The Philosophy of Artificial Intelligence Network Talks (PAINT) is a biweekly international online seminar series that connects philosophers working on normative aspects of AI, including moral and political philosophy, philosophy of science and technology, epistemology, philosophy of mind, metaphysics, and aesthetics.
All seminars are on Mondays at 8:30 am PT / 11:30 am ET / 4:30 pm London / 5:30 pm Berlin. (We use ET as the reference point, when daylight saving changes shift things)
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Date: April 28, 2025
Speaker: Emily Sullivan
Title: Idealization Failure in ML
Abstract: Idealizations, deliberate distortions introduced into scientific theories and models, are commonplace in science. This has led to a puzzle in epistemology and philosophy of science: How could a deliberately false claim or representation lead to the epistemic successes of science? In answering this question philosophers have been single-focused on explaining how and why idealizations are successful. But surely some idealizations fail. I propose that if we ask a slightly different question, whether a particular idealization is successful, then that not only gives insight into idealization failure, but will make us realize that our theories of idealization need revision. In this talk I consider idealizations in computation and machine learning.
For a complete list of past and upcoming seminar presentations see the Talks page.
The seminars are held on Zoom and last 60 minutes. Our seminars will typically have one of the following formats
Format 1: 30 min presentation + 30 min discussion
Format 2: two flash talks, 15 min presentation + 15 min discussion each
Kathleen Creel (Northeastern), Sina Fazelpour (Northeastern), Karina Vold (University of Toronto)
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