McMahon Aisling, Buyx Alena, Prainsack Barbara
Department of Law, Maynooth University, Maynooth, Ireland.
Institute of History and Ethics in Medicine, School of Medicine, Technische Universität München, Munich, Germany.
Med Law Rev. 2020 Feb 1;28(1):155-182. doi: 10.1093/medlaw/fwz016.
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.
在大数据背景下，数字数据使用所产生的危害往往具有系统性，并不总能通过线性的因果关系来把握。个体数据主体和第三方可能要承担日益复杂的数据使用形式所产生的主要下游成本，却无法追踪确切的数据流。由于当前的监管框架未能充分应对这种情况，我们建议转向危害减轻工具，以补充现有的法律补救措施。在本文中，我们从规范和实际的角度论证了为何在此类情况下应向个人提供支持，以及危害减轻工具如何能够做到这一点。我们提出了“危害减轻机构”（HMBs）的构想，当人们觉得自己因数据使用而受到伤害，但不符合法律补救条件，或者现有法律补救措施无法解决其具体情况时，可以求助于这些机构。危害减轻机构将有助于更好地了解合法和非法数据使用所造成危害的性质、严重程度和发生频率，在某些情况下还可以提供经济支持。在本文中，我们首次阐述了这些危害减轻机构的作用和形式。
