Our members, Australia’s 39 comprehensive universities, are quickly adapting to the use of AI in teaching and learning and research. Our members have taken the approach that this rapidly evolving technology presents opportunities as well as risks, and that they are well positioned to ensure the tool is used appropriately by staff and students through internal policies and guidance.
Universities use a range of tools to enhance student learning, responding to their needs and to improve access, retention and application of knowledge. Generative AI is another tool that can be used to achieve these outcomes. However, as with other teaching and learning tools, academic integrity is at the heart of all teaching and learning activities. While innovation is key to responding to shifts in teaching and learning environments, these changes cannot replace human experiential activities, such as learning through work integrated learning programs, workshops, collaborative work, observation and creative performance, and debates – but they may have a role in such activities. As with other technological innovations, universities respond by updating curricula to emphasise new elements of learning while supporting the core functions of good teaching methods and opportunities for students.
Generative AI is both a stream of research itself and a technology development that has the potential to impact research activities across every discipline. AI can boost productivity, but it can also impinge on the protections that are currently in place to ensure research is of highest quality and integrity. AI might be used to improve efficiency through supporting Higher Degree Research (HDR) students conducting background research for a literature review or helping researchers writing grant applications. It may also make research more accessible through improving the readability of discipline-specific research output.
However, overreliance on AI in research also poses significant risks. While AI tools can make research tasks more efficient, HDR students still need to learn the value and integrity of producing their own knowledge and contributions. Data produced using AI tools can still be far from accurate, and there are significant concerns around data storage and leakage when using these platforms which students and researchers need to be aware of. The use of AI in research also raises questions around intellectual property and data ownership. Currently, Australian copyright legislation does not address copyright ownership of anything generated by AI.
UA believes that students, educators, research supervisors and collaborators must continue to engage with emerging technologies, such as generative AI, with an emphasis on developing the general capabilities and skills that foster their professional expertise, critical thinking, evaluation, and intellectual curiosity. While doing so, universities have a responsibility to ensure that generative AI is used in an ethical, transparent and professional way. The full extent of its impact on research and teaching is not yet known. As such, universities will continue to provide and update guidance on how to use the tools correctly without breaching research integrity and ethical standards.
As our knowledge of generative AI and its impact evolves, greater regulation may be appropriate. UA recommends that universities retain the autonomy to manage the opportunities and risks associated with generative AI within their own institutions. Coordination across the sector could be encouraged through the development of best practice guidance and sector-specific standards for the use of generative AI in academia. Importantly, students need to be educated in the practical and ethical implications of generative AI to be adequately prepared for the future workforce. Work to equip students with these skills is already underway across UA’s member institutions.
