Studying People to Study AI: Expert Perspectives on the Epistemic Fit and Barriers of Human Research in AI Safety & Ethics
Jessica Y. Bo, Paula Akemi Aoyagui, Shalaleh Rismani, Dipto Das, Syed Ishtiaque Ahmed, Ashton Anderson
Why It Matters
What makes this one worth your time
Understanding and addressing the barriers to integrating human research in AI Safety & Ethics could lead to more comprehensive risk evaluations and ethical considerations in AI development.
The paper explores the undervaluation of human research in AI Safety & Ethics and proposes ways to enhance its epistemic fit.
Summary
The paper investigates the role and acceptance of human research in AI Safety & Ethics by conducting a survey and interviews with experts from various backgrounds. It identifies barriers to the adoption of human research, such as validity concerns and resource limitations, and suggests recommendations to improve its integration.
Key contributions
- Conducted an expert survey and interviews to assess the perception of human research in AI Safety & Ethics.
- Identified key barriers to the acceptance of human research in the field.
- Proposed recommendations to improve the integration of human research methods.
Notable insights
- Technical researchers show less appreciation for human research and interdisciplinary collaboration, indicating an epistemic tension.
- The paper highlights the need to avoid performative 'human-washing' in AI research.
Possible limitations
- Not stated in the abstract
Abstract
arXiv:2608.05656v1 Announce Type: cross Abstract: Safety risks of AI are becoming increasingly evident in human interactions with AI technologies. The prominent approaches to evaluating these risks favor technical methods, such as model benchmarks and LLM simulations, often sidelining empirical research with human subjects. To examine this apparent gap in the acceptance of human research, we conduct an expert survey (n=93) and expert interviews (n=17) with AI Safety & Ethics (AISE) researchers from Technical, Sociotechnical, Governance, and Normative backgrounds. Our findings suggest that although there is a consensus that human research is valuable for generating evidence for AISE, its adoption and acceptance are constrained by perceived validity issues, tangible resource barriers, epistemic and personal preferences in methods, and infrastructural constraints from the broader research community. In particular, Technical researchers tend to value human research less and collaborate across disciplines less, suggesting an epistemic tension towards human methods. We propose recommendations for establishing the epistemic fit of human research within AISE and bridging the prohibitive limitations that researchers face, while avoiding performative 'human-washing'.