Responsible AI in Academic Research: A Competency Framework for Research Training

2026/01/01 by Michael J. Zyphur · 1 voice

paper · pdf · doi:10.61700/t31oy23grr

openalex publication_date 2026/01/01 · openalex created_date 2026/07/01 · openalex updated_date 2026/07/02

Abstract

This report is written for senior university research leadership: Deputy Vice-Chancellors and Deputy Provosts of Research, Pro-Vice-Chancellors and Deputy Vice Presidents of Research, faculty Deans and Associate Deans of Research, Deans of Graduate Schools and Associate Deans of Research Training, higher-degrees and research-integrity committees, and the peak bodies that represent graduate students. Its purpose is to give that audience a shared, evidence-anchored vocabulary for benchmarking institutional readiness on responsible AI use in research and research training, and a maturity grid that translates the vocabulary into concrete decisions on policy, curriculum, infrastructure, and governance. The report is the global anchor of a planned regional series. The same five-dimension competency framework and the same four-level maturity grid will be re-populated in later companion reports for the US / Americas, the UK / Europe, and APAC ex Japan.

Discussions

• "Responsible AI in research is an obligation universities owe society"👇 Zyphur, M. J. (2026). Responsible AI in academic research: A competency framework for research training. Instats Policy Series [bsky, 1 points, 1 comments]

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