Warning:You don't have javascript enabled.
catherine stinson
email hello · at · myname · dot · ca
Catherine Stinson, photo by Mishann Lau, www.mishann.com

bio

I am Queen's National Scholar in Philosophical Implications of Artificial Intelligence and Assistant Professor in the Philosophy Department and School of Computing at Queen's University, Kingston. I received my PhD from the University of Pittsburgh in History & Philosophy of Science, and a MSc in Computer Science from the University of Toronto. I have published in philosophy of neuroscience (attention, mechanistic explanation), philosophy of psychiatry (anorexia, classification of disorders), philosophy of artificial intelligence (explanation in artificial neural networks, connections between AI and eugenics), and tech policy (data governance, terms of service agreements, AI ethics education).

teaching

Current Courses
PHILOSOPHY IN SCIENCE FICTION
Philosophy Department, Queen's University
SYLLABUS

SOCIAL, ETHICAL, AND LEGAL ISSUES IN COMPUTING
School of Computing, Queen's University
SYLLABUS SAMPLE LECTURE VIDEO

TOPICS IN PHILOSOPHY OF SCIENCE: 3rd WAVE AI
Philosophy Department, Queen's University
SYLLABUS

MORE ABOUT MY TEACHING

Select Past Courses

work in progress
  1. An Empirical Challenge to Social Classification using Facial Recognition
    (With R.F. Khan, S. Baranek, G. Reed)
    (under revision)

academic papers
  1. Large Language Models and the Disappearing Private Sphere
    (With A. Cappello, M. Dada, V. Grigoreva, R. F. Khan, H. Stuart)
    Office of the Privacy Commissioner Contributions Program Report (2024)
    PDF
  2. Collaboration or Corporate Capture? Quantifying NLP’s Reliance on Industry Artifacts and Contributions
    (With W. Aitken, M. Abdalla, K. Rudie)
    ACL (2024)
    PREPRINT
  3. The State of Documentation Practices of Third-party Machine Learning Models and Datasets
    (With E.L. Oreamuno, R.F. Khan, A.A. Bangash, B. Adams)
    IEEE Software (2024)
    PREPRINT
  4. A Feeling for the Algorithm: Diversity and Expertise in Artificial Intelligence
    (With S. Vlaad)
    Big Data and Society (2024)
    LINK
  5. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
    (With Srivastava, A. and 443 other authors)
    Transactions on Machine Learning Research (2023)
    LINK
  6. Algorithms are not neutral: Bias in collaborative filtering
    AI and Ethics (2022)
    PREPRINT LINK
  7. A Bio-Inspired Framework for Machine Bias Interpretation
    (With Robertson, J., Hu, T.)
    Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, AIES ’22 (2022)
    LINK
  8. Revisiting Popularity and Demographic Biases in Recommender Evaluation and Effectiveness
    (With N. Neophytou, B. Mitra.)
    European Conference on Information Retrieval, ECIR 2022 (2022)
    PREPRINT
  9. The Dark Past of Algorithms That Associate Appearance and Criminality
    American Scientist. (January 2021)
    LINK
  10. Limit Corporate Influence, Maximize Public Involvement and Accountability
    (With L. James, M. Abdalla, N. Moellers, S. Monsurinjohn, S. Phillips, A. L. Simpson.)
    New Digital Research Infrastructure Organization, Whitepaper. (December 2020)
    PDF
  11. Algorithms associating appearance and criminality have a dark past
    Aeon. (May 2020)
    LINK
  12. From Implausible Artificial Neurons to Idealized Cognitive Models: Rebooting Philosophy of Artificial Intelligence
    Philosophy of Science (2020)
    PREPRINT LINK
  13. Artificial Intelligence and the Future of Education
    Education for a Changing World. (2020) Future EDge, Issue 2. New South Wales Department of Education.
    LINK
  14. The Absent Body in Psychiatric Diagnosis, Treatment, and Research
    Synthese. (2019) Eds. S. Tekin, E. Machery.
    LINK PREPRINT
  15. Healthy Data: Policy solutions for big data and AI innovation in health
    Mowat Centre (December 13, 2018)
    LINK
  16. Explanation and Connectionist Models
    The Routledge Handbook of the Computational Mind. (2018) Eds. M. Colombo, M. Sprevak.
    PREPRINT
  17. Mechanistic Explanation in Neuroscience
     (With J. Sullivan.)
    The Routledge Handbook of Mechanisms and Mechanical Philosophy. (2017) Eds. S. Glennan, P. Illari.
    PREPRINT
  18. Back to the Cradle: Mechanism Schemata from Piaget to DNA.
    Eppur si muove: Doing History and Philosophy of Science with Peter Machamer. (2017) Eds. M. Adams, Z. Biener, U. Feest, J. Sullivan. Springer.
    PREPRINT
  19. Mechanisms in Psychology: Ripping Nature at its Seams
    Synthese (2016).
    LINK PREPRINT
  20. Owning an Overweight or Underweight Body: Distinguishing the Physical, Experienced and Virtual Body
     (With I.V. Piryankova, H.Y. Wong, S.A. Linkenauger, M.R. Longo, H.H. Buelthoff, B.J. Mohler)
    PLOS One. (2014)
    LINK PREPRINT
  21. Searching for the Source of Executive Attention.
    PSYCHE. (2009)
    With commentary by Andy Clark.
    LINK COMMENTARY LINK PREPRINT

other writing

selected presentations