1.
Introduction ^
One top priority of the General Data Protection Regulation (GDPR) is empowering individuals (or data subjects) to be informed about and in control of the use of their personal data. In fact, the data-driven economy fosters unbalanced relations between the entities that gather and process personal information and the individuals who are often unaware of the extent and the significance of the processing.1 However, the principle of transparency2 mandates data controllers to disclose complete and accurate information3 about the modalities and purposes of their practices, and about data subjects’ rights. This information (usually contained in a privacy policy) is deemed necessary to allow data subjects to understand, give consent to, and, if necessary, challenge the operations carried out on their data.4 Transparency is also a critical element to increase individuals’ trust in the data controller and therefore willingness to provide personal information.5
However, privacy communication tends to be «too long, overly legalistic, uninformative and unhelpful».6 The complexity and the amount of information provided are so excessive that most of the time individuals do not read or understand the notices.7 To fulfill the legal requirement of mandated disclosure, instead of effectively informing individuals about the use of their data, such notices are usually written «by lawyers for lawyers». Traditionally, they tend to focus on content and precision, much less on the needs of the users: the people who are impacted by or need to work with the text – mostly non-lawyers.8
2.
Previous Privacy Design Pattern Work ^
3.
Our Exploratory Design Work to Identify Patterns ^
4.
Our Proposal for a Privacy Communication Design Pattern Library ^
The GDPR puts effective privacy information at the center of data controllers’ obligations, but our analysis shows that even the major players still rely on poor and inadequate communicative strategies. We propose a Privacy Design Pattern Library32 where mechanisms focusing on privacy communication that are being developed and experimented throughout the world can be collected, integrated, and discussed. The core of the library contains not only existing patterns, but also proposed patterns that we or other researchers have developed, together with information about context of use and concrete examples. We hope to engage the vibrant privacy community in this collective effort to produce and share reusable solutions that will make data subjects more aware about the use of their data and their rights, and at the same time will help data controllers to be as transparent as the GDPR mandates. The flaws of traditional privacy communication are well known and well documented. Solutions have been developed and experimented, but have not met widespread adoption: let’s change this. This paper is a first step towards this goal.
5.
References ^
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- 1 Danezis et al. 2014.
- 2 Under the GDPR, transparency becomes a fundamental aspect of the principles of lawfulness and fairness of the processing of personal data. See GDPR, Article 12, and Article 29 Data Protection Working Party 2017. See also European Commission 2017, Article 8.
- 3 The same applies to any communication addressed to data subjects, such as the communication of a personal data breach, see GDPR, Article 34.
- 4 Article 29 Data Protection Working Party 2017.
- 5 See, e.g. Taddei/Contena 2013, Wu et al. 2012.
- 6 Pedder 2016. See also ICO 2016.
- 7 See, e.g. Calo 2012, European Commission et al. 2015, Reidenberg et al. 2015, Solove 2013. For a discussion on mandated disclosure, not only confined to privacy, see Ben-Shahar/Schneider 2014.
- 8 End user license agreements, terms of service, and contract terms present similar shortcomings. See, e.g., Mahler 2013, Haapio 2013, Conboy 2014, Mitchell 2015 and 2017, Haapio/Barton 2017.
- 9 Article 29 Data Protection Working Party 2017, p. 6.
- 10 See GDPR, Articles 13 and 14.
- 11 Article 29 Data Protection Working Party 2017.
- 12 See, e.g., Hoepman 2014, Hagan 2016, Rossi/Palmirani 2017, Edwards/Abel 2014, Raskin 2009 and Lannerö 2013. See also good (and bad) examples of privacy notices available at the Information Commissioner’s Office (ICO) website at https://ico.org.uk/ (all Websites last accessed on 2 January 2018) under the sections Privacy Notices in Practice and Where should you deliver privacy information to individuals? ICO is the UK’s independent authority set up to uphold information rights in the public interest, promoting openness by public bodies and data privacy for individuals. – ICO 2016, the ICO code of practice, provides guidance to organizations on how to make privacy notices more engaging and effective for individuals while emphasizing the importance of greater choice and control over what is done with their data.
- 13 See, e.g., Alexander et al. 1977, Alexander 1979, Gamma et al. 1994, Tidwell 2014, Waller/Delin 2011, and Pan/Stolterman 2013. For a timeline capturing many of the key points in the history of design patterns (albeit not in information design or contract design), see Malone 2017.
- 14 For what concerns privacy and security design patterns, see, e.g. https://privacypatterns.eu, https://privacypatterns.org, Diamantopoulou et al. 2017, Doty/Gupta 2013, Graf et al.2010, Hoepman 2014, Romanosky et al. 2006.
- 15 Haapio/Hagan 2016.
- 16 Hagan 2017.
- 17 Haapio/Hagan 2016, Haapio/Passera (forthcoming), Waller et al. 2016.
- 18 See e.g. Raskin 2009, Holtz/Nocun/Hansen 2010, Moskowitz & Raskin 2011, HIIT 2016.
- 19 See Kelley et al. 2009.
- 20 See videos at LinkedIn (https://www.linkedin.com/legal/privacy-policy), the Guardian (https://www.theguardian.com/help/privacy-policy), and O2 (https://www.o2.co.uk/termsandconditions/privacy-policy). See also video on the GoAnimate website at ico.org.uk/PNvideo.
- 21 See the International Regulatory Strategy Group’s templated GDPR text, https://www.irsg.co.uk/resources-and-commentary/irsg-example-gdpr-ready-processor-terms/.
- 22 See company Zynga’s PrivacyVille game https://www.zynga.com/privacy/privacyville.
- 23 PrivacyPatterns.org and PrivacyPatterns.eu have assembled a mixture of engineering and design mechanisms to present privacy terms. The CommonTerms project proposes five big pattern categories to improve privacy communications, http://www.commonterms.net/conclusions/.
- 24 Schaub et al. 2015.
- 25 Romanosky et al. 2006.
- 26 Doty/Gupta 2013
- 27 Hagan et al. 2014.
- 28 Driscoll 2016.
- 29 Legal Design Lab 2017.
- 30 See the rankings https://www.alexa.com/siteinfo.
- 31 Contact Legal Design Lab for access to our analysis records and full list of sites, at mdhagan@stanford.edu.
- 32 http://www.legaltechdesign.com/communication-design/legal-design-pattern-libraries/privacy-design-pattern-library/; see also http://www.legaltechdesign.com/communication-design/legal-design-pattern-libraries/.