Algorithmic recourse: from theory to practice | AI FOR GOOD DISCOVERY
0In this talk I will introduce the concept of algorithmic recourse, which aims to help individuals affected by an unfavorable algorithmic decision to recover from it.
First, we show that while the concept of algorithmic recourse is strongly related to counterfactual explanations, existing methods for the later do not directly provide practical solutions for algorithmic recourse, as they do not account for the causal mechanisms covering the world.
Next, we explore the theoretical results that prove the need of complete causal knowledge to guarantee recourse and show how algorithmic recourse can be useful to provide novel fairness definitions that short the focus from the algorithm to the data distribution. Such novel definition of fairness allows us to distinguish between situations where unfairness can be better addressed by societal intervention, as opposed to changes on the classifiers. Finally, we examine the practical solutions for (fairness in) algorithmic recourse, in realistic scenarios where the causal knowledge is only limited.
Speaker(s):
Isabel Valera, Full Professor, Department of Computer Science, Saarland University
Moderator(s):
Wojciech Samek, Head of Department of Artificial Intelligence, Fraunhofer Heinrich Hertz Institute
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