HAI Colloquium with Emily Sullivan: Philosophy of Science for Machine Learning

The Human-centered Artificial Intelligence Colloquium Committee warmly invites you to attend the March colloquium on 22 March. The talk ‘Philosophy of Science for Machine Learning’ will be presented by Emily Sullivan, assistant professor in Philosophy at Eindhoven University of Technology.

Philosophy of Science for Machine Learning

More and more sciences are turning to machine learning (ML) technologies to solve long-standing problems or make new discoveries – ranging from medical science to fundamental physics. At the same time, the exact same modelling technologies are used across society ranging from determining what news we see on social media to fraud detection and criminal risk assessment.

The ever-growing fingerprint ML modelling has on the production of scientific and social knowledge comes with opportunities and also pressing challenges. In this talk, Emily Sullivan discusses how philosophy of science and epistemology can help us understand the potential and limits of ML used for science and society. Specifically, Sullivan will draw on themes regarding the nature of scientific modelling, understanding, explanation, and idealisation.

Emily Sullivan

Emily Sullivan is an assistant professor of Philosophy at Eindhoven University of Technology and the Eindhoven Artificial Intelligence Systems Institute. She is a fellow in the ESDiT research consortium, co-director of the Eindhoven Center for the Philosophy of AI, and an associate editor for the European Journal for the Philosophy of Science.

Sullivan’s research lies at the intersection between philosophy and data and computer science, exploring the way AI technology mediates (scientific) understanding and shapes norms of information sharing, scientific modelling, explanation, and the ethical consequences that follow. She is currently the PI on a NWO Veni project (2021-2024) on the explainability of machine learning systems.