Empirical Methods in the Age of AI

Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.

Hosted by the Stanford Causal Science Center and the Graduate School of Business, the Empirical Methods in the Age of AI Conference brings together leading academics and industry practitioners to explore the frontier of data-driven research in an era of powerful AI tools. The conference will examine how AI is changing empirical workflows, enabling new forms of measurement and analysis, and creating opportunities—and challenges—for generating reliable evidence from data.

Through keynote talks, panels, and discussions, participants will explore topics such as AI-assisted research, data analysis workflows, causal inference, econometrics, measurement, and the evolving relationship between human expertise and machine intelligence. The event is designed to foster dialogue between researchers developing new empirical methods and practitioners applying them to real-world problems.

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Please sign up for one of the waitlists below:

• General Admission waitlist
• Non-Stanford Academia, Nonprofit, Government waitlist
• Stanford: Please sign up for the waitlist; Stanford.edu email required