Pattern Recognition in Scientific Practice

What are patterns and how can they be recognized? In the 20th century, scientists across disciplines began asking themselves this question with increased intensity. Anthropologists attempted to reveal patterns in culture. Cyberneticists sought out rules for extracting the most recognizable features from patterns. Mathematicians designed techniques to automatically classify patterns. Under the pressure of this scrutiny, patterns suddenly coalesced as objects of scientific inquiry. This talk situates this development historically, with special reference to the co-extensive emergence of machine learning and data-driven surveillance techniques.

Aaron Gluck-Thaler is an Assistant Professor at the University of Toronto’s Munk School of Global Affairs & Public Policy, where he holds the Professorship in Data Sciences and is a Faculty Affiliate at The Citizen Lab. Aaron’s research focuses on the history of surveillance, artificial intelligence, and science and technology in the Cold War. His current book project examines the role that scientists played in the emergence of data-intensive surveillance in the 20th century. Aaron received his PhD in the History of Science from Harvard University.