How data on individuals are gathered, analyzed, and stored remains largely ungoverned at both domestic and global levels. We address the unique governance problem posed by digital data to provide a framework for understanding why data governance remains elusive. Data are easily transferable and replicable, making them a useful tool. But this characteristic creates massive governance problems for all of us who want to have some agency and choice over how (or if) our data are collected and used. Moreover, data are co-created: individuals are the object from which data are culled by an interested party. Yet, any data point has a marginal value of close to zero and thus individuals have little bargaining power when it comes to negotiating with data collectors. Relatedly, data follow the rule of winner take all—the parties that have the most can leverage that data for greater accuracy and utility, leading to natural oligopolies. Finally, data's value lies in combination with proprietary algorithms that analyze and predict the patterns. Given these characteristics, private governance solutions are ineffective. Public solutions will also likely be insufficient. The imbalance in market power between platforms that collect data and individuals will be reproduced in the political sphere. We conclude that some form of collective data governance is required. We examine the challenges to the data governance by looking a public effort, the EU's General Data Protection Regulation, a private effort, Apple's “privacy nutrition labels” in their App Store, and a collective effort, the First Nations Information Governance Centre in Canada.

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为什么有关人的数据如此难以管理

在国内和全球层面，个人数据的收集、分析和存储方式在很大程度上仍然不受监管。我们解决数字数据带来的独特治理问题，以提供一个框架来理解为什么数据治理仍然难以捉摸。数据易于传输和复制，使其成为有用的工具。但这一特征给我们所有人带来了巨大的治理问题，因为我们希望对如何（或是否）收集和使用我们的数据有一定的代理权和选择权。此外，数据是共同创建的：个人是相关方从中挑选数据的对象。然而，任何数据点的边际价值都接近于零，因此个人在与数据收集者谈判时几乎没有讨价还价的能力。与此相关的是，数据遵循赢者通吃的规则——拥有最多数据的各方可以利用这些数据来获得更高的准确性和实用性，从而导致自然的寡头垄断。最后，数据的价值在于与分析和预测模式的专有算法相结合。鉴于这些特征，私人治理解决方案是无效的。公共解决方案也可能不够。收集数据的平台与个人之间市场力量的不平衡将在政治领域重现。我们的结论是，需要某种形式的集体数据治理。我们通过公共努力、欧盟的《通用数据保护条例》、私人努力、苹果应用程序商店中的“隐私营养标签”以及集体努力（加拿大原住民信息治理中心）来研究数据治理面临的挑战。