A University Framework for the Responsible use of Generative AI in Research
Shannon Smith, Melissa Tate, Keri Freeman, Anne Walsh, Brian Ballsun-Stanton, Mark Hooper, and Murray Lane

TL;DR
This paper presents a practical framework for universities to promote responsible use of generative AI in research, addressing regulatory challenges and supporting research integrity.
Contribution
It introduces a principles-based framework derived from Australian universities' experiences to guide responsible AI use in research settings.
Findings
Framework helps institutions develop policies and initiatives.
Guidance simplifies complex regulatory landscapes.
Supports research integrity and responsible AI adoption.
Abstract
Generative Artificial Intelligence (generative AI) poses both opportunities and risks for the integrity of research. Universities must guide researchers in using generative AI responsibly, and in navigating a complex regulatory landscape subject to rapid change. By drawing on the experiences of two Australian universities, we propose a framework to help institutions promote and facilitate the responsible use of generative AI. We provide guidance to help distil the diverse regulatory environment into a principles-based position statement. Further, we explain how a position statement can then serve as a foundation for initiatives in training, communications, infrastructure, and process change. Despite the growing body of literature about AI's impact on academic integrity for undergraduate students, there has been comparatively little attention on the impacts of generative AI for research…
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