WORKSHOP
Bias and Discrimination in Algorithmic Decision-Making
Issues in Explainable AI #3
October 8/9, 2021, Hannover, Germany
https://www.bias-project.org/wp-content/uploads/2021/03/Bias_Workshop_Poster.pdf

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WORKSHOP

Bias and Discrimination in Algorithmic Decision-Making
Issues in Explainable AI #3
October 8/9, 2021, Hannover, Germany

Keynote Speakers:

•        Emily Sullivan (TU Eindhoven)
•        Christian Heinze (U Heidelberg)
•        Markus Langer (U Saarland)
•        Kasper Lippert-Rasmussen (U Aarhus)

CALL FOR PAPERS

Algorithmic predictions are increasingly used to inform, guide,
justify or even replace human decision-making in many areas of
society. However, there is growing evidence that algorithmic
predictions are often shaped by bias and discrimination and thus
threaten to have detrimental effects on certain social groups and on
social cohesion in general.
We invite researchers to present their work and discuss their ideas
concerning these challenges at our workshop in Hannover. The workshop
will be held in person, but depending on the development of the
pandemic it may be shifted online.

Contributions from various disciplines, including epistemology,
ethics, law, sociology, psychology, and computer science, are welcome.
Presentations (20 minutes) may include, but are not limited to,
research on the following topics:
• Conceptual issues of algorithmic bias and discrimination
(epistemology of computer bias vs. human bias; meaning and
classification of algorithmic discrimination; psychological,
sociological, legal, technical frameworks for capturing algorithmic
discrimination etc.)
• Normative tenets of dealing with algorithmic bias and discrimination
(relation to theories of social fairness and political justice;
stereotype threat, affirmative action and their application to
algorithmic discrimination; connections of discrimination to issues
such as AI explainability, AI transparency, AI autonomy etc.)
• Analyses of types of discrimination, fields of application, or kinds
of implementation (discrimination with regard to gender, race,
religion, age, health; discrimination in job hiring, credit granting,
predictive policing, advertisement selection, recommendation systems;
challenges and solutions for supervised learning, unsupervised
learning, reinforcement learning etc.)

Submissions: Anonymized applications must be submitted as written
abstracts (maximum 500 words) through easy chair (Link:
https://easychair.org/conferences/?conf=bad2021). The deadline for
submissions is April 30, 2021. Notifications concerning participation
will be issued by June 30, 2021.

Organization: The workshop is organized by the interdisciplinary
project “Bias and Discrimination in Big Data and Algorithmic
Processing – BIAS” (www.bias-project.org), funded by Volkswagen
Foundation. It is part of the workshop series “Issues in Explainable
AI” (www.explainable-intelligent.systems)

Contact: Prof. Uljana Feest, Leibniz University Hannover, Institute of
Philosophy, Im Moore 21, D-30167 Hannover, Germany. E-mail:
feest@philos.uni-hannover.de