Empirical Methods in the Age of AI
About
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
