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 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.

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.

What should social media platforms do when the state itself becomes a threat to democracy? In a new paper published in the journal Information, Communication & Society, Daniel Kreiss and Lorcan Neill, both at the Hussman School of Journalism and Media and the Center for Information, Technology, and Public Life at the University of North Carolina at Chapel Hill, borrow from "militant democracy," a framework scholars developed in the 1930s as fascists exploited democratic freedoms to seize power. They offer a framework for wedding platform policies to democratic principles. With midterm elections just weeks away in the United States and elections playing out in Brazil and beyond, Justin Hendrix caught up with them about what the framework suggests, and what trust and safety executives can do even in a context where the interests of platform owners are fused with those of autocratic leaders.

In the United States, the census touches tech policy at more points than you might realize. It's a massive data collection operation and a piece of democratic infrastructure all at once. danah boyd is the author of Data Are Made, Not Found: A Story of Politics, Power, and the Civil Servants Who Saved the US Census, a new book from the University of Chicago Press that tells the story of the people who make the census, recounting how the 2020 census came together amid fractured politics and a raging pandemic. It’s a complicated story, and it has implications for the next census, which is already in planning, and is already a source of controversy and concern.

Amid a frenzy of headlines about AI safety and just two weeks out from a planned meeting of US President Donald Trump and China’s President Xi Jinping, Justin Hendrix moderated a discussion around the question, what does AI governance actually demand right now? Convened by the the Institute for America, China, and the Future of Global Affairs at the Johns Hopkins School of Advanced International Studies (SAIS) in Washington, D.C., the discussion included Amba Kak from the AI Now Institute, Kat Duffy from the Council on Foreign Relations, Miro Plueckebaum from the Oxford Martin AI Governance Initiative, and Jack Shanahan from SAIS ACF and the Center for a New American Security.

On July 16, Hugging Face, a company that provides a platform for AI models, datasets, and other machine learning applications, posted a “security incident disclosure” to its blog about an “intrusion” into its infrastructure. But this was no typical hack. The company said “it was driven, end to end, by an autonomous AI agent system,” matching what it said is the “‘agentic attacker’ scenario the industry has been forecasting.”A few days later, OpenAI posted to its blog that the agent was in fact “driven by a combination of OpenAI models” with “reduced cyber refusals for evaluation purposes — while being internally tested on a benchmark⁠ of cyber capabilities.”To try to better understand these developments and their implications for the US and international debates over AI governance, Justin Hendrix spoke to two individuals who are following the details closely:Vinh Nguyen, a senior fellow for AI at the Council on Foreign Relations and the former chief responsible AI officer and chief data scientist for operations at the National Security Agency (NSA), andGraham Webster, a lecturer and research scholar in the Program on Geopolitics, Technology, and Governance at Stanford University, where he leads the DigiChina Project.