How will generative AI affect qualitative research?

Recording of lecture by Dr. Trena Paulus for the University of Illinois-Chicago Department of Educational Psychology Speaker Series

Algorithmic Justice League

European AI Office

Data & Society

Fairlytrained.org

Anis & French (2023). Efficient, explicatory, and equitable: Why qualitative researchers should embrace AI, but cautiously. Business & Society 62(6), 1139-1144.

Ashwin, J., Chhabra, A., & Rao, V. (2023). Using Large Language Models for Qualitative Analysis can Introduce Serious Bias. World Bank Policy Research Working Paper 10597.

Atkinson, C.F. (2023). Cheap, quick and rigorous: Artificial intelligence and the systematic literature review. Social Science Computing Review, 1-18. https://doi.org/10.1177/08944393231196281

Attick, R. (2016). Intelligent things >> It’s all about machine learning.

Christou, P.A. (2024). Thematic analysis through artificial intelligence (AI.) The Qualitative Report 29(2), Article 13.

Christou, P.A. (2023). The use of artificial intelligence (AI) in qualitative research for theory development. The Qualitative Report 28(9), 2739-2755.

Chubb, L.A. (2023). Me and the machines: Possibilities and pitfalls of using artificial intelligence for qualitative data analysis. International Journal of Qualitative Methods 22(1-16).

Ciechanowski, L., Jemielniak, D., & Gloor, P.A. (2020). TUTORIAL: AI research without coding: The art of fighting without fighting: Data science for qualitative researchers. Journal of Business Research 117, 322-330.

Correia, A.P. (2024). Detecting AI-generated text: Are we looking at an infinity mirror of illusive control?

Davison, R.M., Chughtai, H., Nielsen, P., Marabelli, M., Iannacci, F., van Offenbeek, M., Tarafdar, M., Trenz, M., Techatassanasoontorn, A.A, Diaz Andrade, A., & Panteli, N. (2024). Editorial: The ethics of using generative AI for qualitative data analysis. Information Systems Journal, 1-7.

DePaoli, S. (2023). Performing an Inductive Thematic Analysis of Semi-Structured Interviews With a Large Language Model: An Exploration and Provocation on the Limits of the Approach. Social Science Computer Review, 1-23. DOI:10.1177/08944393231220483

Fostier, J., Leemans, E., Meeussen, L., Wulleman, A., Van Doren, S., De Coninck, D. & Toelen, J. (2024). Dialogues with AI: Comparing ChatGPT, Bard, and Human Participants’ Responses in In-Depth Interviews on Adolescent Health Care. Future (2), 30–45.

Gamieldien, Y., Case, J.M. & Katz, A. (2023). Advancing qualitative analysis: An exploration of the potentials of generative AI and NLP in thematic coding. Gamieldien, Yasir and Case, Jennifer M. and Katz, Andrew, Advancing Qualitative Analysis: An Exploration of the Potential of Generative AI and NLP in Thematic Coding (June 21, 2023). Available at SSRNhttp://dx.doi.org/10.2139/ssrn.4487768

Hamilton, L., Elliott, D., Quick. A., Smith, S. & Choplin, V. (2023). Exploring use of AI in qualitative analysis: A comparative study of guaranteed income data. International Journal of Qualitative Methods 22 1-13.

Head, C.B., Jasper, P., McConnachle, M., Raftree, L. & Higdon, G. (2023). Large language model applications for evaluation: Opportunities and ethical implications. New Directions in Evaluation, 33-46.

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Kolbert, E. (2024). The obscene energy demands of AI. The New Yorker.

Montrosse-Moorehead, B. (2023). Evaluation criteria for artificial intelligence. New Directions in Evaluation, 123-134.

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Parker, J.L., Richard, V.M & Becker, K., (2023). Flexibility & Iteration: Exploring the Potential of Large Language Models in Developing and Refining Interview Protocols. The Qualitative Report 28(9), 2772-2791.

Paulus, T. & Marone, V. (Conditional acceptance, March 2024). ‘In minutes instead of weeks’: Discourse dilemmas on AI for qualitative data analysis. Qualitative Inquiry.

Paulus & Lester (2022). Doing qualitative research in a digital world. Sage

Paulus, T.M., Lester, J.N., Britt, V. (2013). Constructing hopes and fears: A discourse analysis of introductory qualitative research texts. Qualitative Inquiry, 19(9), 637-649.

Paulus & Lester (2023). Digital qualitative research workflows: a reflexivity framework for technological consequences, International Journal of Social Research Methodology, DOI: 10.1080/13645579.2023.2237359

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Paulus, T., Woods, M., Atkins, D., & Macklin, R. (2017). The discourse of qualitative data analysis software (QDAS): Reporting practices of ATLAS.ti and NVivo users with implications for best practices .International Journal of Social Research Methodology 20(1), 35-47.

Silver, C. (2023). What’s a foot in the Qualitative AI Space?

Silver, C. (2024). Navigating the Intersection of Qualitative Analysis and Technology: Strategies Driving Tactics in the Age of AI.

Tai, R.H., Bentley, L.R., Xia, X., Sitt, J.M., Fankhauser, S.C., Chicas-Mosier, A.M. & Monteith, B.G. (2024). An examination of the use of large language models to aid analysis of textual data. International Journal of Qualitative Methods 23, 1-14.

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Turner (2024). Outsourcing decision-making: AI, ethics, and qualitative research.

Walsh, S. & Pallas-Brink, J. (2023). The ethnographer in the machine: Everyday experiences with AI-enabled data analysis. EPIC Proceedings 538-554.

Whitaker & Atkinson (2021). Reflexivity in social research. Palgrave Macmillan.

Wilson (2023). Computer does qual: Avoiding AI-overclaim and false equivalency.

Woolf, N. & Silver, C. (2018). The Five Level QDA Method.

Resources for keeping up with AI developments more generally

Thanks to Dr. Vittorio Marone for these suggestions

Matt Wolfe (market research)

https://www.youtube.com/@mreflow/videos

https://www.futuretools.io

https://futuretools.beehiiv.com/subscribe

Andy Stapleton (academic research) https://www.youtube.com/@DrAndyStapleton/videos

https://academiainsider.com/about-us/

https://andrewstapleton.com.au/newsletter

Ethan Mollick

Co-intelligence

One Useful Thing

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