DEMO Seminar: Causal Inference and Decision Making


17.4.2019 10:15 — 12:00

Sijainti: Mattilanniemi, MaD 302
DEMO - Decision Analytics utilizing Causal Models and Multiobjective Optimization is a profiling area of our university, http://www.jyu.fi/demo. This presentation is aimed at anyone interested in themes of DEMO and does not require deep knowledge of e.g. causality or statistics.

Speaker: Juha Karvanen (University of Jyväskylä, Department of Mathematics and Statistics)

Title: Causal inference and decision making

Abstract: The talk starts with an introduction to causality. Do-calculus and ID-algorithm are tools for checking the identifiability of causal effects from observational data. The connections between causality and decision making are natural: A decision maker optimizes the consequences of actions and the estimation of these consequences, i.e., the causal effects of actions, from the data is a problem of causal inference.  In the second part of the talk, counterfactuals are formally defined. A counterfactual definition of fairness in artificial intelligence and decision making is discussed. Finally, some new results on the causal inference from multiple experimental and observational studies are presented.

You are warmly welcome!



Kaisa Miettinen

Professor, director of DEMO

Faculty of IT


050 373 2247