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追踪数据在大学研究和服务中的社会许可路径。

Paths to social licence for tracking-data analytics in university research and services.

机构信息

Complex Human Data Hub, Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Victoria, Australia.

Melbourne School of Engineering, The University of Melbourne, Melbourne, Victoria, Australia.

出版信息

PLoS One. 2021 May 21;16(5):e0251964. doi: 10.1371/journal.pone.0251964. eCollection 2021.

Abstract

While tracking-data analytics can be a goldmine for institutions and companies, the inherent privacy concerns also form a legal, ethical and social minefield. We present a study that seeks to understand the extent and circumstances under which tracking-data analytics is undertaken with social licence-that is, with broad community acceptance beyond formal compliance with legal requirements. Taking a University campus environment as a case, we enquire about the social licence for Wi-Fi-based tracking-data analytics. Staff and student participants answered a questionnaire presenting hypothetical scenarios involving Wi-Fi tracking for university research and services. Our results present a Bayesian logistic mixed-effects regression of acceptability judgements as a function of participant ratings on 11 privacy dimensions. Results show widespread acceptance of tracking-data analytics on campus and suggest that trust, individual benefit, data sensitivity, risk of harm and institutional respect for privacy are the most predictive factors determining this acceptance judgement.

摘要

虽然跟踪数据分析对于机构和公司来说可能是一座金矿,但其中固有的隐私问题也构成了一个法律、伦理和社会的雷区。我们进行了一项研究,旨在了解在何种情况下,跟踪数据分析是在获得社会许可的情况下进行的,也就是说,除了正式遵守法律要求之外,还得到了广泛的社区认可。我们以大学校园环境为案例,探讨了基于 Wi-Fi 的跟踪数据分析的社会许可问题。员工和学生参与者回答了一份问卷,其中提出了涉及 Wi-Fi 跟踪用于大学研究和服务的假设情景。我们的结果呈现了一个贝叶斯逻辑混合效应回归模型,将可接受性判断作为参与者在 11 个隐私维度上的评分的函数。结果表明,校园内广泛接受跟踪数据分析,并表明信任、个人利益、数据敏感性、伤害风险和机构对隐私的尊重是决定这种接受判断的最具预测性的因素。

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