第一部分:概念框架

H. Nissenbaum
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引用次数: 0

摘要

这一部分首先考虑在隐私和保密背景下收集和使用大数据的现有法律约束。然后,它指出了当前法律环境中的差距,以及在设计一套既保护隐私又允许大数据带来潜在好处的连贯政策时存在的问题。出现了三个主题:在更广泛的隐私和大数据讨论中使用的概念需要更新;我们如何理解和评估侵犯隐私的危害需要更新;我们必须重新思考在大数据环境下管理隐私的既定方法。“大数据”的概念被解释为范式的变化,而不仅仅是技术的变化。这说明了本书这一部分的第一个中心主题。Barocas和Nissenbaum将大数据定义为一种“范式,而不是一种特定的技术”,而Strandburg区分了数据集合和已经“数据化”的数据集合,即“以一种计算上可操作的格式聚合”。她声称,这种数据化是提高隐私问题的关键一步,并且更需要一个连贯的数据获取监管结构。管理隐私的传统监管工具——通知和同意——未能提供一种可行的市场机制,允许某种形式的自我监管来管理行业数据收集。Strandburg阐明了当前工业环境中数据收集的法律限制和指导,包括1973年的公平信息实践原则(FIPPs),以及1970年的公平信用报告法(FCRA)和1974年的隐私法。Strandburg主张对大数据环境下的权衡进行更细致的评估,而不是对侵犯隐私的成本进行个性化评估。应当加强关于为监测目的收集私人数据的隐私法,特别是应当在数据化和作为提供服务的副产品收集的数据的重新用途之间作出实质性区分。此外,她建议对通知和同意的概念采取实质性的方法,特别是澄清它们对大型实体的含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PART I: CONCEPTUAL FRAMEWORK
This part begins by considering the existing legal constraints on the collection and use of big data in the privacy and confidentiality context. It then identifies gaps in the current legal landscape and issues in designing a coherent set of policies that both protect privacy and yet permit the potential benefits that come with big data. Three themes emerge: that the concepts used in the larger discussion of privacy and big data require updating; that how we understand and assess harms from privacy violations needs updating; and that we must rethink established approaches to managing privacy in the big data context. The notion of ‘big data’ is interpreted as a change in paradigm, rather than solely a change in technology. This illustrates the first central theme of this part of the book. Barocas and Nissenbaum define big data as a “paradigm, rather than a particular technology,” while Strandburg differentiates between collections of data, and collections of data that have been “datafied,” that is, “aggregated in a computationally manipulable format.” She claims that such datafication is a key step in heightening privacy concerns and creating a greater need for a coherent regulatory structure for data acquisition. Traditional regulatory tools for managing privacy – notice and consent – have failed to provide a viable market mechanism allowing a form of self-regulation governing industry data collection. Strandburg elucidates the current legal restrictions and guidance on data collection in the industrial setting, including the Fair Information Practice Principles (FIPPs) dating from 1973 and underlying the Fair Credit Reporting Act (FCRA) from 1970 and the Privacy Act from 1974. Strandburg advocates a more nuanced assessment of trade-offs in the big data context, moving away from individualized assessments of the costs of privacy violations. The privacy law governing the collection of private data for monitoring purposes should be strengthened, in particular, a substantive distinction should be made between datafication and the repurposing of data that was collected as a byproduct of providing services. Additionally, she suggests taking a substantive approach to the ideasofnotice andconsent inparticular to clarify their meaning for large entities.
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