LLMs as Research Tools: Applications and Evaluations in HCI Data Work
Marianne Aubin Le Quéré, Hope Schroeder, Casey Randazzo, Jie Gao, Ziv Epstein, Simon T. Perrault, David Mimno, Louise Barkhuus, Hanlin Li
Abstract
Large language models (LLMs) stand to reshape traditional methods of working with data. While LLMs unlock new and potentially useful ways of interfacing with data, their use in research processes requires methodological and critical evaluation. In this workshop, we seek to gather a community of HCI researchers interested in navigating the responsible integration of LLMs into data work: data collection, processing, and analysis. We aim to create an understanding of how LLMs are being used to work with data in HCI research, and document the early challenges and concerns that have arisen. Together, we will outline a research agenda on using LLMs as research tools to work with data by defining the open empirical and ethical evaluation questions and thus contribute to setting norms in the community. We believe CHI to be the ideal place to address these questions due to the methodologically diverse researcher attendees, the prevalence of HCI research on human interaction with new computing and data paradigms, and the community’s sense of ethics and care. Insights from this forum can contribute to other research communities grappling with related questions.