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Computational Epistemology

2024-2025

This Think Tank project responds to the rapid uptake of novel computational techniques across scientific research, including machine learning, large-scale simulations, and generative AI. While these methods open new avenues of research, their use has outpaced our understanding of the tools themselves. Science often demands new methods and tools to make progress, but their introduction should be accompanied by a detailed understanding of how, when, and why they work. This project brings together an interdisciplinary team to assess the opportunities and challenges raised by these methods and to develop a computational epistemology suited to frontier scientific research. 

A central concern is the lack of transparency in modern computational tools, which complicates efforts to distinguish between theoretical, data-driven, and computational sources of error. The project engages with current work on reliability and explainability, including the role of so-called “black box” models, and examines how these tools can support scientific discovery while remaining open to critical assessment and iterative refinement. These questions are important in because transparency and reliability are essential to maintaining trust in scientific knowledge. 

The project is designed to counter the main barrier we foresee, namely that different disciplines treat problems in this domain using quite distinctive conceptual repertoires. The project aims to make translation among these domains possible, to facilitate the full use of complementary expertise of the team members. 

Faculty Members: 

  • PI: Chris Smeenk, Professor, Department of Philosophy, Faculty of Arts & Humanities 
  • Sarah Gallagher, Professor, Department of Physics & Astronomy, Faculty of Science 
  • Alice Huang, Assistant Professor, Department of Philosophy, Faculty of Arts & Humanities; Department of Computer Science, Faculty of Science 
  • Dan Lizotte, Associate Professor, Department of Computer Science, Faculty of Science; Epidemiology & Biostatistics, Schulich School of Medicine & Dentistry 
  • Rob Corless, Emeritus Distinguished University Professor, Department of Mathematics and Department of Computer Science, Faculty of Science; Department of Philosophy, Faculty of Arts & Humanities 
  • Bill Turkel, Department of History, Faculty of Social Science 
  • Francesca Vidotto, Associate Professor, Department of Philosophy, Faculty of Arts & Humanities; Department of Physics & Astronomy and Department of Applied Mathematics, Faculty of Science (now at Instituto de Estructura de la Materia (IEM-CSIC), Madrid, Spain) 
  • Mark Daley, Professor, Departments of Computer Science, Biology, Applied Mathematics and Statistics & Actuarial Science, Faculty of Science; Epidemiology & Biostatistics, Schulich School of Medicine & Dentistry; Department of Electrical & Computer Engineering, Faculty of Engineering 
  • Lyle Muller, Assistant Professor, Department of Mathematics, Faculty of Science 

Postdoctoral Fellow: 

  • Andrew Richmond, Postdoctoral fellow, Rotman Institute of Philosophy 

Trainees: 

  • Jack Johnson, PhD Student, Department of Philosophy, Faculty of Arts & Humanities 
  • Carson Johnston, PhD Student, Department of Philosophy, Faculty of Arts & Humanities 
  • Heather Champion, PhD Student, Department of Philosophy, Faculty of Arts & Humanities