它需要一个村庄:一个基于社区的参与式隐私设计框架

Darakhshan J. Mir, Yan Shvartzshnaider, Mark Latonero
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引用次数: 6

摘要

随着以数据为中心的技术越来越多地被考虑在社会环境中干预边缘化人群的生活,我们考虑设计范式来创建满足他们独特的隐私需求和要求的系统。被剥夺权利的人群通常会因隐私的丧失而遭受不同的伤害,但通常在制定此类干预的范围和性质,以及伴随的(隐性或显性)隐私政策和随之而来的工程过程方面的作用有限。这一差距可以通过在设计这些隐私政策时包括接收社区来解决。我们为以数据为中心的应用程序提出了一种参与式设计模型,其中隐私政策(规范)来自于社区在研究/设计过程中的参与。情境完整性的框架将隐私表述为对特定情境下信息流规范规则的尊重,这使得在拟议干预的背景下,社区能够很好地制定这些隐私规范。采用形式化逻辑,这些隐私规范可以用于设计能够根据协商规范调节信息流的系统[1]。这整个过程,我们称之为情境化参与式隐私设计,旨在授权社区协商和阐明他们的隐私规范,导致系统的发展,能够强制执行他们认为合乎道德的,情境化使用他们的数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
It Takes a Village: A Community Based Participatory Framework for Privacy Design
As data-centric technologies are increasingly being considered in social contexts that intervene in marginalized peoples' lives, we consider design paradigms to create systems that fulfill their unique privacy needs and requirements. Disempowered populations often experience disparate harms from the loss of privacy but, typically, have a limited role in formulating the scope and nature of such interventions, and accompanying (implicit or explicit) privacy policies and consequent engineering processes. This gap can be addressed by including recipient communities in designing these privacy policies. We propose a participatory design model for data-centric applications where privacy policies (norms) emerge out of participation of the community in the research/design process. The framework of Contextual Integrity which articulates privacy as respect for normative rules of information flow in specific contexts, lends itself well to enable a community-generated formulation of these privacy norms within the contexts of the proposed intervention. Employing formal logic, these privacy norms can then be used to engineer systems capable of regulating the flow of information as per the negotiated norms [1]. This entire process which we call Contextualized Participatory Privacy by Design, seeks to empower communities in negotiating and articulating their privacy norms, leading to the development of systems that are capable of enforcing what they deem as ethical, contextualized use of their data.
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