Description

Is it okay to use large language models in the research process? For what task, exactly, and to automate the task or to augment the researcher? In this episode, we try to explore whether and how LLMs could be used in five aspects of the research process – for paper writing, reviewing, data analysis, as a subject of research, or as a surrogate for research subjects. We also discuss whether they should be used at all, and what some long-term consequences could be of such a choice, and we develop a number of heuristic rules to help researcher make decisions about using LLMs for research.

Episode Reading List

• Kankanhalli, A. (2024). Peer Review in the Age of Generative AI. Journal of the Association for Information Systems, 25(1), 76-84.
• Yang, Y., Duan, H., Liu, J., & Tam, K. Y. (2024). LLM-Measure: Generating Valid, Consistent, and Reproducible Text-Based Measures for Social Science Research. arXiv preprint, https://arxiv.org/abs/2504.02234v1.
• Li, J., Larsen, K. R. T., & Abbasi, A. (2020). TheoryOn: A Design Framework and System for Unlocking Behavioral Knowledge Through Ontology Learning. MIS Quarterly, 44(4), 1733-1772.
• Larsen, K. R., Yan, S., & Lukyanenko, R. (2024). LLMs and Psychometrics: Global Construct Validity Integrating LLMs and Psychometrics. 45th International Conference on Information Systems, Bangkok, Thailand.
• Anthis, J. R., Liu, R., Richardson, S. M., Kozlowski, A. C., Koch, B., Evans, J., Brynjolfsson, E., & Bernstein, M. (2025). LLM Social Simulations Are a Promising Research Method. arXiv preprint, https://arxiv.org/abs/2504.02234.
• Abbasi, A., Somanchi, S., & Kelley, K. (2025). The Critical Challenge of using Large-scale Digital Experiment Platforms for Scientific Discovery. MIS Quarterly, 49(1), 1-28.