded in technology”
Discussion about how platforms monetize user attention
[No transcript — approximate]
“[No transcript — approximate] The regulatory framework for prediction markets hasn't caught up with the technology”
Concluding thoughts on policy challenges
About the show
›
Hard Fork is the New York Times' daily podcast covering the intersection of technology, business, and culture. Hosted by Kevin Roose and Casey Newton, the show explores how technology is reshaping society, from AI developments to regulatory challenges. This episode examines prediction markets, AI experiments, and attention in the digital age.
Takeaways
1
Prediction markets need clearer U.S. regulations Prediction markets offer valuable signal aggregation but face legal ambiguity that creates insider trading risks. Without clear regulatory frameworks, the U.S. risks falling behind other countries in developing this technology, limiting its potential as a forecasting tool.
2
AI integration is now invisibly pervasive Stern's experiments show AI is embedded across consumer experiences—from search to content recommendations—often without explicit user awareness. This invisible integration raises questions about transparency and whether users truly understand how AI influences their digital experiences.
3
Attention economy defines tech competition Platforms compete primarily for user attention rather than delivering specific features, employing sophisticated behavioral design to maximize engagement time. Understanding attention as a resource helps explain platform incentives and the difficulty users face in controlling their digital habits.