Jonathan Stray is a Senior Scientist at the Center for Human-compatible AI at UC Berkeley, where he works on the design of AI-driven media with a particular interest in well-being and conflict. Previously, he taught the dual masters degree in computer science and journalism at Columbia University, worked as an editor at the Associated Press, and built document mining software for investigative journalism.

Jonathan Stray

What Are the Politics of a Platform? The Case of X

Meta Dropped Fact-Checking Because of Politics. But Could Its Alternative Produce Better Results?

Experiments are the Best Kind of Transparency

What is Media Diversity and Do Recommender Systems Have It?

What’s the Difference Between Search and Recommendation?

Remote Query Execution: A Powerful Way to do Privacy-Protecting Research on Platform Data

Making Amplification Measurable

From “Filter Bubbles”, “Echo Chambers”, and “Rabbit Holes” to “Feedback Loops”

A Menu of Recommender Transparency Options

What Will “Amplification” Mean in Court?

Governing Access to Synthetic Media Detection Technology

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Jonathan Stray