Forget the Hype, Let’s Focus on Smart Regulation of Real Artificial Intelligence
Joshua Tamayo-Sarver, MD, PhD, FACEP, FAMIA
I recently heard someone argue that AI should be regulated like we would regulate any other professional. I am the first to admit that I have developed a relationship with different tools over the years. As a family we often name our cars, with my sons naming their car “Umami” because the concept of umami escapes me. But I have not thought we should regulate a car like it was a person. I have thought we should regulate it like it was a car. Because, well, it is a car. Similarly, AI is a tool that does powerful math and turns inputs into, we hope, insightful outputs. But it is still a tool built for a specific use case.
The world is enamored with AI — its potential seems limitless, its power undeniable. However, in the realm of healthcare, this enthusiasm is often accompanied by a degree of fear and misunderstanding. We hear calls to regulate AI as if it were a sentient being, capable of independent thought and malicious intent. While ethical considerations are paramount, I believe this approach is misguided, fueled by hypothetical scenarios and fear of the unknown rather than real-world understanding.
Having spent years developing and deploying AI solutions in healthcare, I can attest that AI, in its current form, is far from the all-powerful, autonomous entity depicted in science fiction like Terminator’s “SkyNet.” It is a tool, a powerful one, but a tool nonetheless, reliant on human guidance and oversight.
The reality of AI in healthcare is both more mundane and more complex than many realize. It’s not about replacing human judgment, but augmenting it. It’s about sifting through vast amounts of data to identify patterns and insights that include a “clinical intelligence data layer” that can inform clinical decision-making. It’s about streamlining administrative tasks to free up healthcare professionals to focus on patient care.
However, implementing AI in healthcare is not without its challenges. One of the most significant hurdles is the gap between theoretical potential and practical implementation. Many well-intentioned initiatives fail because they don’t account for the realities of healthcare environments — the complexities of workflows, the nuances of patient care, and the (warranted) stringent requirements for security and compliance.
The Importance of Hands-On Experience
To truly harness the power of AI in healthcare, we need to move beyond theoretical discussions and get our hands dirty with real-world implementation. Only by doing so can we understand the true capabilities and limitations of AI in healthcare settings.
This hands-on approach allows us to:
- Identify actual use cases where AI can make a meaningful difference
- Understand the practical challenges of implementation
- Develop realistic expectations for AI performance
- Create effective strategies for integration with existing systems and workflows
The problem with getting real-world experience, is we need to ensure that we have appropriate policies, procedures, governance, and regulation so that real-world experience does not translate into real harm for real patients.
The Need for Targeted Regulation
The call for blanket regulation of AI in healthcare, while well-intentioned, may do more harm than good. AI is not a monolithic entity — it encompasses a wide range of technologies and applications, each with its own set of challenges and potential risks.
Instead of broad, one-size-fits-all regulations, we need:
- Use-case specific guidelines: Tailored approaches that address the unique challenges of different AI applications in healthcare.
- Risk-based regulation: More stringent oversight for high-risk applications, balanced with flexibility for lower-risk uses.
- Adaptive frameworks: Regulatory approaches that can evolve as AI technology advances and our understanding deepens.
This type of approach already exists within other areas like medical device development and FDA approval. The FDA has done an excellent job of both supporting and regulating AI regulation as described in JAMA. (Warraich et al., 2024) It can be done within Regulation of AI too!
Balancing Innovation and Responsibility
The path forward lies in striking a balance between fostering innovation and ensuring responsible development and deployment of AI in healthcare. This requires:
- Collaboration: Bringing together technologists, clinicians, ethicists, and regulators to develop comprehensive, practical guidelines — grounded in real-world experience with AI and healthcare technology development and deployment.
- Education: Ensuring that all stakeholders have a realistic understanding of AI’s capabilities and limitations.
- Transparency: Clear communication about how AI systems are developed, validated, and used in healthcare settings.
- Ongoing evaluation: Continuous monitoring and assessment of AI systems to ensure they perform as intended and do not introduce unintended biases or risks.
The Road Ahead
As we continue to explore the potential of AI in healthcare, it’s crucial that we ground our efforts in reality. We must move beyond the hype and fear-mongering to focus on practical, ethical, and effective implementation.
By fostering a culture of responsible innovation, we can harness the transformative power of AI to improve patient outcomes, enhance healthcare efficiency, and address some of the most pressing challenges in modern medicine. The future of AI in healthcare is not about replacing human expertise, but about empowering healthcare professionals with powerful tools to provide better, more personalized patient care.
The journey ahead is complex, but by approaching it with a combination of enthusiasm, caution, and hands-on experience, we can navigate the challenges and unlock the true potential of AI in healthcare. It’s time to bridge the gap between hype and reality, and in doing so, shape a future where AI serves as a powerful ally in our quest for better health outcomes for all. In the meantime, I will continue to struggle with understanding when I taste “umami.”
Warraich, H. J., Tazbaz, T., & Califf, R. M. (2024). FDA Perspective on the Regulation of Artificial Intelligence in Health Care and Biomedicine. JAMA. https://doi.org/10.1001/jama.2024.21451
