Should Healthcare Students Be Familiar with AI?

Artificial intelligence (AI) has the potential to revolutionize healthcare and, thus, healthcare education with its increasing adoption in healthcare practices and technological innovations. In education, AI has the potential to provide personalized learning experiences and democratized access to education. However, integrating AI into health professions education raises concerns about ethics, rote and meaningful learning, quality, equity, and privacy.  

In discussions with our HPEd students and academic colleagues, we seem to be having the same conversation as new members jump into our conversation around student use of AI. This blog series aims to capture the conversational evolution of this topic in hopes that, upon reading it, our future conversations can build upon prior conversations.

The second point-counterpoint discussion on AI's potential benefits and challenges in health professions education is:

Should we tell students: “You should be familiar with AI” or “It is essential for you to know and understand AI”? 

Point: AI will be used in healthcare. Our students MUST understand and know AI.

AI is rapidly transforming the healthcare industry, making it essential for students in health professions to understand and master its applications. As AI becomes more integrated into healthcare systems—from diagnostics and treatment planning to patient monitoring—future healthcare professionals will need to be equipped with the knowledge and skills to use these tools effectively. It is no longer enough to rely on traditional care methods simply; AI is becoming a fundamental part of modern healthcare, and students must be prepared to navigate this evolving landscape.

While AI has long been used to analyze complex medical data, assist with imaging and diagnostics, and personalize treatment plans, these applications are distinct from generative AI. Although traditional AI remains prevalent and crucial in healthcare, the current growing excitement surrounds generative AI and large language models, which bring new possibilities. Health professions students who understand this newer form of AI will be better prepared to interpret AI-generated insights and make informed decisions, especially as generative AI adoption becomes more common in clinical and educational practices. This AI knowledge will enable them to collaborate with AI systems to enhance precision and efficiency in treatment, ultimately leading to improved patient outcomes. Without this knowledge, future healthcare providers may struggle to keep up with the technological advancements shaping their field.

Furthermore, understanding AI will allow students to evaluate the technology’s benefits and limitations critically. Not all AI systems are perfect, and some may come with biases or inaccuracies that could affect patient care. Healthcare professionals who are educated in AI will be better positioned to assess the reliability of AI tools and determine when and how to use them effectively. This ability to critically engage with AI and discern its pitfalls will be crucial as the healthcare field continues to innovate, ensuring that AI is used ethically and to benefit patients.

Ultimately, integrating AI education into health professions curricula is not just about keeping up with technological trends—it’s about empowering the next generation of healthcare professionals to provide the highest standard of care in a rapidly changing world. As AI becomes an indispensable tool in patient care, students who understand and can work with AI will be at the forefront of this transformation, ready to lead the healthcare industry into the future.

Counterpoint: No, we should not mandate that students learn about AI. Students should have the option to CHOOSE to understand it.

While integrating AI into curricula is vital, it comes with significant challenges due to the rapidly evolving nature of the field. AI technology advances swiftly, making it difficult for educational programs to remain current. As a result, students may be exposed to outdated information, miss out on the latest developments in AI, or become inundated with so much extra information beyond their usual course load. This creates a risk of preparing students for a version of the field that may be obsolete by the time they enter the workforce or sub-optimally prepared, limiting the long-term relevance of their education.

Another critical challenge in incorporating AI into education is the ethical concerns surrounding its use. AI raises complex issues related to bias, privacy, and job displacement, which require thoughtful exploration and discussion. Educators must carefully balance teaching AI’s technical aspects with understanding its societal impact. Without this, students may enter the workforce unaware of the ethical dilemmas AI presents, potentially contributing to its misuse or reinforcing existing inequalities. Additionally, in healthcare education and training, we need to respect the autonomy of adult learners who bring their own viewpoints and life experiences to this field of work.  

While AI holds enormous potential to revolutionize patient care, not all healthcare students will end up using AI in their professional lives. Mandating AI education for all students might not be the best approach for educational programs, especially when their career paths may not require AI expertise. The growing evolution of AI will undoubtedly create careers in these areas to partner with health professionals. Moreover, considering our social inequities, it might be a waste of resources because there are many healthcare settings—particularly in underserved or rural areas—where AI adoption is slow or may not happen for quite some time. These communities rely on healthcare providers who meet their immediate needs without the latest tech innovations. Requiring all students to master AI, regardless of whether they'll use it in these environments, may divert attention from other vital skills more relevant to their future work.

Moreover, AI's potential for misuse highlights the importance of teaching students about responsible AI practices. AI can be weaponized to spread misinformation, perpetuate biases, or be used for unethical purposes. Students must be educated not only on how to use AI but also on the importance of using it ethically and with a strong sense of accountability. Failing to do so could result in future professionals misapplying AI in ways that harm society, emphasizing the need for caution in AI education.

Potential Solutions

AI knowledge for health professions students is becoming more and more necessary. Balancing the need for familiarity with the importance of informed choice in learning about AI may be achieved by the following:

• Ethical and Responsible AI Education: Promote a culture of ethical awareness to prepare students for responsible AI use in healthcare. This can be achieved by developing and implementing ethical guidelines for AI in healthcare education to address concerns about bias, privacy, and quality. Another way could be through integrating discussions on the ethical implications of AI into existing health curricula and using case studies to highlight potential misuse and biases in AI systems.
• Providing an AI Foundations Course or weaving AI into all courses: Implement a required foundational course on AI for health professions students or weave it into each course, covering the basics of AI technologies, their applications in healthcare, and ethical considerations.
• Interdisciplinary Collaboration: Foster collaboration between educators, AI experts, and healthcare professionals to develop innovative and ethical AI-powered solutions and curricular integrations to ensure current and applicable content.  
• Human Oversight: Ensuring that AI systems are used under the supervision of human experts to maintain quality and address potential issues. Regularly evaluating the effectiveness and impact of AI in healthcare education to identify areas for improvement
• Flexible Learning Options: Offer a range of elective courses focused on AI, allowing students to choose their level of engagement and explore further learning à la carte. Tailor these courses to different interests, such as data analysis, AI ethics, or healthcare applications.