Dr Laura Strumidlo, Associate Professor and Head of the Oxford School of Nursing and Midwifery at Oxford Brookes University, has been part of the Council of Deans of Health’s working group to develop Principles of Generative AI for healthcare education. In this blog she shares the perspectives of the OBU Health Science and Technology Faculty Service User and Caregiver Group on this work.

The future of healthcare education is evolving with the rise of Artificial Intelligence (AI), but as a recent consultative meeting showed, the human element must remain at its core. I recently met with seven members of the Oxford Brookes University Service User and Caregiver Group to gain their perspectives on a new set of principles developed by the Council of Deans of Health, Innovation and Pedagogy Special Interest Group, for using AI in healthcare education. Their insights, which included a valuable contribution from a retired software engineer, were both pragmatic and illuminating.

The group’s feedback can be summarised around several key themes:

• It’s About Empowerment, Not Plagiarism. The group was clear that AI can be a powerful tool for learning, but we need to define the line between empowering students and enabling them to plagiarise. We need to acknowledge that students will use these tools and focus on teaching them how to do so responsibly, whilst maintaining academic integrity. As one person explained “The danger is that our students rely too heavily on this tool and don’t have the experience to know when it goes wrong how to deal with it but more so, how to recognise it.  Dependency and total faith in a tool isn’t a substitute for personal experience.”
• Principles Need to Be Actionable. While high-level principles are a good starting point, the group stressed that real-world application requires more. They suggested that developing case studies would be a sensible way to show how these principles can be put into practice by staff and students on the ground. These examples need to be inclusive drawing from a diverse range of settings/services and involve service users. A focus on how service users themselves utilise AI information to manage their own health conditions would be particularly useful.
• Assessment Is Everything. We can’t talk about AI without talking about assessment. The group highlighted that new assessment strategies are fundamental to ensure students use AI to augment, rather than replace, their own learning and critical thinking. How to integrate the principle of sustainable assessments in an everchanging AI context needs much thought.
• Addressing the Access Gap. The issue of inequality came up, particularly concerning students who can afford next-level AI tools compared to those who can’t. The group’s pragmatic acceptance of this unequal playing field is a powerful call to action for universities to ensure equitable access. This is both ethically and fiscally challenging for HEI’s at this time.

Conclusion:

Ultimately, the group’s message was a resounding vote of confidence in AI, so long as it serves the interests of students and future patients. The core of their feedback was a call to move beyond a fear-based narrative and to instead focus on a balanced approach that uses AI to strengthen, not diminish, the human skills that are so vital to professional healthcare. The principles when used in conjunction with institutional guidance and real-life case studies showing the art of the possible can help all with the ethical use of AI in health care. This discussion replicated key themes within the CoDH development group and have been echoed in the wider sector by students and academics. Good to know we are all in this together! Indeed, as one participant explained.

“A balanced, thoughtful, ethical approach to AI is vital, with collaboration between institutions, students, and caregivers will ensure AI supports education and future patient care.”