Legal Aspects of Big Data

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1 Big Data: Little Ethics? Legal Aspects of Big Data HWZ-Darden Conference 4 June 2015 Roland Mathys, LL.M. (LSE) Attorney at law / Partner

2 Agenda > Introduction > Fundamentals > Principles of data processing > Proportionality > Purpose limitation > Transparency > Accuracy > Failure of traditional approaches > Anonymization > Consent > Emergence of new approaches > Conclusion Legal Aspects of Big Data 4 June 2015 Page 2/15

3 #UBERDATA Rides of Glory (RoG) > A RoGer is anyone who takes a ride between 10pm and 4am, and then takes a second ride from within 1/10th of a mile of the previous night s drop-off point 4-6 hours later (enough for a quick night s sleep). > Big Data Analysis SF NY Boston Chicago DC Source: uber.com Legal Aspects of Big Data 4 June 2015 Page 3/15

4 Pizza Palace Source: https://www.aclu.org/ordering-pizza Legal Aspects of Big Data 4 June 2015 Page 4/15

5 Fundamentals of Data Protection > Data protection > Protection of a person s privacy when his or her data is processed > Privacy: Human, fundamental and constitutional right in many jurisdictions > Personal data > Information related to an identified or identifiable person > Person: Natural person and (in some jurisdictions) legal entities > Specific personal data > Sensitive personal data: E.g. related to race, origin, health, crimes > Personality profiles: Data collection permitting assessment of personality > Processing > Any operation with personal data, irrespective of the means applied and the procedure, and in particular the collection, storage, use, revision, disclosure, archiving or destruction of data > Virtually everything! Legal Aspects of Big Data 4 June 2015 Page 5/15

6 Principles of Data Processing (1) Lawfulness Accuracy Good Faith Transparency Proportionality Purpose Limitation Legal Aspects of Big Data 4 June 2015 Page 6/15

7 Principles of Data Processing (2) > Proportionality > Which data, how much data? > Whom to share with? > How long to keep it? > Purpose limitation: Processing purposes have to be > indicated at time of collection; > evident from the circumstances; or > based on statutory provision. > Transparency > If personal data is shared with third parties? > If personal data is anonymized and eventually re-identified? Legal Aspects of Big Data 4 June 2015 Page 7/15

8 Principles of Data Processing (3) > Accuracy > Big data analysis based on correlations, not causalities > Findings may be correct in many, but not in all cases: Joe Pyne, Moderator: You have long hair, so you are a girl? Frank Zappa, Musician: You have a wooden leg, so you are a table? Source: tvdays.com Source: ibigdan.livejournal.com Imagine you have no own car, you are regularly working during the night shift (from 11 pm to 5 am), and, for reasons unknown to you (and to your wife!), start to receive ads for escort services Legal Aspects of Big Data 4 June 2015 Page 8/15

9 Failure of Traditional Approaches Consent Right to Information, Access, Correction Anonymization Legal Aspects of Big Data 4 June 2015 Page 9/15

10 The Legend of Anonymization > What information do you need to identify 89% of U.S. citizens? > Birth date > Sex > Postal code > Anonymized Traffic Metering > Based on GPS data, collected from mobile devices > Swiss village with residents > Analysis Average Speed Sample Size Means of Transportation ~ 5 km/h Many Pedestrians km/h Many Cyclists ~ 50 km/h Many Motorists > 50 km/h Some Speeders 10 km/h 1 (!)??? Legal Aspects of Big Data 4 June 2015 Page 10/15

11 The Myth of Consent > For consent to be valid, it must be given > informed; > freely; > and in some cases express. > Informed consent > Do you know what you are consenting to? > Transparency? > Free consent > Take it or leave it! > Take it or pay for it! > Alternatives on the market? Source: facebook.com Legal Aspects of Big Data 4 June 2015 Page 11/15

12 So What? "You have zero privacy anyway Get over it!" Scott McNealy, Chairman Sun Microsystems (1999!) "Privacy no longer a social norm" Marc Zuckerberg, CEO Facebook (CNBC on 3 December 2009) "If you have something that you don t want anyone to know, maybe you shouldn t be doing it in the first place! " Eric Schmidt, CEO Google (The Guardian of 11 January 2010) Legal Aspects of Big Data 4 June 2015 Page 12/15

13 Emergence of New Approaches Data Ownership (Private, Public, Open) "Profiling" Restrictions Certification (PIA, Privacy by Design, Privacy by Default) New Balance between Benefits of Big Data and Data Protection Legal Aspects of Big Data 4 June 2015 Page 13/15

14 Conclusion > Data protection is still an issue in the big data era or even more! > Big data falls foul of many core principles of data protection. > Traditional approaches are not suitable to address big data issues. > New and innovative approaches will be paramount for effective data protection. > Data protection legislation needs evolution, but no revolution. > Legislative action alone won t solve the issue! Legal Aspects of Big Data 4 June 2015 Page 14/15

15 Thank you for your attention! Roland Mathys, LL.M. (LSE) Attorney at law / Partner Schellenberg Wittmer Ltd / Attorneys at Law Löwenstrasse 19 / P.O. Box 1876 / 8021 Zurich / Switzerland T / F ZURICH / GENEVA / SINGAPORE Legal Aspects of Big Data 4 June 2015 Page 15/15

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