Researchers examine the legal and ethical aspects of AI in radiology

Bart Custers and Eduard Fosch-Villaronga from eLaw–Center for Law and Digital Technologies have contributed a chapter to the volume “AI Implementation in Radiology: Challenges and Opportunities in Clinical Practice.”

Edited by Erik Ranschaert from the Department of Diagnostic Sciences at Ghent University, Mohammad H. Rezazade Mehrizi from the School of Business and Economics, Vrije Universiteit Amsterdam, Willem Grootjans from Department of Radiology, Leiden University Medical Center, and Tessa S. Cook from the Department of Radiology, Hospital of University of Pennsylvania, this interdisciplinary work gathers contributions from experts worldwide that describes change management in the context of implementing AI in medicine and radiology.

Why do many medical institutions struggle to use AI in their clinical practice? What are the essential steps for and before an effective implementation of AI in radiology workflow? How can AI implementation trigger enduring improvements in the clinical process? The book shows how change management is crucial to effectively introduce AI to medicine and radiology, transform health care delivery and ensure a smooth transition while maximizing the benefits of AI and minimizing potential disruptions.

Their chapter “Legal and Ethical Aspects of AI in Radiology” explains that developing, implementing, and deploying AI in radiology requires more than focusing on technological and medical aspects like functionality, effectiveness, and efficiency.

To ensure basic levels of user-friendliness, user acceptance, and public support, it is essential to consider legal and ethical aspects. Legal requirements are a conditio sine qua non: non-compliance with legal norms would constitute an illegal practice. Ethical norms may be softer but may need consideration in cases with no legal requirements or when legal requirements are unclear or insufficiently detailed.

The authors also discuss AI’s most relevant legal and ethical aspects in radiology. Legal aspects include safety, privacy, data protection, security, bias, and non-discrimination. Relevant ethical aspects include human dignity, autonomy, and accountability.

These lists are not exhaustive; other legal and ethical aspects may also be relevant depending on the context. Therefore, some approaches (most notably impact assessments and value-sensitive design) are examined to help identify legal and ethical aspects and consider them for AI in radiology.

Overall, the researchers from eLaw bridge the gap between legal and medical disciplines to ensure that AI technologies are implemented in a way that is legally sound, ethically responsible, and aligned with patient-centered care.

This interdisciplinary contribution showcases how integrating law, ethics, and technology can help overcome barriers to AI adoption, offering a pathway for innovation that meets both technical and human needs. This volume is a critical resource for stakeholders involved in the evolution of AI in clinical practice.