Publications

New Papers

Cappello, A., Dada, M., Grigoreva, V., Khan, R., Stinson, C. & Stuart, H. (2024) Large Language Models and the Disappearing Private Sphere. Report for the Office of the Privacy Commissioner Contributions Program. https://etlab.cs.queensu.ca/files/2024/04/OPC_Final_Report_2023.pdf

Aitken, W., Abdalla, M., Rudie, K. & Stinson, C. (under review). Collaboration or Corporate Capture? Quantifying NLP’s Reliance on Industry Artifacts and Contributions. https://arxiv.org/abs/2312.03912

2024

Oreamuno, E.L., Khan, R.F., Bangash, A.A., Stinson, C. & Adams, B. (forthcoming). The State of Documentation Practices of Third-party Machine Learning Models and Datasets. IEEE Software. https://arxiv.org/pdf/2312.15058

Stinson, C. & Vlaad, S. (2024). A Feeling for the Algorithm: Diversity and Expertise in Artificial Intelligence. Big Data & Society. https://journals.sagepub.com/doi/full/10.1177/20539517231224247

Vlaad, S. (2024). Transitioning Texts and Genre Reassignment: Trans Poetics as Trans Philosophy. PhiloSOPHIA. https://www.pdcnet.org/sophia/content/sophia_2024_0014_0031_0049

2023

Srivastava, A., A. Rastogi, A. Rao, …, Stinson, C., et al. (441 additional authors). (2023). Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. Transactions on Machine Learning Research, 2835-8856. https://openreview.net/forum?id=uyTL5Bvosj

Li, J., Aitken, W., Bhambhoria, R., & Zhu, X. (2023). Prefix Propagation: Parameter-Efficient Tuning for Long Sequences. ArXiv, abs/2305.12086. https://arxiv.org/abs/2305.12086

Medema, E. (2023). A Comprehensive Framework for the Development of Ethical Machine Learning in Medicine. Proceedings of the Canadian Conference on Artificial Intelligence. https://doi.org/10.21428/594757db.166dda67

2022

Ferguson, V. (August 2022) Race, Racism, and Sickle Cell Disease: Where it Began and Where it Ends. The Red Blood Cell Disorders hub. https://www.rbcd.ca/blog/race-racism-and-sickle-cell-disease-where-it-began-and-where-it-ends

Stinson, C (2022). Algorithms are not Neutral: Bias in Collaborative Filtering. AI and Ethics. https://link.springer.com/epdf/10.1007/s43681-022-00136-w 

Robertson, J., C. Stinson & T. Hu. (2022). A Bio-Inspired Framework for Machine Bias Interpretation. In Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society, AIES ’22. 588598. https://dl.acm.org/doi/abs/10.1145/3514094.3534126 

Neophytou, N., B. Mitra & C. Stinson. (2022). Revisiting Popularity and Demographic Biases. In Recommender Evaluation and Effectiveness. In Advances in Information Retrieval. ECIR 2022. Lecture Notes in Computer Science 13185. Springer. https://doi.org/10.1007/978-3-030-99736-6_43 

Li, X., Aitken, W., Zhu, X., & Thomas, S. W. (2022). Learning Better Intent Representations for Financial Open Intent Classification. arXiv preprint arXiv:2210.14304. https://arxiv.org/abs/2210.14304

2021

Stinson, C. (January 2021) The Dark Past of Algorithms That Associate Appearance and Criminality. American Scientist, 109:1(26). https://www.americanscientist.org/article/the-dark-past-of-algorithms-that-associate-appearance-and-criminality 

2020

Stinson, C., L. James, M. Abdalla, N. Moellers, S. Mosurinjohn, S. Phillips & A. Simpson. (November 2020) NDRIO: Limit Corporate Influence, Maximize Public Involvement and Accountability. New Digital Research Infrastructure Organizationhttps://alliancecan.ca/en/document/232 

Stinson, C. (2020) From Implausible Artificial Neurons to Idealized Cognitive Models: Rebooting Philosophy of Artificial Intelligence. Philosophy of Science. 87(4), 590–611. https://www.journals.uchicago.edu/doi/pdf/10.1086/709730

Stinson, C. (September 2020) Agency and Ethics in a Complex World. Future EDge, Issue 2. New South Wales Department of Education. https://education.nsw.gov.au/content/dam/main-education/teaching-and-learning/education-for-a-changing-world/media/documents/FutureEdge-Issue2.pdf 

Stinson, C. (May 2020) Algorithms Associating Appearance and Criminality Have a Dark Past. Aeonhttps://aeon.co/ideas/algorithms-associating-appearance-and-criminality-have-a-dark-past