Who Owns the Data?

The vision of computers simulating human intelligence has materialized in the form of artificial intelligence (AI) and machine learning, which affects many aspects of modern healthcare. The past two decades have seen a 25-fold increase in the volume of literature about AI in medicine, underscoring its profound implications for the field. These applications leverage diverse model architectures, from neural networks to large language models, but their effectiveness and continued growth are contingent on availability of high-quality data. This raises important ethical questions regarding data ownership and stewardship in healthcare. The following chapter explores these ethical dilemmas from different stakeholder perspectives, including patients, healthcare providers, and technology companies. As each group’s needs may be distinct, guidelines should emphasize transparency and accountability to minimize the misuse of healthcare data. Data security is paramount to maintaining public trust in the confidentiality of their information and should be as important for the sustained growth of AI in medicine as profitability or scalability. To balance these considerations, regulatory bodies must enforce operating requirements through the collaboration of researchers, the private sector, and policymakers. The utility of cloud-based storage in accommodating the expanding volume of healthcare data is also discussed. The collection of this data has significant implications for patient autonomy and informed consent. Data ownership in the age of AI is a complex matter that must balance access to healthcare data with security and privacy such that informed consent and confidentiality are preserved. Guidelines must help stakeholders traverse this evolving landscape. While AI offers tremendous potential for innovation in medicine, it also must operate within and be accountable to an established set of ethical standards to preserve the trust implicit in the patient-physician relationship.