The Tech Policy Press Podcast

Google is an illegal monopolist. That is the finding of two federal judges in landmark antitrust cases over the company’s dominance of online search and advertising technology. But when it came time to order remedies, neither judge broke up the company. To discuss what the remedies mean for competition and for the broader effort to hold big tech firms accountable to democracy, particularly in the AI era, Justin Hendrix spoke with Barry Lynn, executive director of the Open Markets Institute, and Mihir Kshirsagar, who leads the Tech Policy Clinic at Princeton’s Center for Information Technology Policy (CITP).

In this episode, Tech Policy Press deputy editor Ramsha Jahangir examines the latest developments in Europe’s AI policy debate, from the push for safe, trusted and resilient AI to renewed calls for legislation on AI liability.
Risto Uuk, head of European policy and research at the Future of Life Institute, joins the podcast to discuss the emerging risks and the broader policy landscape. Then, Ramsha interviews Brando Benifei, a Member of the European Parliament, about the gaps left by the withdrawal of the proposed AI Liability Directive, the challenges of assigning responsibility across the AI value chain, and the case for a renewed European approach.

In the daily surge of news and headlines about technology, it can be hard for any journalist to fully contextualize the individual events they are reporting on and trace the underlying patterns, structures, and ideas that are producing them. Today’s guest excels at just that, covering one of the most complicated beats in technology journalism. Natasha Singer is a technology reporter for The New York Times, where she has spent more than a decade investigating how tech shapes schools. Her new book is Coding Kids: Big Tech’s Battle to Remake Public Schools, published by W.W. Norton.

It’s a cliché to say that technology is changing war. But today, the pace of change is severe, not only because of advances in fields such as artificial intelligence, but also because of a range of trends and phenomena at the intersection of tech and geopolitics that are changing what it means for nations to compete, and to fight and defend themselves. Today’s guest is Steve Feldstein, a senior fellow in the Democracy, Conflict, and Governance Program at the Carnegie Endowment for International Peace and the author of Bytes and Bullets: Global Rivalries, Big Tech, and the New Shape of Modern Warfare, published by St. Martin’s Press.

How can you tell if an algorithm is any good? For University of Michigan assistant professor of information and public policy Ben Green, the answer lies less in accuracy scores, fairness metrics or any other technical measure than in what the system actually does once it’s out in the world. In his new book, Algorithmic Realism: Data Science Practices to Promote Social Justice (MIT Press), he offers data scientists a method for scoping, building and evaluating algorithms in the service of social justice.