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?
| 20 Oct ’22 6:00 pm |
What AI can Learn from Law Law |
Réka Markovich University of Luxembourg |
| 17 Nov ’22 6:00 pm |
Hybrid, Explanatory, Interactive Machine Learning – Towards Human-AI Partnership Computer Science |
Ute Schmid University of Bamberg |
| 15 Dec ’22 6:00 pm |
What Advertising Data Tells us about Society Computer Science |
Ingmar Weber Saarland University |
| 19 Jan ’23 6:00 pm |
Minimal Ethics – A Framework for Applied Ethics in the Digital Sphere Philosophy |
Vincent Müller Friedrich-Alexander-University Erlangen-Nuremberg |
Next lecture: Vincent Müller – Minimal Ethics
19 Jan’23 – 6:00 pm
Location: H 24 (RW I)
Further information will follow soon.
To register, either click on the registration button and fill out the Google form or send an email with the subject “Registration” to Leon Weiser: leon.weiser@uni-bayreuth.de.
The mail should contain the dates you want to participate and whether you want to participate online or in person.
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, Timo Speith
Funded by the
