Explainable AI and Society

an interdisciplinary, hybrid lecture series

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 experts. 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 April ’22
6:15 pm
Why We Need a Science of Machine Behavior
Iyad Rahwan
Max Planck Institute for Human Development
19 May ’22
6:15 pm
The Invisible Hand of Prediction
Computer Science
Moritz Hardt
Max Planck Institute for Intelligent Systems
09 Jun ’22
6:15 pm
Justification, Decision Threshold, and Randomness
Kate Vredenburgh
London School of Economics
14 Jul ’22
6:15 pm
Liability for AI
Herbert Zech
Humboldt Universität zu Berlin

Next lecture: Herbert Zech — Liability for AI

14 Jul ’22 – 6:15 pm 

Further details will be made available in due time.

Click here for information on past lectures.

Scientific organizers

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

Funded by the