Integrating Generative AI in Dental Education: What We Found

 

Artificial intelligence is increasingly part of dental education, but how are universities addressing its use? Together with Ilze Maldupa and Falk Schwendicke, we conducted a scoping review to answer this question. Our paper, published in the European Journal of Dental Education, examines existing guidelines from universities and organizations on using generative AI (GenAI) in dental education.

We reviewed documents from 21 universities across 15 countries and three international organizations, looking for recommendations on how academic staff should approach AI in teaching and learning. While institutions recognize the potential of GenAI tools like ChatGPT for personalizing education, improving content creation, and fostering critical thinking, challenges remain. Academic integrity, ethical concerns, and the absence of clear, dental-specific guidance stand out as major gaps.

One of our key findings was that, despite the widespread interest in AI, no dental schools had published formal guidelines specific to dentistry. Instead, most policies were general, addressing education as a whole. Universities emphasized ethical AI use, transparency, and maintaining academic integrity, but clear strategies tailored to dental education were missing. This highlights an opportunity for dental institutions to establish best practices suited to their specific needs.

Our review emphasises the need for structured, discipline-specific guidelines that help educators integrate GenAI responsibly. Specifically, we mean it should contain examples; for instance, rather than certain students must use these in an ethical way these tools, there should be clear definitions about what is allowed and what is not. Rather than seeing AI as a challenge, dental schools should consider how it can enhance learning while mitigating risks.

Our paper is open access in the European Journal of Dental Education here: LINK TO FULL TEXT. 

The conversation on AI in education is just beginning, and we hope this work contributes to a more informed, evidence-based approach.