Intro to Causal Discovery | Causal Summit 2026 | Pr. Martin Huber

Pr. Martin Huber — A Non-Technical Introduction to Causal Discovery (Block 3 · Causal Discovery in Business) A non-technical introduction to causal discovery. Rather than assuming a fixed causal structure about which intervention (e.g. a marketing campaign) affects which business outcome (e.g. sales), causal discovery aims to learn causal relationships among multiple variables in a data-driven manner. After introducing the general ideas behind causal discovery, the talk focuses on the practically relevant problem of identifying which variables in a system directly affect a business outcome of interest, and under which circumstances this can be learned from non-experimental data. About the speaker: Martin Huber is Professor of Applied Econometrics and Policy Evaluation at the University of Fribourg, where he develops statistical methods for causal analysis, impact evaluation, and machine learning, with applications in economics and business analytics. He holds a Ph.D. from the University of St. Gallen and held a visiting appointment at Harvard University. His work has been published in journals such as the Journal of the American Statistical Association, the Journal of Econometrics, and the Review of Economics and Statistics, and he is the author of the textbooks Causal Analysis and Impact Evaluation in Firms and Organizations. Links: Causal Analysis (book): https://mitpress.mit.edu/978026254591... Impact Evaluation in Firms and Organizations (book): https://mitpress.mit.edu/978026255292... LinkedIn:   / martin-huber-038a172   More about The Causal Summit: https://causalsummit.com