Developing a Responsible Use of Generative AI Module for Researchers

Dr Shannon Taylor1

1The University of Sydney, Camperdown, Australia

Biography:

Shannon Taylor is a Research Data Consultant at The University of Sydney. Shannon engages with researchers, professional and faculty staff to assist with research data concerns. She also produces content and resources to provide uplift for researchers.

Abstract:

As generative AI tools become increasingly embedded in research workflows and innovative approaches, universities face growing pressure to support researchers in their ethical and responsible use of generative AI (Gen AI) tools. In response to rising uncertainty and numerous inquiries from researchers, a project was initiated to develop an interactive training module tailored specifically to the research community. The module focuses on responsible Gen AI use across disciplines, aiming to foster informed decision-making through a non-prescriptive, reflective approach rather than enforcing simple compliance.

To ensure the module was relevant and effective, a program of research and outreach was undertaken to explore existing AI use and perceptions. The objective was to strike a balance between highlighting opportunities and addressing risks. Stakeholder consultations and focus groups helped uncover knowledge gaps, areas of uncertainty, and real-world concerns. Researchers consistently expressed a need for practical, non-technical guidance to navigate legal, ethical, and reputational risks. Feedback was gathered through three iterative rounds involving both Higher Degree by Research students and academic staff.

Key outcomes of the project included not only the development of the training module, but also the creation of practical institutional resources and guidelines identified as necessary by participants.

This presentation will outline the development process, challenges, and strategies for creating effective, researcher-led training in response to emerging technologies. The model presented offers a framework that can be adapted by other institutions in similar contexts.

 

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