Explainable AI and Society

an interdisciplinary, hybrid lecture series

This interdisciplinary lecture series discusses the potentials and questions within the rising field of Explainable Artificial Intelligence (XAI). Modern AI can be used to drive cars, to decide on loans, or to detect cancer. Yet, the inner workings of many AI systems remain hidden even to expert programmers. Given the crucial role that AI systems play in modern society, this seems unacceptable. But how can we make complex, self-learning systems explainable? What kinds of explanations are we looking for when demanding that AI must be explainable? And which societal, ethical and legal desiderata can actually be satisfied via explainability?


21 Oct ’21
6:15 pm
Law
 
Discrimination by AI systems:
An Analysis from a Legal Perspective.
Georg Borges
Saarland University
18 Nov ’21
6:15 pm
Psychology
 
Action Regulation in Human-AI-Interaction:
The Psychology of Intelligent Automation
Thomas Franke & Tim Schrills
University of Lübeck
16 Dec ’21
6:15 pm
Computer
Science
Algorithmic recourse:
Theory and Practice
Isabel Valera
Saarland University
20 Jan ’22
6:15 pm
Philosophy
 
Explaining Machine Learning:
A New Kind of Idealization?
Emily Sullivan
Eindhoven University of Technology

Next lecture: to be announced…

Scientific organizers

Kevin Baum, Georg Borges, Holger Herrmanns, Lena Kästner, Markus Langer, Astrid Schomäcker, Andreas Sesing, Ulla Wessels

Funded by the