数据信任:数据多于信任?数据主体的视角面临着日益严重的问题

Q1 Social Sciences
Christine Rinik
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引用次数: 7

摘要

最近的报告《英国人工智能产业的发展》(Hall, Wendy, and Jerome Pesenti. 2017, https://www.gov.uk/government/publications/growing-the-artificial-intelligence-industry-in-the-uk)建议使用“数据信任”来促进数据共享。虽然政府和企业都在关注他们促进数据共享的需要,但许多个人的观点是,太多的数据正在被共享。这个问题不仅关乎数据,也关乎权力。在处理与数据共享有关的问题时,个人通常没有发言权。当讨论数据治理时,监管机构可以引用“公共利益”,但个人的利益可能与公众的利益不同。本文考虑了数据主体在数据收集方面的地位,从而考虑到监控和数据化。数据信托的建议将考虑应用英国信托法的原则,以可能减轻大数据用户和个人数据主体之间的权力不平衡。最后,将探讨以集体诉讼的形式进行可行补救的可能性,这种形式可以在数据泄露事件中赋予数据主体一些集体权力。尽管监管机构努力保护个人数据,但公众对当前的数据共享系统缺乏信任。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data trusts: more data than trust? The perspective of the data subject in the face of a growing problem
ABSTRACT The recent report, Growing the Artificial Intelligence Industry in the UK (Hall, Wendy, and Jerome Pesenti. 2017, https://www.gov.uk/government/publications/growing-the-artificial-intelligence-industry-in-the-uk) suggests the use of a 'data trust' to facilitate data sharing. Whilst government and corporations are focusing on their need to facilitate data sharing, the perspective of many individuals is that too much data is being shared. The issue is not only about data, but about power. The individual does not often have a voice when issues relating to data sharing are tackled. Regulators can cite the ‘public interest’ when data governance is discussed, but the individual’s interests may diverge from that of the public. This paper considers the data subject's position with respect to data collection leading to considerations about surveillance and datafication. Proposals for data trusts will be considered applying principles of English trust law to possibly mitigate the imbalance of power between large data users and individual data subjects. Finally, the possibility of a workable remedy in the form of a class action lawsuit which could give the data subjects some collective power in the event of a data breach will be explored. Despite regulatory efforts to protect personal data, there is a lack of public trust in the current data sharing system.
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来源期刊
CiteScore
3.70
自引率
0.00%
发文量
25
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