Jusletter IT

Big Data


Dear Readers,

The term «Big Data» as a keyword has been subject to constant change in the last years. Basically, it indicates amounts of data that are too big, too complex or changing too fast to be registered and evaluated with traditional methods, respectively by hand. Today, in addition technologies for the extraction of information are increasingly named big data. Data collections, ascertainments and evaluations entered almost every area of life, big data can take data from nearly all sources: electronic communication in private or on business, authorities, companies, hospitals, schools et cetera. Targets of heavy criticism are claims from industry and authorities for comprehensive access on private data. These claims are increasingly in conflict with personal rights.
 
More than 40 years ago, Stanley Kubrick showed in his movie «2001: A Space Odyssee» the computer of the future as an artificially intelligent – almost human – creature. Introductory to the topic «Big Data», Hanspeter Thür asks himself the following questions: Where are we today, 14 years after Kubricks deadline? Was this a realistic vision or did it remain an innocent science fiction? How significant is privacy in the era of Big Data?
 
Astrid Epiney disassembles the existing data privacy laws and concludes that the applicability of the Federal Act on Data Protection is afflicted with notably big insecurities due to the very nature of Big Data. She concludes that legislative action is required. Robert G. Briner even calls the data protection laws «toothless paper tigers», which are not capable to handle Big Data properly. He demands: Information as an economic value should have a proprietor who can dispose about it according to property law.
 
I myself ask the fundamental question: «What changes with Big Data?» What kind of value is created by Big Data? Which paradigm shifts, chimeras and illusions are we dealing with? And in which areas new needs for regulation may emerge?
 
Several contributions are dealing with re-identification of anonymised personal data respectively de-anonymisation. Whilst Michal Cichocki brings light into different data protection aspects of Big Data and gives a review on the data protection principles of perceptibility, appropriation, comparativeness and acceptance, Rolf H. Weber and Dominic Oertly concretely demand a cooperation of organisation,engineering and law to minimize risks in the processing of data. They recommend a stronger focus on risk orientation (depending on the area), plus limitations on the publishing of anonymised data, and improved transparency. These measures can contribute to the reduction of the information gap between professionals and normal people and may fortify informational integrity of the person affected.
 
Against this background, the creation of a consistent legal terminology as well as semantic and Meta structure are important, as Erich Schweighofer explains. In addition, for an appropriate use of data, there is a need of proportionate and purposeful networking that can not be personal. According to Erich Schweighofer, new identity systems, that permit a certain anonymisation within sufficient integration, are inevitable. Transparency is then no longer a fiction, but solvable in an equitable way to society – in the magical triangle of Big Data, Open Data and Data Protection.
 
Focusing on health data, Roland Mathys explains, which consequences result from the qualification as particularly sensitive personal data in the Big Data discussion. The area of data elevation and evaluation in the automobile industry as well as the ongoing fight about data sovereignty is analysed by Max von Schönfeld. Sabine Wieneroiter and Daniel Wieneroiter are dealing with data acquisition in schools, especially in E-Learning. On the one hand, this enables the providing of tailored teaching and learning contents, on the other hand privacy risks are created.
 
From Canada’s point of view, Ann Cavoukian, Michelle Chibba, Graham Williamson and Andrew Ferguson are investigating, how the upcoming attribute-based access control technology can assist in protecting against unauthorized access to personal data in a Big Data context. From the Czech perspective, Jakub Míšek detects snares in the converting of personal data and sees a collision between the current data protection frame and new technologies.

René Huber focuses on the Swiss cantons und asks in relation to the federation: Are the cantons allowed to participate in «Big Data»? Which legal frameworks are to be considered? And what about data protection in this case?

Finally, Klaus Mainzer shows the consequences of the calculation of the world: exponentially increasing computing capacity (Moore’s Law), exponentially increasing sensor numbers, exponentially increasing amounts of data et cetera.

And Dirk Helbing guides us from Big Data over Deep Learning and artificial intelligence to manipulative technology and – colourfully and complex – summarises the societal, economical, ethnic and legal challenges of the digital revolution.

In addition to the particular articles, for the first time in this issue presentations held on the Conference for Informatics and Law on 5 November 2014 on the topic of Big Data are published as podcasts in Jusletter IT:
 
  • Martin Dumermuth, Chancen und Risiken von Big Data (Podcast)
  • Erich Schweighofer, Die Transparenzfiktion in der Big Data Welt (Podcast)
  • Klaus Mainzer, Die Berechenbarkeit der Welt und ihre Folgen (Podcast)
  • Dirk Helbing, Gefahren von Big Data und Lösungsansätze (Podcast)
  • Maximilian Wolf, Big Data und innere Sicherheit: Grundrechtliche Rahmenbedingungen einer datenintensiven Sicherheitsarchitektur (Podcast)

In the future, such lectures will also be provided in Jusletter IT as podcasts. Additionally, you can already find further fascinating podcasts about data protection at podcasts.weblaw.ch/datenschutzforum.html.

I hope that we could contribute to the discussion about Big Data and wish you a enlightening reading, listening and watching with this issue of Jusletter IT.

Bern, in May 2015

Reinhard Riedl
Redaktion Jusletter IT 

    Big Data