Research Accountability and Integrity for Sustainable Ethics in AI (R.A.I.S.E.): A Mixed-Methods Study of Faculty Practices and Institutional Responses - As artificial intelligence (AI) transforms research by accelerating data analysis, writing, and design, it also introduces urgent ethical challenges that threaten core principles of research integrity, particularly in authorship, transparency, disclosure, and fairness. Yet institutional policies and training often lag behind AI adoption, leaving faculty and administrators without clear guidance. This project proposes a mixed-methods empirical study to examine the ethical use of AI in academic research, with a focus on Research 1 (R1) universities. We will begin with a confidential online survey of R1 social science faculty (e.g., those engaged in behavioral research), using purposive sampling to assess AI usage patterns, perceived ethical concerns, and awareness of institutional or federal guidance. The second phase will involve in-depth interviews with research administrators, IRB personnel, and staff overseeing research misconduct cases to explore institutional policies, oversight practices, and responses to AI-related dilemmas. Data will be analyzed using latent class analysis and reflexive thematic analysis to identify trends, tensions, and policy gaps across individual and institutional contexts. Findings will inform the development of practical guidance and a pilot training module for integration into Responsible Conduct of Research (RCR) programs and faculty onboarding. Dissemination will include peer-reviewed publications, webinars, and an open-access digital toolkit. By addressing this rapidly evolving issue, the project advances ORI’s mission to strengthen institutional accountability, researcher awareness, and the integrity of federally funded research.
