A Human-Centric Perspective on Digital Consenting: The Case of GAFAM | SpringerLink
Skip to main content
Springer Nature Link
Log in

A Human-Centric Perspective on Digital Consenting: The Case of GAFAM

  • Conference paper
  • First Online:
Human Centred Intelligent Systems

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 189))

Abstract

According to different legal frameworks such as the European General Data Protection Regulation (GDPR), an end-user’s consent constitutes one of the well-known legal bases for personal data processing. However, research has indicated that the majority of end-users have difficulty making sense of what they are consenting to in the digital world. Moreover, it was demonstrated that marginalized people are confronted with even more difficulties dealing with their own digital privacy. In this paper, using an enactivist perspective in cognitive science, we develop a basic human-centric framework regarding digital consent. We argue the action of consenting is a sociocognitive action and includes cognitive, collective, and contextual aspects. Based on this theoretical framework, we present our qualitative evaluation of the practice of gaining consent conducted by the five big tech companies, i.e. Google, Amazon, Facebook, Apple, and Microsoft (GAFAM). The evaluation shows that these companies are lacking in their efforts to empower end-users by considering the human-centric aspects of the action of consenting. We use this approach to argue that the consent gaining mechanisms violate principles of fairness, accountability and transparency and suggest that our approach might even raise doubts regarding the lawfulness of the acquired consent–particularly considering the basic requirements of lawful consent within the legal framework of the GDPR.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 22879
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 28599
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
JPY 28599
Price includes VAT (Japan)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    To ensure the webpage was specifically designed to be compliant with the GDPR, we chose the local top-level domain of Austria where applicable. All consent forms mentioned the GDPR in one way or the other.

  2. 2.

    Firefox 68.0.1 and Chrome 76.0.3809, respectively.

  3. 3.

    Through third-party tool.

  4. 4.

    Including YouTube.

  5. 5.

    http://optout.aboutads.info/.

  6. 6.

    https://youradchoices.ca/.

  7. 7.

    http://www.youronlinechoices.eu/.

References

  1. Amazon.de: Advertising Preferences. https://www.amazon.de/adprefs?ref_=ya_d_l_advert_prefs (2019). Accessed 22 Aug 2019

  2. Microsoft account \(\vert \) Privacy. https://account.microsoft.com/privacy/ad-settings/ (2019). Accessed 23 Aug 2019

  3. Microsoft Privacy Statement—Microsoft privacy. https://privacy.microsoft.com/en-us/privacystatement (2019). Accessed 23 Aug 2019

  4. Acquisti, A.: Privacy in electronic commerce and the economics of immediate gratification. In: Proceedings of the 5th ACM Conference on Electronic Commerce, pp. 21–29. ACM (2004)

    Google Scholar 

  5. Allen, M., Friston, K.J.: From cognitivism to autopoiesis: towards a computational framework for the embodied mind. Synthese 195(6), 2459–2482 (2018)

    Article  Google Scholar 

  6. Alt, R., Human, S., Neumann, G.: End-user empowerment in the digital age. In: Proceedings of the 53rd Hawaii International Conference on System Sciences, pp. 4099–4101 (2020)

    Google Scholar 

  7. Anderson, R.J.: Representations and requirements—the value of ethnography in system design. Hum.-Comput. Interact. 9(2), 151–182 (1994). https://doi.org/10.1207/s15327051hci0902_1

    Article  Google Scholar 

  8. Aybar, K.O., Human, S., Gesenger, R.: Digital inequality: call for sociotechnical privacy management approaches. Workshop on Engineering Accountable Information Systems. European Conference on Information Systems—ECIS 2019 (2019)

    Google Scholar 

  9. Blackmon, M.H., Polson, P.G., Kitajima, M., Lewis, C.H.: Cognitive walkthrough for the web. CHI p. 463 (2002). https://doi.org/10.1145/503376.503459

  10. Bösch, C., Erb, B., Kargl, F., Kopp, H., Pfattheicher, S.: Tales from the dark side: privacy dark strategies and privacy dark patterns. Proc. Priv. Enhanc. Technol. 2016(4), 237–254 (2016). https://doi.org/10.1515/popets-2016-0038

    Article  Google Scholar 

  11. Boyd, D.: It’s Complicated: The Social Lives of Networked Teens. Yale University Press (2014)

    Google Scholar 

  12. Boyd, D., Marwick, A.: Social privacy in networked publics: teens attitudes, practices, and strategies. In: Decade in Internet Time: Symposium on the Dynamics of the Internet and Society. Oxford, UK (2011)

    Google Scholar 

  13. Busch, A.: Privacy, technology, and regulation: why one size is unlikely to fit all. Social Dimensions of Privacy: Interdisciplinary Perspectives, pp. 303–323. Cambridge University Press, Cambridge (2015)

    Google Scholar 

  14. Chromik, M., Eiband, M., Völkel, S.T., Buschek, D.: Dark Patterns of Explainability, Transparency, and User Control for Intelligent Systems. IUI Workshops, vol. 2327 (2019)

    Google Scholar 

  15. Clark, A.: Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behav. Brain Sci. 36(3), 181–204 (2013)

    Article  Google Scholar 

  16. Commission, E.: Special Eurobarometer 431: Data Protection (2015)

    Google Scholar 

  17. Das, S., Kramer, A.D., Dabbish, L.A., Hong, J.I.: The role of social influence in security feature adoption. In: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, pp. 1416–1426. ACM (2015)

    Google Scholar 

  18. Dourish, P.: Implications for design. In: The SIGCHI Conference, p. 541. ACM Press, New York, NY, USA (2006). https://doi.org/10.1145/1124772.1124855

  19. Emami Naeini, P., Degeling, M., Bauer, L., Chow, R., Cranor, L.F., Haghighat, M.R., Patterson, H.: The influence of friends and experts on privacy decision making in iot scenarios. In: Proceedings of the ACM on Human-Computer Interaction, vol. 2(CSCW), p. 48 (2018)

    Article  Google Scholar 

  20. EU: Regulation (EU) 2016/679 of the European Parliament and of the Council of 27 April 2016 on the protection of natural persons with regard to the processing of personal data and on the free movement of such data, and repealing. Off. J. European Union 1–88 (2016)

    Google Scholar 

  21. Fox, J.: The uncertain relationship between transparency and accountability. Dev. Pract. 17(4–5), 663–671 (2007). https://doi.org/10.1080/09614520701469955

    Article  Google Scholar 

  22. Granovetter, M.: Economic action and social structure: the problem of embeddedness. Am. J. Sociol. 91(3), 481–510 (1985)

    Article  Google Scholar 

  23. Gray, C.M., Kou, Y., Battles, B., Hoggatt, J., Toombs, A.L.: The dark (patterns) side of UX design. In: Proceedings of the Conference on Human Factors in Computing Systems. Purdue University, West Lafayette, United States (2018). https://doi.org/10.1145/3173574.3174108

  24. Greenberg, S., Boring, S., Vermeulen, J., Dostal, J.: Dark patterns in proxemic interactions—a critical perspective. In: Proceedings of the Conference on Designing Interactive Systems, pp. 523–532 (2014). https://doi.org/10.1145/2598510.2598541

  25. Huber, J., Payne, J.W., Puto, C.: Adding asymmetrically dominated alternatives: violations of regularity and the similarity hypothesis. J. Consum. Res. 9(1), 90–98 (1982)

    Article  Google Scholar 

  26. Human, S., Bidabadi, G., Peschl, M.F., Savenkov, V.: An enactive theory of need satisfaction. In: Müller, V.C. (ed.) Philosophy and Theory of Artificial Intelligence 2017, pp. 40–42. Springer International Publishing, Cham (2018)

    Chapter  Google Scholar 

  27. Human, S., Bidabadi, G., Savenkov, V.: Supporting pluralism by artificial intelligence: conceptualizing epistemic disagreements as digital artifacts. In: Müller, V.C. (ed.) Philosophy and Theory of Artificial Intelligence 2017. Springer, Cham (2018)

    Google Scholar 

  28. Human, S., Fahrenbach, F., Kragulj, F., Savenkov, V.: Ontology for representing human needs. In: Różewski, P., Lange, C. (eds.) Knowledge Engineering and Semantic Web, pp. 195–210. Springer International Publishing, Cham (2017)

    Chapter  Google Scholar 

  29. Human, S., Gsenger, R., Neumann, G.: End-user empowerment: an interdisciplinary perspective. Hawaii Int. Conf. Syst. Sci. 2020, 4102–4111 (2020)

    Google Scholar 

  30. Human, S., Neumann, G., Peschl, M.: [how] can pluralist approaches to computational cognitive modeling of human needs and values save our democracies? Intellectica 70, 165–180 (2019)

    Google Scholar 

  31. Human, S., Wagner, B.: Is informed consent enough? considering predictive approaches to privacy. In: CHI2018 Workshop on Exploring Individual Differences in Privacy. Montréal (2018)

    Google Scholar 

  32. Hutto, D.D.: Surfing uncertainty: prediction, action and the embodied mind, by andy clark, pp. xviii+ 401,£ 19.99 (hardback), 2016. Oxford University Press, New york (2018)

    Google Scholar 

  33. Kain, E.: Facebook Turned a Blind Eye to ‘Friendly Fraud’ as Kids Racked up Thousands on Games. Forbes (2019)

    Google Scholar 

  34. Kemper, J., Kolkman, D.: Transparent to whom? No algorithmic accountability without a critical audience. Inf. Commun. Soc. 1–16 (2018). https://doi.org/10.1080/1369118X.2018.1477967

    Article  Google Scholar 

  35. Kirchner, N., Human, S., Neumann, G.: Context-sensitivity of informed consent: the emergence of genetic data markets. Workshop on Engineering Accountable Information Systems. European Conference on Information Systems—ECIS 2019 (2019)

    Google Scholar 

  36. Kumaraguru, P., Cranor, L.F.: Priv. Indexes : A Surv. Westin’s Stud. (2005). https://doi.org/10.1184/R1/6625406.v1

    Article  Google Scholar 

  37. Lehtiniemi, T., Kortesniemi, Y.: Can the obstacles to privacy self-management be overcome? Exploring the consent intermediary approach. Big Data Soc. 4(2), 2053951717721,935 (2017)

    Article  Google Scholar 

  38. Lehtiniemi, T., Kortesniemi, Y.: Can the obstacles to privacy self-management be overcome? Exploring the consent intermediary approach. Big Data & Soc. 4(2), 205395171772,193 (2017). https://doi.org/10.1177/2053951717721935

    Article  Google Scholar 

  39. Lupton, D.: Personal data practices in the age of lively data. Digit. Sociol. 335–50 (2016)

    Google Scholar 

  40. Lyon, D.: Surveillance Capitalism, Surveillance Culture and Data Politics, pp. 1–15 (2018)

    Google Scholar 

  41. Madden, M.: Privacy, security, and digital inequality: how technology experiences and resources vary by socioeconomic status, race, and ethnicity. Data Soc. (2017)

    Google Scholar 

  42. Marwick, A., Fontaine, C., Boyd, D.: Nobody sees it, nobody gets mad: social media, privacy, and personal responsibility among low-ses youth. Soc. Media+ Soc. 3(2), 2056305117710,455 (2017)

    Article  Google Scholar 

  43. Marwick, A.E., Boyd, D.: Networked privacy: how teenagers negotiate context in social media. New Media Soc. 16(7), 1051–1067 (2014)

    Article  Google Scholar 

  44. Marwick, A.E., Boyd, D.: Privacy at the margins understanding privacy at the margins-introduction. Int. J. Commun. 12, 9 (2018)

    Google Scholar 

  45. Mathur, A., Acar, G., Friedman, M., Lucherini, E., Mayer, J., Chetty, M., Narayanan, A.: Dark patterns at scale—findings from a crawl of 11K shopping websites. CoRR 1907 (2019). arXiv:1907.07,032

  46. Obar, J.A., Oeldorf-Hirsch, A.: The biggest lie on the internet: ignoring the privacy policies and terms of service policies of social networking services. Inf. Commun. Soc. (2018)

    Google Scholar 

  47. Rudolph, M., Feth, D., Polst, S.: Why users ignore privacy policies–a survey and intention model for explaining user privacy behavior. In: International Conference on Human-Computer Interaction, pp. 587–598. Springer (2018)

    Google Scholar 

  48. Tene, O., Polonetsky, J.: A theory of creepy: technology, privacy and shifting social norms. Yale J. Law Technol. 16, 59 (2013)

    Google Scholar 

  49. Tidwell, J.: Designing interfaces. Patterns for Effective Interaction Design. O’Reilly Media, Inc. (2005)

    Google Scholar 

  50. Van Dijck, J., Poell, T., De Waal, M.: The Platform Society: Public Values in a Connective World. Oxford University Press (2018)

    Google Scholar 

  51. Varela, F.J., Thompson, E., Rosch, E.: The Embodied Mind: Cognitive Science and Human Experience. MIT Press (2017)

    Google Scholar 

  52. Zuboff, S.: The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. Profile Books (2019)

    Google Scholar 

Download references

Acknowledgments

This work is partially funded through the EXPEDiTE project (Grant 867559) by the Austrian Federal Ministry for Climate Action, Environment, Energy, Mobility, Innovation and Technology under the program “ICT of the Future” between September 2018 and February 2020. We would like to express our great appreciation for valuable criticism and ideas contributed by Gustaf Neumann, Seyedeh Anahit Kazzazi, Seyedeh Mandan Kazzazi, Stefano Rossetti, Kemal Ozan Aybar, Rita Gsenger, and Niklas Kirchner.

Author information

Authors and Affiliations

  1. Sustainable Computing Lab & Institute for Information Systems and New Media, Vienna University of Economics and Business (WU Wien), Vienna, Austria

    Soheil Human

  2. Centre for Informatics and Society, Vienna University of Technology (TU Wien), Vienna, Austria

    Florian Cech

Authors
  1. Soheil Human
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Florian Cech
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Soheil Human .

Editor information

Editors and Affiliations

  1. Faculty of Informatics, Reutlingen University, Reutlingen, Baden-Württemberg, Germany

    Alfred Zimmermann

  2. KES International and Bournemouth University, Shoreham-by-sea, UK

    Robert J. Howlett

  3. University of Technology Sydney, Sydney, NSW, Australia

    Lakhmi C. Jain

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Human, S., Cech, F. (2021). A Human-Centric Perspective on Digital Consenting: The Case of GAFAM. In: Zimmermann, A., Howlett, R., Jain, L. (eds) Human Centred Intelligent Systems. Smart Innovation, Systems and Technologies, vol 189. Springer, Singapore. https://doi.org/10.1007/978-981-15-5784-2_12

Download citation

Publish with us

Policies and ethics

Search

Navigation