Ethics and Governance of Big Data in Health Research and Digital Health Applications

Abstract

The health sector is undergoing a digital revolution. Digital technologies monitor and capture data about people’s health and physiology. The widespread availability of digital technologies and powerful analytical tools - such as artificial intelligence (AI) algorithms – makes it possible to generate, store, share and analyze vast amounts of aggregated data – “big data”. Big data offers exciting opportunities to improve prevention, diagnostics and therapeutics. Despite its benefits however, big data and AI-enabled technologies come with a series of technical, legal and methodological challenges which have ethical implications including privacy, equity, fairness, accountability, risk assessment, and benefit distribution. Given these novel ethical implications, the existing ethical guidance and oversight mechanisms are inadequate to effectively regulate big data use and health technology development. The first part of this thesis aims to gain a deeper insight into the ethical implications of big data and AI-enabled technologies in the health sector – specifically in health research and digital health applications. This analysis informs the second part of the thesis, which aims to determine the current state of ethical oversight mechanisms in health research and health apps in respect to big data. This goal will be achieved by mapping gaps in the existing ethical guidelines to suggest key reforms and future recommendations. The findings of this thesis show that the ethical discourse is biased toward privacy and technical concerns, leaving other ethical considerations unexamined. This narrow perspective is also reflected in the lack of comprehensive governance and adequate oversight to ensure an ethically aligned use of data in health research and health app development. The focus on data security compliance may result in insufficient guidance for stakeholders to make ethical choices, and thus may cause individual and collective harms. To avoid this risk, this thesis recommends updating the existing data governance and oversight mechanisms, considering a more comprehensive and robust ethical approach, which promotes shared values beyond data protection. Furthermore, this thesis includes an ethical toolkit that can guide stakeholders toward the ethically aligned use of big data. Only within good and ethical governance, big data and AI will be able to unlock their full potential for benefit to the health sector.