The Cost of Progress: Exploring Privacy Nightmares for AI in Precision Medicine

Abstract

Precision medicine is an innovative approach to healthcare that relies on the use of genomic data, electronic health records, and other types of medical data to develop personalized prevention, diagnosis, and treatment strategies for patients. The use of artificial intelligence (AI) in precision medicine has the potential to improve patient outcomes and reduce healthcare costs, but it also raises significant privacy concerns. This paper provides a comprehensive review of the privacy nightmares associated with the use of AI in precision medicine. We examine the potential risks and threats to patient privacy, including the use of personal data for unintended purposes, the risk of data breaches and hacking, and the potential for discrimination and bias. We also analyze the legal and ethical implications of using AI in precision medicine, including issues related to informed consent and data ownership. Our investigation highlights the need for strong data protection regulations and ethical frameworks to safeguard patient privacy in the age of AI in precision medicine. As the use of AI in precision medicine continues to expand, the paper presents a road for future directions for protecting patient privacy, including the use of privacy-preserving machine learning algorithms and the adoption of privacy-enhancing technologies.