McMahon, Aisling and Buyx, Alena and Prainsack, Barbara (2019) Big Data Governance needs more collective responsibility: The role of harm mitigation in the governance of data use in medicine and beyond. Medical Law Review. pp. 1-28. ISSN 0967-0742

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Abstract

Harms arising from digital data use in the big data context are often systemic and cannot always be captured by linear cause and effect. Individual data subjects and third parties can bear the main downstream costs arising from increasingly complex forms of data uses—without being able to trace the exact data flows. Because current regulatory frameworks do not adequately address this situation, we propose a move towards harm mitigation tools to complement existing legal remedies. In this article, we make a normative and practical case for why individuals should be offered support in such contexts and how harm mitigation tools can achieve this. We put forward the idea of ‘Harm Mitigation Bodies’ (HMBs), which people could turn to when they feel they were harmed by data use but do not qualify for legal remedies, or where existing legal remedies do not address their specific circumstances. HMBs would help to obtain a better understanding of the nature, severity, and frequency of harms occurring from both lawful and unlawful data use, and they could also provide financial support in some cases. We set out the role and form of these HMBs for the first time in this article.

Item Type:	Article
Keywords:	Big Data; Biomedical data; Collective responsibility and oversight; Data governance; GDPR; Harm mitigation;
Academic Unit:	Faculty of Social Sciences > Law
Item ID:	11637
Identification Number:	https://doi.org/10.1093/medlaw/fwz016
Depositing User:	Aisling McMahon
Date Deposited:	05 Nov 2019 16:39
Journal or Publication Title:	Medical Law Review
Publisher:	Oxford University Press
Refereed:	Yes
URI:	Publisher
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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