Privacy Trading in the Surveillance Capitalism Age Viewpoints on ‘Privacy-Preserving’ Societal Value Creation
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Privacy Trading in the Surveillance Capitalism Age Viewpoints on ‘Privacy-Preserving’ Societal Value Creation Ranjan Pal, Jon Crowcroft University of Cambridge [email protected],[email protected],[email protected] This article is an editorial note submitted to CCR. It has NOT been peer reviewed. The authors take full responsibility for this article’s technical content. Comments can be posted through CCR Online. ABSTRACT well as the state-of-the-art IoT/CPS systems. All this is made possi- In the modern era of the mobile apps (part of the era of surveil- ble through mobile apps (applications) that enable the functioning lance capitalism, a famously coined term by Shoshana Zuboff), huge of operations in this ecosystem. ln-app advertising is an essential quantities of data about individuals and their activities offer a wave part of this digital ecosystem of free mobile applications, where of opportunities for economic and societal value creation. How- the ecosystem entities comprise the consumers, consumer apps, ever, the current personal data ecosystem is mostly de-regulated, ad-networks, advertisers, and retailers (see Figure 1 for a simplified fragmented, and inefficient. On one hand, end-users are often not representation for the ad-network and advertisers case). In reality, able to control access (either technologically, by policy, or psycho- advertisers and retailers could be directly linked to the consumer logically) to their personal data which results in issues related to apps in sell-buy relationships. As a popular example, Evite.com privacy, personal data ownership, transparency, and value distri- may sell lists of their consumers attending a party in a given loca- bution. On the other hand, this puts the burden of managing and tion directly to advertisers. As another example, the gene testing protecting user data on profit-driven apps and ad-driven entities company 23andMe might sell their clientele information directly to (e.g., an ad-network) at a cost of trust and regulatory accountability. pharmaceutical companies in order for the latter to develop medical Data holders (e.g., apps) may hence take commercial advantage of drugs. As a social objective, a win-win situation among the entities the individuals’ inability to fully anticipate the potential uses of of this ecosystem is desired, where (a) the privacy preferences of their private information, with detrimental effects for social welfare. consumers can be preserved, (b) the free apps can display appropri- As steps to improve social welfare, we comment on the the existence ate targeted consumer ads [21], (c) the ad-networks can publish the and design of efficient consumer-data releasing ecosystems aimed right ads on their billboards, and (d) the advertisers can target as at achieving a maximum social welfare state amongst competing large as possible and more importantly the right set of consumers. data holders. In view of (a) the behavioral assumption that humans The basic requirement for this ‘win-win’ ecosystem to exist in the are ‘compromising’ beings, (b) privacy not being a well-boundaried first place, is the flow of personalized information from thecon- good, and (c) the practical inevitability of inappropriate data leakage sumer to the advertisers via the ad-networks for effective/profitable by data holders upstream in the supply-chain, we showcase the idea ad placements, that subsequently motivate the latter to collect per- of a regulated and radical privacy trading mechanism that preserves sonal data about consumers via apps. The vision and benefits for the heterogeneous privacy preservation constraints (at an aggregate such an ecosystem were laid down by a certain school of infor- consumer, i.e., app, level) upto certain compromise levels, and at mation economists [1][16], in favor of having increased aggregate the same time satisfying commercial requirements of agencies (e.g., societal welfare. More specifically, according to the authors in[1], advertising organizations) that collect and trade client data for in return for personal data, advertisers and marketers will benefit the purpose of behavioral advertising. More specifically, our idea the individuals through monetary compensation (e.g., discounts, merges supply function economics, introduced by Klemperer and Facebook Libre Coins) and intangible benefits (e.g., personalization Meyer, with differential privacy, that, together with their powerful and customization of information content), and price discrimina- theoretical properties, leads to a stable and efficient, i.e., a maximum tion. Furthermore, the authors state that the lack of use of personal social welfare, state, and that too in an algorithmically scalable data will lead to opportunity costs and market inefficiencies. To manner. As part of future research, we also discuss interesting this end, three important questions that draw our attention are: can additional techno-economic challenges related to realizing effective such an ecosystem exist in the digital society?; if yes, then how should privacy trading ecosystems. it be designed?; and what is the implication of such a design to policy, economic science, and technology? CCS CONCEPTS Organization of the Paper - In this note, we first provide arguments for the virtually inevitable need of such ecosystems, despite positive- • Security and Privacy; • Economics; minded barriers put in place to prevent commercial use of personal KEYWORDS data in practice (see Section 2). We then provide an overview of supply function economics as an appropriate tool, that when com- Privacy, Trading, Mobile Apps, Market, Ecosystem, Efficiency bined with differential privacy, can be used to design an ecosystem resulting in stable and efficient economic outcomes from privacy 1 INTRODUCTION trading (see Section 3). Finally, we also discuss interesting additional Mobile technology is a major driving force behind the modern digi- techno-economic challenges related to realizing effective privacy tal society including business small and large, personal lifestyles, as trading ecosystems in practice. ACM SIGCOMM Computer Communication Review Volume 49 Issue 3, July 2019 26 Auction Process risks in holding personal data (e.g., via penalty mechanisms en- Matching b/w CB DH AO1 1 1 Ad- DHs & AOs Network1 forced by GDPR), re-identification by data brokers of data through Consumer Base the connection of disparate datasets, finds an efficient market. This, AO2 despite a plethora of popular anonymization and aggregation tech- CB2 DH2 Ad- niques aimed to prevent personal data breach attempts. Thereby, - Network2 AO3 Data - it is fair to assume that, with a high likelihood, there would be an Holders - Benefit - - $$, Incentive - - $$ Advertising inevitable breach of personal consumer information in general to sat- - - - Organizations - - isfy the economics behind the working of the current ad ecosystem, - - 2 - thereby leading to failing of the privacy-preservation property . CBk-1 DHk-1 Ad- Networkn Some recent studies [17] have stacked up cases against behavioral AOm-1 advertising post GDPR, stating that advertising firms can make Data Release more revenues from traditional advertising channels such as TV CBk DHk AOm and newspapers, compared to online/mobile advertising. However, Applications E-commerce, Healthcare, Transportation, Energy, Smart Homes the firms under question in the studies are big popular ones like NYT, and the same ‘increased revenue’ reasoning cannot be said Figure 1: Illustration of Mobile In-App Ad Ecosystem to hold for small to medium sized firms who rely heavily on be- havioral advertising for generating revenues. Thus, in view of the above mentioned arguments, an ecosystem possessing all the de- 2 LIKELY INEVITABILITY OF DATA RELEASE sired properties (a) - (d) mentioned in Section 1, cannot exist in practice. Mathematically, even for a relaxed version of this ecosys- In this section, we state the likely inevitable need of data release tem, this has been proved by the authors in [19] - their main result ecosystems citing multiple reasons, despite positive-minded barri- being that the standard utilitarian social objective cannot be opti- ers put in place to prevent commercial use of personal data in prac- mized for the case when aggregate consumer privacy preferences, tice. This subsequently calls for putting privacy trading methodolo- represented via the popular differential privacy metric, are ideally gies in place as one possible direction to ensure improved economic homogeneous across the apps. welfare. As section organization, we first discuss the inevitability The Age and Rise Of Surveillance Capitalism - In her recent of data release frameworks in the presence of positive-minded bar- book [25], Shoshana Zuboff states with numerous real-life surveil- riers to commercial use of personal data, thereby paving the way lance examples. since the early 2000’s, of how our daily life ac- for trading of data (privacy). We then brief the reader about the tivities are all recorded, rendered as behavioral data, processed, two-decade old but a newly-coined term, ‘surveillance capitalism’, analysed, bought, bundled, and resold like sub-prime mortgages and how such a capitalism era we are in bolsters the inevitability in a behavioral futures market. The litany of appropriated expe- of data release. Further, we take a quick look into privacy issues riences is repeated so often and so extensively that we become that might arise in the presence of privacy trading itself. Finally, numb, forgetting that this