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2018 | OriginalPaper | Buchkapitel

1. Setting the Stage

verfasst von : Aurelia Tamò-Larrieux

Erschienen in: Designing for Privacy and its Legal Framework

Verlag: Springer International Publishing

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Abstract

This chapter addresses the current state of privacy in the digital age and how it came to be. The focus rests predominantly on technical and economic issues, as they greatly influence the discourse on the “digital privacy challenge.” [The term digital privacy challenge is framed by Gasser, Schweizerischer Juristentag 2015, ZSR Band 134 II, pp. 339 et seqq, 2015. Note that other forces at play, such as societal and legal aspects, exist and will be discussed in Chap. 3 in particular. Cf. for a complete analysis of technological, economic, behavioral, and legal forces Gasser, Schweizerischer Juristentag 2015, ZSR Band 134 II, pp. 355 et seqq., 2015.] First, we describe the technical revolution, specifically the shift from big mainframe computers towards ever-smaller data processing devices. Second, we discuss how economic developments led to the emergence of new business models which use data as their new raw material. Both developments feed into each other and compound the other’s effect on the erosion of privacy. We then examine how the movement towards a digital environment raises issues with respect to privacy protection. Finally, we explore the regulatory developments which are a result of concerns over the loss of privacy in a digital ecosystem.

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Nächstes Kapitel Research Approach

Cf. Catuogno/Turchi, p. 205; Federrath/Pfitzmann, pp. 857-858; Floridi, pp. 6-12; Langheinrich, pp. 1-5; Mayer-Schönberger, delete, pp. 62 et seqq.; Purtova, p. 19; Webster et al., pp. 90-97; approximately every 1.5-2 years the progress in microelectronic leads to duplication of the performance ability of processors—for a fixed price. This rule is known as “Moore’s Law”, cf. Moore, pp. 114 et seqq.; Mattern, p. 3.

Druey defines data as a sub-unit of information (p. 20). Information entails two characteristics: first an information process, a prerequisite for information to originate, and second, a meaning, which requires specification or has to be interpreted, cf. Specht, p. 23 with further references. Information is not an objective value, but its interpretation depends on the perception of the recipient, cf. Druey, p. 356. Information yields an added value compared to the raw data, cf. Linde, p. 6; Druey, pp. 5 et seqq., pp. 25 et seqq. This resulting knowledge in turn yields power, cf. Pasquale, p. 3.

Mattern, p. 4; cf. also Federrath/Pfitzmann, pp. 857-858; the increased transferability of data has triggered the growth of transborder data flows, cf. Kuner, pp. 1 et seqq.

Cf. Cohen, p. 107; Froomkin, pp. 1476 et seqq.; Gasser, pp. 357-358; Langheinrich, pp. 39-40.

Cf. i.a. Langheinrich, pp. 3 et seqq.; Mayer-Schönberger, delete, pp. 62 et seqq.

Wiegerling, pp. 19-21; cf. on robots, Lutz/Tamò, p. 27 with reference to Bekey, p. 18.

Cf. Catuogno/Turchi, p. 205; Mattern, p. 11; Purtova, pp. 38-39; Thierer, p. 1, 7; Wiegerling, pp. 19-25; cf. also Tene, pp. 5-6 elaborating on RFID, smart grids, and robotics.

The attributes efficiency, convenience, and security distinctively influence the likelihood of the social adaption of technological trends, such as ubiquitous computing, Internet of Things, or big data analysis, cf. Langheinrich, pp. 5-6.

Quercia et al., p. 971 et seqq.

So-called “high-resolution management,” cf. Subirana/Sarma/Fleisch, pp. 8 et seqq.

Cf. i.a. Calo, pp. 1007 et seqq.; Langheinrich, pp. 37-39; Mayer-Schönberger/Cukier, pp. 91 et seqq.

Calo, pp. 1007 et seqq.; Purtova, pp. 33-35; Solove, Metaphors, pp. 1404 et seqq.; cf. also Zuiderveen Borgesius, Singling out, pp. 261 et seqq.

Kobsa, p. 629; Zarsky, pp. 17-26; cf. also Brown, unpaginated; Hildebrandt, pp. 17-30.; Solove, Metaphors, pp. 1404 et seqq.; van der Hof/Prins, pp. 112-115.

Zuiderveen Borgesius, Singling out, pp.256 et seqq.; Purtova, pp. 23-24; cf. also Simitis, pp. 513-515; Tene, pp. 2-3. Behavioral profiling is the study of patterns of behavior. Here the focus rests on the analysis of typical behavior(s) of data subjects and deviations from it. Cf. on the process of behavioral profiling also Canhoto/Backhouse, pp. 47-58; Solove, Metaphors, pp. 1404 et seqq.

In the literature, these trends are defined as either Ubiquitous Computing, Ambient Intelligence (AmI), Pervasive Computing, Augmented Reality (AR), or “onlife” (a term proposed by Floridi, pp. 43 et seq.). Cf. Floridi, pp. 43 et seqq.; Hildebrandt, p. 23; Mattern, pp. 11 et seqq.; Purtova, pp. 38-39; Thierer, p. 61; Wiegerling, pp. 19-25; Weiser, pp. 94-104.

Weiser envisioned the evolution towards ubiquitous computing, cf. Weiser, pp. 94 et seqq.; cf. also Burkert, Privacy, pp. 63-64; Floridi, pp. 6-12; Froomkin, pp. 1476 et seqq.; Langheinrich, pp. 1-5; Purtova, p. 19; Uteck, pp. 85-91; Webster et al., pp. 28-33.

Spiekermann, p. 268.

Cf. i.a. Calo, pp. 1007 et seqq.; Langheinrich, pp. 37-39; Mayer-Schönberger/Cukier, pp. 91 et seqq.

Cf. for historical analysis of Big Data, Ambrose, pp. 25 et seqq.; cf. also Floridi, pp. 13-17; Rubinstein, pp. 3-4; Shaw, pp. 30 et seqq.; Thierer, pp. 1 et seqq.; cf. also Opinion EDPS, 2014; PCAST Report, 2014; OECD, Digital Outlook, 2015, p. 246.

So-called “Garterns 3-Vs” first proposed in 2001 (cf. META Group (now Gartner), 2001); cf. also MGI Report, 2011; OECD, Digital Outlook, 2015, p. 246; Floridi, pp. 13-17 arguing that “big data” is wrongly linked to the idea of “information overload.” He argues that the exponential growth of data (i.e., our entrance in the age of the zattabyte and a “data-richer” world), must be welcomed as the way forward.

Cf. Ambrose, pp. 25 et seqq.; boyd/Crawford, pp. 662 et seqq.; Mayer-Schönberger/Cukier, pp. 104-110; Floridi, pp. 22-24 on the value of connectivity of computers; cf. also Opinion EDPS, 2014.

Mayer-Schönberger/Cukier, p. 152. With aggregated data, reidentification of anonymized data is often possible, cf. Ohm, pp. 1716 et seqq.; cf. also Kosinski/Stillwell/Graepel, unpaginated; Montjoye et al., pp. 536-539; Sweeny/Abu/Winn, p. 1 et seqq.

Cf. Mayer-Schönberger/Cukier, pp. 17 et seqq.; Zarsky, pp. 26-30; Economist Prediction, 2016.

Mayer-Schönberger/Cukier, p. 17. Probably a more realistic scenario than getting arrested is a scenario where algorithms determine whether an arrested criminal can be released on bail. Cf. Joseph, Citylab, 2016.

Tene/Polonetsky, pp. 243-251; cf. also Brynjolfsson/Hitt/Kim, unpaginated; Bygrave, pp. 98-99; Tene, pp. 5-7; Thierer, pp. 6 et seqq.; MGI Report, 2011; cf. also Kuner, pp. 102-105 on the benefits and risks of transborder data flow in particular.

Cf. e.g., on downsides of predictions through algorithms and their build in biases: Economist, Prediction, 2016; Crawford, NYT, 2016; Joseph, Citylab, 2016; Leigh, Guardian, 2016.

Bekey, pp. 17 et seqq.; Lutz/Tamò, pp. 27-28.

Mindell, pp. 191 et seqq.

Cf. on the topic of accountability of algorithms, Kroll et al.

Mayer-Schönberger/Cukier, p. 17.

boyd/Crawford, pp. 662 et seqq.; Mayer-Schönberger/Cukier, pp. 17 et seqq.; Rubinstein, pp. 4-5.

Tavani, pp. 139-140; Floridi, Ontological interpretation, pp. 185 et seqq., introducing the 2P2Q hypothesis, which focuses on issues affecting “processing, pace, quantity, and quality.”

Own framework, inspired by Birnhack, p. 80; Floridi, pp. 5-6; Purtova, pp. 43-53; Zarsky, pp. 17-32.

Cf. Bygrave, Data Privacy, pp. 9-11; Langheinrich, Privatsphäre, pp. 233 et seqq.; Mattern/Langheinrich, pp. 55 et seqq.; Wiegerling, fn. 8.

The subsumption in this book follows approaches taken by e.g., Solove, p. 101-170; Tavani, pp. 139-140; Floridi, Ontological interpretation, pp. 185-200 and his 2P2Q examination scheme. Cf. also Chap. 3.

Cf. Purtova, pp. 45-51; cf. also Chap. 3. This demand for untraceability and regaining control over the information that data collectors collect has materialized in the development of privacy-enhancing technologies, see Chaps. 2 and 4.

Eurobarometer 431, 2015, p. 6 and Eurobarometer 359, 2011, p. 1. The willingness of an individual to disclose such personal information depends on the information type. Cf. also Kobsa, pp. 633-634; Phelps/Nowak/Ferrell, pp. 27 et seqq.; for attitudes of US-Americans cf. PEW Cybersecurity Report, 2015.

Cf. in particular Eurobarometer 431, 2015, p. 6 and Eurobarometer 359, 2011, p. 1. By “control capabilities,” the ability to “exert influence over those who are the subjects of surveillance” is meant, cf. Bygrave, p. 100 (citation). Cf. also Lessig, Code 2, pp. 223 et seqq.; Zuboff, pp. 75 et seqq., who coined the term “surveillance capitalism.”

Schneier, Blog on Security: Public/Private Surveillance Partnership, 2013; cf. also Christle/Spieckermann, pp. 9 et seqq.; Zuboff, pp. 75 et seqq.

Barocas/Nissenbaum, unpaginated; Brunton/Nissenbaum, unpaginated; Cohen, Privacy, pp. 1904 et seqq.; Tene/Polonetsky, OBA, pp. 288 et seqq; van der Hof/Prins, p. 119 et seqq.; Zarsky, pp. 17-26; cf. also EC, Impact Assessment, 2012, pp. 21 et seqq. with reference to the Eurobarometer 359, 2011.

Cf. e.g., study on how mobile apps share personal data by Zang et al., unpaginated; cf. also Christle/Spieckermann, pp. 9 et seqq.

Cf. i.a. Brunton/Nissenbaum, unpaginated; Calo, pp. 999 et seqq.; Christle/Spieckermann, pp. 123 et seqq.; Hartzog, Blueprint, pp. 153 et seqq.; Searls, pp. 61 et seqq.; cf. also ENISA Report, 2014, p. 1.

Searls, p. 55; An example of a controversial change was Google’s 2012 privacy policy update for which it was fined, cf. CNIL, Deliberation No. 2013-420; cf. Chap. 7.

Acquisti/Grossklags, p. 365; Hermstrüwer, pp. 17 et seqq.; Reidenberg et al., pp. 83 et seqq.; WP29, Opinion on IoT, 2014, pp. 6-7.

Mayer-Schönberger/Cukier, pp. 17 et seqq.; Zarsky, pp. 26-30.

A term connoted by Mayer-Schönberger/Cukier, p. 178 and Pasquale’s “Black Box Society” book; cf. also Watson, unpaginated; Executive Office Report, 2016.

Cf. Bygrave, pp. 105-106 stating that the realization that much data hold by organizations was deficient was a catalyst for the emergence of data protection laws (cf. Chap. 5); cf. also Executive Office Report, 2016.

Commonly referred to are scenarios resembling the movie “Minority Report,” where artificial intelligence is used to prevent crimes (i.e., predict violent crimes and enforcing the law before the crime happens; cf. e.g., Economist, Prediction, 2016).

Bygrave, p. 104; cf. also Bygrave, Data Privacy, pp. 10-11.

van der Hof/Prins, p. 117.

Hildebrandt, Profiling, p. 306.

Note that the fear over the increased automatization of decision-making is not new. Already in 1992 the EC discussed the diminishing influence of data subjects with increased automatization. Cf. Bygrave, p. 96 with reference to EC, Amended proposal, 1992.

Cf. i.a. Mayer-Schönberger/Cukier, pp. 150 et seqq.; Pasquale, pp. 59 et seqq.

Cf. on online price discrimination IViR research paper by Zuiderveen Borgesius, Price Discrimination, pp. 3 et seqq.

Zuiderveen Borgesius, Price Discrimination, pp. 5-9; Lessig, Code 1, pp. 155-156; Lessig, Code 2, pp. 220-222; Schneier, pp. 108-113; cf. also Executive Office Report, 2015 and Executive Office Report, 2016.

Citron/Pasquale, pp. 8 et seqq.; Crawford/Schultz, pp. 99 et seqq.; Gürses, p. 45; Schneier, pp. 108 et seqq.

Zarsky, pp. 51-52 on the manipulation of interests and choices; cf. also Bygrave, p. 107; Bygrave, Data Privacy, pp. 10-11.

Lessig, Code 1, p. 154; Lessig, Code 2, p. 220.

Sunstein has coined the term “echo chamber,” cf. Sunstein, Echo Chambers, pp. 1 et seqq.; cf. also Pariser, pp. 47 et seqq.; Shapiro, pp. 113 et seqq.; Sunstein, pp. 46 et seqq; Tene/Polonetsky, p. 252.

Sunstein, pp. 25 et seqq. Sunstein argues that citizens should have a range of shared experiences, as those common experiences are necessary for addressing social issues and understanding one another, cf. in particular pp. 99 et seqq.

Cf. Cuijpers/Purtova/Kosta, p. 555 on the right to be forgotten as the inverse to the notion of “total recall” enabled through the “ever growing data storage and retrieval capacity of modern IT.”

Mayer-Schönberger, delete, p. 7, pp. 62 et seqq and pp. 97 et seqq. Cf. also Brown, unpaginated.

As elaborated upon by Mayer-Schönberger in his book “delete”.

Brunton/Nissenbaum, unpaginated; Christle/Spieckermann, pp. 123 et seqq.; ENISA Report, 2014, p. 1.

Brown/Marsden, pp. 50-53.

Burkert, Privacy, pp. 63-64.

Burkert, Changing Patterns, pp. 2-4.

Burkert, Changing Patterns, pp. 2-4; cf. also Rossnagel/Pfitzmann/Garstka, p. 22 on the revision of the German data protection legislation.

Cf. Chap. 5, Sect. 5.3; CJEU, C-131/12; Art. 17 GDPR.

Cf. Chap. 5, Sect. 5.2. The attitude of policymakers towards the use of technical tools has changed over the past decades. They have gradually embraced the notion that technology is part of the solution. The importance of technology for data protection has also been discussed by Bennett/Raab, p. 179; Brown/Marsden, p. 57, pp. 66-68, pp. 200-203; Leenes/Koops, Code, pp. 195 et seqq.; Leenes/Koops, pp. 329 et seqq.; Lessig, Code 2; Lessig, Code 1.

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Titel: Setting the Stage
verfasst von: Aurelia Tamò-Larrieux
Verlag: Springer International Publishing
Buch: Designing for Privacy and its Legal Framework
Print ISBN: 978-3-319-98623-4

Electronic ISBN: 978-3-319-98624-1

Copyright-Jahr: 2018
DOI: https://doi.org/10.1007/978-3-319-98624-1_1

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