Beyond Bias - Locating Questions of Injustice in Teaching Data Science and Artificial Intelligence - Tobias Matzner (Germany)
Abstract
Data Science and Artificial Intelligence have repeatedly come under scrutiny because of injustices they produce. AI based services only work for a certain part of the populace, scoring and ranking systems are skewed towards certain groups, errors concentrate on specific persons etc.
Thus, when teaching Data Science and Artificial Intelligence, such issues should be part of the curriculum. Most often in research and in educational concepts, injustice is discussed as bias outputs of information processing. In social studies of technology, recently some people have begun to challenge this idea of equating injustice with bias. The talk will shortly present why this is the case – and how this challenge from current research opens up new ways of discussing the social impact of Data Science and Artificial Intelligence in schools.
Bio Tobias Matzner
Dr. Tobias Matzner is professor for “Media, Algorithms, and Society” at Paderborn University in Germany. His work combines theories of (digital) media and technologies with approaches from political philosophy, cultural studies, and social theory.
He has studied philosophy and computer science in Karlsruhe, Rome, and Berlin. Prior to his appointment in Paderborn, he has been working at the International Centre for Ethics in the Sciences and Humanities at the University of Tübingen as well as the New School for Social Research in New York.
