2 December 2020, by Internetredaktion
At the interface of computer science, social sciences and law a new research field is currently establishing itself, which addresses the fairness of algorithms. Foci of research are, by which mechanisms and to what extent decisions made by algorithms can contain systematic biases – particularly in the context of machine learning and artificial intelligence.
The urgency of this highly interdisciplinary research field is underlined by the tremendous expansionof applications of artificial intelligence and algorithm-based decisions in all aspects of societal organization.
With this summer school we want to discuss some aspects of this new research field and attempt a dialog about these topics across disciplinary boundaries.
Call for Application
We ask doctoral students and post-docs to apply.
The summer school is an opportunity for all lawyers who work on legal issues which involve AI elements and assumes a deeper analysis of the respective field of law and want to work on algorithmic biases. Please, present your research topic and your motivation for your application (not more than 4.000 characters). CV and list of publication (if possible) are required. Please, send your application to claudia.schubert"AT"uni-hamburg.de.
For data scientists and computer scientists with a focus on machine learning / artificial intelligence this summer school is an opportunity to understand the challenges of identifying algorithmic biases and their societal impact. We require a statement indicating your competence level in ML/AI and a brief statement outlining your motivation for participating in this summer school (not more than 4.000 characters). CV and list of publication (if possible) are required.
Place: Otto-Bagge-Kolleg, Sehlendorf
Deadline for applications: 1.5.2021
Organisation Team: Prof. Dr. Marc-Thorsten Hütt (Jacobs University), Prof. Dr. Claudia Schubert (Universität Hamburg)
Please, note that the summer school will take place in person. If the pandemic situation does not allow this, we will postpone the event as we need a close cooperation with direct interaction.