{"id":581,"date":"2026-06-05T15:57:03","date_gmt":"2026-06-05T15:57:03","guid":{"rendered":"https:\/\/facultyhub.elsevier.com\/en\/?p=581"},"modified":"2026-06-05T19:54:05","modified_gmt":"2026-06-05T19:54:05","slug":"asclepio-ai-2025-keys-to-understanding-how-artificial-intelligence-will-transform-medical-education-and-clinical-practice","status":"publish","type":"post","link":"https:\/\/facultyhub.elsevier.com\/en\/asclepio-ai-2025-keys-to-understanding-how-artificial-intelligence-will-transform-medical-education-and-clinical-practice","title":{"rendered":"Asclepio AI 2025: Keys to Understanding How Artificial Intelligence Will Transform Medical Education and Clinical Practice"},"content":{"rendered":"\n

Asclepio AI 2025 (Milan, Italy)<\/em> took place in May, the first summit bringing together media and medical professionals to share reflections on professional ethics and new scenarios applied to digital medicine. During intense sessions (May 29-30), various international experts delved into the impact and role of artificial intelligence in health with an eye toward a sustainable future.<\/p>\n\n\n\n

This space allowed for exploring the opportunities and challenges of integrating AI into medicine, promoting ethical and responsible innovation that preserves fundamental human values. The congress featured David Game, SVP in Medical Education Partnerships at Elsevier, who sat down for an interview to share his vision on the role of AI in medical education and clinical practice.<\/p>\n\n\n\n

How do you imagine that artificial intelligence will improve the way we educate and train future healthcare professionals?<\/h2>\n\n\n\n

\u2013 David Game<\/strong>: I believe there are several ways in which this can help future clinicians, that is, today’s students. When thinking about teaching and learning, and the need for students to interact with a knowledgeable and expert peer in their learning process, one of the difficulties we constantly see is he availability of professors and the time they can devote to giving students thoughtful attention.<\/p>\n\n\n\n

Our research so far has shown us that, certainly, in part of this process \u2014like the Socratic questioning between an informed peer and a student\u2014 generative AI can do a very good job guiding students. It does not give them the answer, but rather guides them through the intellectual process to master a subject<\/strong>. We see this as a fantastic area where students can interact at any time, day or night, with an expert peer who understands their level, knows the learning objectives of the school they attend, and instead of simply giving them the answer, pushes them toward the correct answer. Therefore, we see this as a really important area where our generative AI can enhance the learning process by increasing that contact, which is currently very difficult to manage for both students and teachers.<\/p>\n\n\n\n

In addition, AI will be a critical tool that the clinicians of tomorrow will use as part of their medical practice<\/strong>. For example, at the point of care, AI can be a partner in diagnosis and treatment. Using AI tools at the point of care to explore different diagnostic and treatment options, clinicians can address the complexity of patients with multiple concurrent conditions and overlapping treatments. This complexity requires a simultaneous understanding of multiple aspects that may not be within a clinician’s specific specialty.<\/p>\n\n\n\n

Therefore, we see two great opportunities: one is the idea of the Socratic guide<\/strong>, that figure of an informed clinician or faculty member in your pocket, so to speak, whom you can ask whenever you have a doubt, trained and structured not simply to give answers to the students. The other exciting opportunity is the use of AI as a tool at the point of care for practicing clinicians<\/strong>.<\/p>\n\n\n\n

What are the biggest challenges and opportunities when it comes to scaling AI-driven medical knowledge in healthcare systems?<\/h2>\n\n\n\n

–David Game<\/strong>: This is a fantastic question because, in my opinion, we are at the very beginning of the beginning of how we are going to use AI. The way we use AI today in medical situations will be very different from how we will use it five years from now. We keep finding use cases and opportunities we didn’t know existed \u2014 ones we hadn’t considered as ways to apply this power and knowledge to solve problems.<\/p>\n\n\n\n

We see several challenges in scaling AI, from what I would call a pilot implementation with a handful of clinicians or students, to an implementation at the state, national, or municipal level. I see two key challenges. The first is hallucination<\/strong>. Hallucination will likely continue to be part of AI solutions, at least in the near future, as it is inherent to AI. We can do a lot to mitigate it, but it remains an aspect of this technology, and the more complex the diagnosis, the harder it is to detect hallucination. Basic hallucinations, like the absurd question ‘Should you use glue to stick the cheese to the pizza?’, are easy to detect. However, more complex hallucinations, where the questions and contexts are sophisticated, will be much harder to identify, and that will be a challenge.<\/p>\n\n\n\n

The second difficulty, which I feel especially in education, but also in clinical work, is the lack of repeatability<\/strong>. Every time you ask the AI a question, there is a chance that you will receive a different answer. In fact, there is a high probability, and I believe that in some situations this can be very difficult to manage.<\/p>\n\n\n\n

\n

\u201cOpportunities are, in my opinion, immeasurable, partly because, as I said, we are at the beginning of the beginning. So I look forward to discovering how we will use AI constructively in the next three, four, or five years, and I am sure there will be many excellent examples.\u201d<\/h2>\n\n\n\n

\u2013 David Game, SVP in Medical Education Partnerships at Elsevier<\/p>\n<\/section>\n\n\n\n

How can Elsevier support institutions like AsclepioAI that seek to connect research, clinical practice, and ethical innovation?<\/h2>\n\n\n\n

–David Game<\/strong>: To repeat what I have already said, anyone who thinks they have all the answers is undoubtedly deceiving themselves, because there are many ways to understand how AI works and many opportunities to collaborate and test those ideas. I think it is especially important, as you mentioned, to think about ethical innovation. Advancing in areas that are ethically grey carries very high risk<\/strong>.<\/p>\n\n\n\n

While everyone is moving at high speed, at Elsevier we are especially committed to advancing responsibly. We have our own responsible AI principles, designed firstly to create transparency and also to ensure ethical alignment. We could move faster, but by following these principles we are in a position where we try to safeguard trust, protect the data we use, make our work transparent, and be able to explain what we do. For this reason, I see that collaboration between us and organizations like yours is incredibly important. This technology is very powerful, but it requires multiple perspectives to ensure that we move in the right direction.<\/p>\n\n\n\n

If I could share one key idea with the next generation of medical professionals entering the AI era, what would it be?<\/h2>\n\n\n\n

–David Game<\/strong>: I think the most important idea here is that great doctors, all over the world, have compassion, empathy, and treat their patients as whole individuals<\/strong>. Although AI will provide opportunities to improve certain medical skills, in the end those core values are what make a great doctor. So, I think the crucial idea for me is that AI will be a powerful tool that we will want to use whenever it can produce better outcomes, but in the end, the relationship between the patient and the doctor is the essence of good medicine<\/strong>.<\/p>\n\n\n\n

When one thinks about their own treatment or the treatment of their loved ones, they want to know that they are being cared for by a compassionate, empathetic, and ethical person, who sees them not just as a set of conditions, but as a person with feelings about their own life and more. Therefore, AI is important, but all those qualities that have made great doctors for hundreds of years will, I believe, remain constant.<\/p>\n\n\n\n

Access the original interview on the Congress website:<\/em>\u00a0Interview | David Game SVP Global Product for Medical Education, Elsevier, Special guest of Asclepio AI \u2013 2025 | Milan \u2013 AsclepioAI<\/em><\/a><\/p>\n\n\n\n

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David Game<\/strong>, SVP in Medical Education Partnerships at Elsevier, has extensive experience in educational technology in the United Kingdom and North America; he has led the digital strategy for medical and nursing education since joining the company. In 2018, he launched ClinicalKey Student<\/strong> and has expanded his product portfolio in the following years. He currently leads the product strategy for the Global Medical Education group, which includes platforms such as ClinicalKey Student, Osmosis, and Complete Anatomy.<\/p>\n\n\n\n

Before his time at Elsevier, he managed the Mastering Physics<\/strong> program in North America at Pearson and worked at MIT, where he developed introductory materials for innovative science and engineering courses. In addition, he participated in a pioneering STEM project that integrated television with the Internet.<\/p>\n\n\n\n

His primary interest is in assessment within the learning process and on how to effectively integrate software into the tools used by students and teachers for complex subjects. Currently, he is very involved in exploring the role of Generative Artificial Intelligence<\/strong> (GAI) in medical education and leads initiatives to introduce AI tools in the training of future doctors and nurses.<\/p>\n<\/div>\n\n\n\n

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David Game<\/figcaption><\/figure>\n<\/div>\n<\/div>\n<\/section>\n","protected":false},"excerpt":{"rendered":"

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