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"I'm categorizing LLM as a productivity tool": Examining ethics of LLM use in HCI research practices

Shivani Kapania, Ruiyi Wang, Toby Jia-Jun Li, Tianshi Li, Hong Shen

TL;DR

This study investigates how HCI researchers use large language models (LLMs) and how they address associated ethics. Using a sequential mixed-method design with a survey of 50 researchers and 16 in-depth interviews, it maps LLM use across the research workflow and identifies a gap between ethical awareness and action. Findings show widespread LLM deployment from ideation to writing, with concerns about privacy, authorship, bias, and environmental impact, yet many respondents engage in conditional or incomplete ethical handling due to the LLM supply chain and competing priorities. The paper discusses implications for IRB practices, informed consent, tooling to interrupt the supply chain, ethics education, and incentive reforms to foster responsible LLM use in HCI.

Abstract

Large language models are increasingly applied in real-world scenarios, including research and education. These models, however, come with well-known ethical issues, which may manifest in unexpected ways in human-computer interaction research due to the extensive engagement with human subjects. This paper reports on research practices related to LLM use, drawing on 16 semi-structured interviews and a survey conducted with 50 HCI researchers. We discuss the ways in which LLMs are already being utilized throughout the entire HCI research pipeline, from ideation to system development and paper writing. While researchers described nuanced understandings of ethical issues, they were rarely or only partially able to identify and address those ethical concerns in their own projects. This lack of action and reliance on workarounds was explained through the perceived lack of control and distributed responsibility in the LLM supply chain, the conditional nature of engaging with ethics, and competing priorities. Finally, we reflect on the implications of our findings and present opportunities to shape emerging norms of engaging with large language models in HCI research.

"I'm categorizing LLM as a productivity tool": Examining ethics of LLM use in HCI research practices

TL;DR

This study investigates how HCI researchers use large language models (LLMs) and how they address associated ethics. Using a sequential mixed-method design with a survey of 50 researchers and 16 in-depth interviews, it maps LLM use across the research workflow and identifies a gap between ethical awareness and action. Findings show widespread LLM deployment from ideation to writing, with concerns about privacy, authorship, bias, and environmental impact, yet many respondents engage in conditional or incomplete ethical handling due to the LLM supply chain and competing priorities. The paper discusses implications for IRB practices, informed consent, tooling to interrupt the supply chain, ethics education, and incentive reforms to foster responsible LLM use in HCI.

Abstract

Large language models are increasingly applied in real-world scenarios, including research and education. These models, however, come with well-known ethical issues, which may manifest in unexpected ways in human-computer interaction research due to the extensive engagement with human subjects. This paper reports on research practices related to LLM use, drawing on 16 semi-structured interviews and a survey conducted with 50 HCI researchers. We discuss the ways in which LLMs are already being utilized throughout the entire HCI research pipeline, from ideation to system development and paper writing. While researchers described nuanced understandings of ethical issues, they were rarely or only partially able to identify and address those ethical concerns in their own projects. This lack of action and reliance on workarounds was explained through the perceived lack of control and distributed responsibility in the LLM supply chain, the conditional nature of engaging with ethics, and competing priorities. Finally, we reflect on the implications of our findings and present opportunities to shape emerging norms of engaging with large language models in HCI research.
Paper Structure (24 sections, 1 figure, 1 table)

This paper contains 24 sections, 1 figure, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. The Use of LLMs in HCI Research
  4. Research Ethics in HCI
  5. Ethics of LLM use
  6. Methods
  7. Survey
  8. Interviews
  9. Findings
  10. Where do HCI researchers use LLMs in their everyday work?
  11. What are HCI researchers' ethical concerns with the use of LLMs?
  12. Harms of engaging with LLM outputs
  13. Threats to privacy of participant data
  14. Violations of intellectual integrity
  15. Overtrust and overreliance on LLMs
  16. ...and 9 more sections

Figures (1)

  • Figure 1: LLMs are used in various ways for ideation and project scoping, study design and execution, and analysis and paper writing. The figure illustrates a typical HCI study across our research participants. Not all HCI research projects would include all activities listed above (e.g., critical theoretical contributions).