Uploaded April 2021 | Updated September 2026, 10 hours ago
Reupload from the 26th of April 2021
Recorded in the Carl Friedrich von Weizsäcker Colloquium on the 21st of April 2021.
AI is not only supposed to help to tackle social problems but it is also frequently used to in fact solve such problems. AI-assisted systems play an increasingly important role in the legal domain, the health sector, environmental research, public policy-making and the like. Research in this field is numerous and diverse. In this talk, we want to argue, however, that it is also interesting to have a look at the opposite direction: How can our knowledge of the social world and its structural features help us to approach problems of AI? In particular, we will investigate how a social perspective on problems of justification helps us to address epistemic problems of machine learning theory.
Reupload from the 26th of April 2021
Recorded in the Carl Friedrich von Weizsäcker Colloquium on the 21st of April 2021.
AI is not only supposed to help to tackle social problems but it is also frequently used to in fact solve such problems. AI-assisted systems play an increasingly important role in the legal domain, the health sector, environmental research, public policy-making and the like. Research in this field is numerous and diverse. In this talk, we want to argue, however, that it is also interesting to have a look at the opposite direction: How can our knowledge of the social world and its structural features help us to approach problems of AI? In particular, we will investigate how a social perspective on problems of justification helps us to address epistemic problems of machine learning theory.
