In the modern era of the mobile apps (part of the era of surveillance capitalism , a famously coined term by Shoshana Zuboff), huge quantities of data about individuals and their activities offer a wave of opportunities for economic and societal value creation. However, the current personal data ecosystem is mostly de-regulated, fragmented, and inefficient. On one hand, end-users are often not able to control access (either technologically, by policy, or psychologically) to their personal data which results in issues related to privacy, personal data ownership, transparency, and value distribution. On the other hand, this puts the burden of managing and protecting user data on profit-driven apps and ad-driven entities (e.g., an ad-network) at a cost of trust and regulatory accountability. Data holders (e.g., apps) may hence take commercial advantage of the individuals' inability to fully anticipate the potential uses of their private information, with detrimental effects for social welfare. As steps to improve social welfare, we comment on the the existence and design of efficient consumer-data releasing ecosystems aimed at achieving a maximum social welfare state amongst competing data holders. In view of (a) the behavioral assumption that humans are 'compromising' beings, (b) privacy not being a well-boundaried good, and (c) the practical inevitability of inappropriate data leakage by data holders upstream in the supply-chain, we showcase the idea of a regulated and radical privacy trading mechanism that preserves the heterogeneous privacy preservation constraints (at an aggregate consumer, i.e., app, level) upto certain compromise levels, and at the same time satisfying commercial requirements of agencies (e.g., advertising organizations) that collect and trade client data for the purpose of behavioral advertising. More specifically, our idea merges supply function economics , introduced by Klemperer and Meyer, with differential privacy, that, together with their powerful theoretical properties, leads to a stable and efficient, i.e., a maximum social welfare, state, and that too in an algorithmically scalable manner. As part of future research, we also discuss interesting additional techno-economic challenges related to realizing effective privacy trading ecosystems.

中文翻译：

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监控资本主义时代关于“保护隐私”的社会价值创造观点中的隐私交易

在移动应用程序的现代时代（部分时代监视资本主义，Shoshana Zuboff 创造的一个著名术语），关于个人及其活动的大量数据为经济和社会价值创造提供了一波机会。然而，当前的个人数据生态系统大多是去监管、碎片化和低效的。一方面，最终用户通常无法控制对其个人数据的访问（无论是技术上、政策上还是心理上），这会导致与隐私、个人数据所有权、透明度和价值分配相关的问题。另一方面，这将管理和保护用户数据的负担置于利润驱动的应用程序和广告驱动的实体（例如，广告网络）上，以牺牲信任和监管责任为代价。数据持有者（例如，应用程序）可能因此利用个人的商业利益 无法充分预测其私人信息的潜在用途，从而对社会福利产生不利影响。作为改善社会福利的步骤，我们评论了有效的消费者数据发布生态系统的存在和设计，旨在在竞争数据持有者之间实现最大的社会福利状态。鉴于 (a) 人类是“妥协”生物的行为假设，(b) 隐私不是一种界限分明的商品，以及 (c) 供应链上游数据持有者不当数据泄露的实际必然性，我们展示了一种受监管且激进的隐私交易机制的想法，该机制保留了 我们评论了有效的消费者数据发布生态系统的存在和设计，旨在在竞争数据持有者之间实现最大的社会福利状态。鉴于 (a) 人类是“妥协”生物的行为假设，(b) 隐私不是一种界限分明的商品，以及 (c) 供应链上游数据持有者不当数据泄露的实际必然性，我们展示了一种受监管且激进的隐私交易机制的想法，该机制保留了 我们评论了有效的消费者数据发布生态系统的存在和设计，旨在在竞争数据持有者之间实现最大的社会福利状态。鉴于 (a) 人类是“妥协”生物的行为假设，(b) 隐私不是一种界限分明的商品，以及 (c) 供应链上游数据持有者不当数据泄露的实际必然性，我们展示了一种受监管且激进的隐私交易机制的想法，该机制保留了异质隐私保护约束（在总体消费者，即应用程序级别）达到某些折衷级别，同时满足为行为广告目的收集和交易客户数据的机构（例如广告组织）的商业需求。更具体地说，我们的想法融合了供给函数经济学，由 Klemperer 和 Meyer 介绍，具有不同的隐私，连同其强大的理论特性，导致稳定和有效的，即最大的社会福利，状态，以及算法上可扩展的方式。作为未来研究的一部分，我们还将讨论与实现有效的隐私交易生态系统相关的其他有趣的技术经济挑战。