会后派对:广告科技转向隐私的玩世不恭的辞职

IF 6.5 1区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
Lee McGuigan, Sarah Myers West, Ido Sivan-Sevilla, Patrick Parham
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引用次数: 1

摘要

数字广告和科技公司不得不屈从于新的隐私要求。他们正准备迎接一个第三方追踪将受到设计或法律限制的世界。数字辞职通常指的是企业如何在互联网用户中培养一种对隐私无能为力的感觉。我们的论文从另一个角度来看待这个问题:数字广告业如何应对日益突出的隐私问题?最近的发展迫使公司实施“保护隐私”的设计——或者至少承诺一些表面上的隐私。然而,该行业仍然依赖于数据流和识别手段来实现仍然期望的目标、测量和优化。我们的论文通过观察旨在复制现有功能同时保护用户“隐私”的系统来分析这种矛盾。我们称之为一种“玩世不恭的辞职”,并将其关键操作描述为:(a)消毒监视;(b)次之;(三)蓄意破坏。我们认为,这种对隐私要求的“玩世不恭的辞职”代表着政策的失败。在缺乏对数据资本主义潜在商业模式的决定性干预的情况下,公司提供的技术解决方案和自我监管似乎符合新的法律和规范,同时加强对数据驱动的个性化的承诺。这可能会使大型科技公司受益,因为它们对第一方数据的特权访问将使更多的公司依赖它们,而且在一个利用建模来弥补第三方数据和传统个人识别方法损失的世界里,它们的计算能力将更加有价值。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The after party: Cynical resignation in Adtech's pivot to privacy
Digital advertising and technology companies are resigned to a new privacy imperative. They are bracing for a world where third-party tracking will be restricted by design or by law. Digital resignation typically refers to how companies cultivate a sense of powerlessness about privacy among internet users. Our paper looks through this optic from the other end of the lens: How is the digital advertising industry coping with the increasing salience of privacy? Recent developments have forced companies to implement “privacy-preserving” designs—or at least promise some semblance of privacy. Yet, the industry remains dependent on flows of data and means of identification to enable still-desired targeting, measurement, and optimization. Our paper analyzes this contradiction by looking at systems that aim to replicate existing functionalities while protecting user “privacy.” We call this a form of “cynical resignation” and characterize its key maneuvers as follows: (a) sanitizing surveillance; (b) party-hopping; and (c) sabotage. We argue that this “cynical resignation” to a privacy imperative represents a policy failure. In the absence of decisive interventions into the underlying business models of data capitalism, companies offer techno-solutionism and self-regulations that seem to conform to new laws and norms while reinforcing commitments to data-driven personalization. This may benefit the largest tech companies, since their privileged access to first-party data will make more companies reliant on them, and their computational power will be even more valuable in a world where modeling is used to compensate for the loss of third-party data and traditional methods of personal identification.
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来源期刊
Big Data & Society
Big Data & Society SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
10.90
自引率
10.60%
发文量
59
审稿时长
11 weeks
期刊介绍: Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government. BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices. BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.
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