The AI for Qualitative Research workshop brings together four speakers to explore how artificial intelligence is reshaping qualitative research. As AI tools become more capable of interpreting language, images, and behavior, they offer new possibilities for analyzing complex social phenomena while also raising important methodological questions.
Presentations will highlight emerging pipelines, tools, and challenges in integrating AI with qualitative research. The event concludes with a networking lunch, offering participants a chance to connect with speakers and peers working at the intersection of AI, data science, and the social sciences.
This workshop is part of the DSI Computational & Quantitative Social Sciences (CQSS) initiative.
| November 20, 2025 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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9:30-9:50 |
Registration
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9:50-10:05 |
Qualitative Data Analysis After the Toronto Revolution Prof. Ethan Fosse Associate Director, UTSC, Data Sciences Institute Department of Sociology, University of Toronto Scarborough |
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10:05-10:30 |
Exploring the Collaboration between Artificial Intelligence and Human Intelligence in Qualitative Data Analysis Dr. Qin Liu Senior Research Associate, Institute for Studies in Transdisciplinary Engineering Education and Practice, Faculty of Applied Science & Engineering |
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10:30-10:55 |
Use of AI for Transforming Qualitative Data
Prof. Susan McCahan Associate Vice-President and Vice-Provost, Digital Strategies, University of Toronto Department of Mechanical and Industrial Engineering, Faculty of Applied Science & Engineering, University of Toronto |
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10:55-11:00 |
Break
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11:00-11:25 |
Ethical Considerations for Using Artificial Intelligence in Qualitative Research Dr. Jordan Joseph Wadden Clinical Ethicist, Centre for Clinical Ethics, Unity Health Toronto Assistant Professor (status), Department of Family and Community Medicine, Temerty Faculty of Medicine, University of Toronto |
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11:25 -12:20 |
Keynote: On Patterns, Edge Cases, and Scalable Interpretation: Pragmatic Uses of AI in Qualitative Research
Prof. Corey Abramson Associate Professor of Sociology, Rice University |
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12:20-12:30 |
Closing the Loop: Integrating AI into the Qualitative Research Journey Prof. Nicholas Spence Departments of Sociology and Health & Society, University of Toronto Scarborough |
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12:30-1:30 |
Networking Lunch |
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Corey M. Abramson
Associate Professor, Department of Sociology, Rice University
Professor Corey’s empirical research examines the connections between inequality, health, and culture over the life course. His methodological work integrates computational social science, AI, and traditional qualitative analysis in innovative ways, in order to address social science and policy questions.
His scholarly works have examined the connections between health and society using a variety of empirical methods including participant observation in urban communities and clinics, quantitative modeling of national health survey data, in-depth interviews with people diagnosed with terminal diseases, analyses of health narratives employing AI to visualize language patterns, and team-based mixed-method approaches.
Ethan Fosse
Associate Professor, Department of Sociology, University of Toronto Scarborough
Associate Director, UTSC, Data Sciences Institute
Professor Fosse’s research focuses on developing and applying computational and quantitative methods to study social change, inequality, and social connectedness. His work includes designing new techniques for cohort analysis, applying these methods to topics such as verbal ability, political identification, and social mobility, as well as advancing data-driven AI methods to address central questions in the social sciences. Prior to Toronto, he was a Postdoctoral Research Associate in the Departments of Sociology and Politics at Princeton University, where he developed and led a series of open-source data science and programming workshops.
Qin Lin
Senior Research Associate, Institute for Studies in Transdisciplinary Engineering Education and Practice, Faculty of Applied Science & Engineering, University of Toronto
Dr. Qin’s research includes examining the association between student experiences and competency development, students’ educational and career pathways, student data analytics, and evidence-based instructional strategies in engineering education. At ISTEP, Dr. Qin supports faculty members and students in conducting engineering education research. She earned her Ph.D. from the Ontario Institute for Studies in Education at the University of Toronto.
Susan McCahan
Associate Vice-President and Vice-Provost, Digital Strategies, and Provostial Advisor on AI, University of Toronto
Professor, Department of Mechanical and Industrial Engineering, Faculty of Applied Science & Engineering, University of Toronto
As Vice-Provost, Professor McCahan provides leadership in enterprise-level information technology services and systems, with a focus on supporting the university’s academic mission. She collaborates with the Chief Information Officer to lead strategic planning efforts, working closely with deans, vice-presidents, vice-provosts, and academic administrators.
Nicholas Spence
Departments of Sociology and Health & Society, University of Toronto Scarborough
Prof. Spence’s research focus is on social inequality and the multiple determinants of health and well-being, and computational and quantitative research methods. He is working on a variety of research topics, including the relationship between psychosocial exposures, stress, and health; health services and clinical research on obesity; political trust, national pride, and sense of belonging; and Indigenous health and well-being.
Jordan Joseph Wadden
Clinical Ethicist, Centre for Clinical Ethics, Unity Health Toronto
Assistant Professor (status), Department of Family and Community Medicine, Temerty Faculty of Medicine, University of Toronto
Dr. Wadden’s research primarily focuses on the implementation of ethical technology and machine learning in clinical settings. For his work on AI and patient consent, he recently received the Ethics of Artificial Intelligence Award from the 3rd International Conference on the Ethics of Artificial Intelligence.
