By 2023, 65% of the world’s population will have its personal information covered under modern privacy regulations, up from 10% today. More than 60 jurisdictions around the world have enacted or proposed postmodern privacy and data protection laws, following the introduction of the GDPR in 2018.
Privacy concerns are cropping up as companies feed more and more consumer and vendor data into advanced, AI-fuelled algorithms to create new bits of sensitive information, unbeknownst to affected consumers and employees. This means that AI may create personal data.
Digital data privacy is a rapidly evolving concept in health care. As electronic records have replaced paper charts, and with the rise of “Big Data” and artificial intelligence (AI), this issue has become increasingly important. Big Data has been defined by the three V’s: volume (large amounts of data), variety (data heterogeneity), and velocity (speed of access and analysis).1,2 Analyses of these large datasets have allowed for more powerful assessments of healthcare quality and efficiency with the goal of improving patient care.3 AI is a branch of applied computer science that uses computer algorithms to perform cognitive tasks that approximate human intelligence, such as clinical decision making.4 More specifically, deep learning, a subset of machine learning within the field of AI, has been particularly successful in training powerful algorithms for the classification of medical images and other high-dimensional data.5–9 Taken together, these approaches may offer many benefits for patients, including automated screening and triage of disease and treatment optimization. For example, AI-enabled screening of diseases such as diabetic retinopathy, retinopathy of prematurity, and glaucoma could improve early detection and treatment.5,10,11 Furthermore, AI has been used for future disease predictions, in areas ranging from acute kidney injury to age-related macular degeneration and diabetic retinopathy; in the future, such approaches could lead to better preventative strategies.12–15 The combination of Big Data and AI also offers many potential benefits for healthcare systems, including increased productivity with decreased costs, as well as reductions in medical error. New data privacy problems have arisen with the use of this technology, however, leading to concerns about the balance between innovation and privacy and the need for better data protection methods that can evolve along with Big Data and AI.