AI & Data Significance 7/10

Patient Privacy in the Era of Medical Big Data and AI: Legal and Ethical Challenges

This Nature Medicine perspective outlines the privacy risks that accompany large-scale health data collection for AI development, covering consent frameworks, equity in data governance, algorithmic discrimination, and breach management. The authors argue that existing regulatory structures are inadequate for the scale and complexity of modern medical datasets, and propose updated frameworks that balance innovation with patient protection -- a critical consideration for any laboratory or diagnostic platform handling genomic and clinical data.

The original study

Privacy in the age of medical big data.

Authors
Price WN, Cohen IG
Journal
Nature medicine
Type
Journal Article, Review
PMID
30617331
Read the original study →

Original abstract

Big data has become the ubiquitous watch word of medical innovation. The rapid development of machine-learning techniques and artificial intelligence in particular has promised to revolutionize medical practice from the allocation of resources to the diagnosis of complex diseases. But with big data comes big risks and challenges, among them significant questions about patient privacy. Here, we outline the legal and ethical challenges big data brings to patient privacy. We discuss, among other topics, how best to conceive of health privacy; the importance of equity, consent, and patient governance in data collection; discrimination in data uses; and how to handle data breaches. We close by sketching possible ways forward for the regulatory system.