Die LTS LunchTimeSeries on Law, Technology and Society startet ins Wintersemester 2018/19!

Univ.-Prof. Dr. Iris Eisenberger, M.Sc. (LSE), Universität für Bodenkultur Wien, und Univ.-Prof. Dr. Konrad Lachmayer, Sigmund Freud Privatuniversität Wien, organisieren die erfolgreiche Vortragsreihe bereits das sechste Semester in Folge.

Im Wintersemester 2018/19 beginnt die Reihe am 12. Oktober mit einem Vortrag von Prof. Alain Strowel, University of Louvain (UCLouvain), zu dem Thema "From the Cloud to the Edge: New Ways for Data Appropriation". Die Ankündigung finden Sie hier.

Am 13. Dezember ist Prof. Joanna Bryson, University of Bath, zu Gast und hält einen Vortrag zu "Human control of machine intelligence". Die Ankündigung finden Sie hier.

Den dritten Vortrag hält Prof. Susanne Beck, LL.M. (LSE), Leibniz Universität Hannover. Sie spricht am 17. Dezember über "Strafbarkeit beim Einsatz autonomer Systeme - Neue Impulse für das Konzept der Fahrlässigkeit?". Die Ankündigung finden Sie hier.

Nach den Vorträgen laden wir zur öffentlichen Diskussion ein. In anglo-amerikanischer Tradition wird für Verpflegung gesorgt. Die Veranstaltung ist frei zugänglich; die Teilnahme ist kostenlos.

Wir ersuchen um Anmeldung unter law(at)boku.ac.at.

Das gesamte Programm als PDF finden Sie hier.

From the Cloud to the Edge: New Ways for Data Appropriation



“Data is the new oil. It must be collected, refined, and transmitted – preferably without being leaked.” With this analogy, Professor Alain Strowel set the stage for his talk “From the Cloud to the Edge: New Ways for Data Appropriation” on 19 October 2018 at the University of Natural Resources and Life Sciences, Vienna.

Whereas oil resources are shrinking, the amount of data in our world is enormous and growing larger every minute. One autonomous car, for example, generates up to 4,000 gigabytes of data per day.  How should we regulate the control of and the access to this valuable resource? Who should own it? How should it be saved? And should the legislator regulate it by law or leave it to private autonomy?

Big Data, from the cloud to the edge

Strowel started his lecture by briefly introducing the concept of Big Data as large amounts of data that are interpreted by data analysis tools designed to “cope with data abundance as opposed to data scarcity”.

(Big) data can be stored “in the cloud” or “on the edge”. Whereas data storage in the cloud stores data in a centralized way (e.g., on so-called “server-farms”), computing on the edge decentralises data, bringing processing power closer to the source of data. Strowel explained the tension between the two storage concepts by the examples of smart metering and autonomous cars. Efficient smart metering (e.g., for tracking household energy consumption) relies on a centralised treatment of data and on simple end-devices. Autonomous cars, however, require high local processing power, be-cause a short response time is crucial for the passenger’s safety. From a data protection perspective, diverging data storage designs (here: centralised cloud storage versus decentralised edge compu-ting) can have far-reaching legal consequences. For example, data breaches are more severe if they happen in centralised data silos. In contrast, the more complex the data collecting device on the edge is, the more privacy concerns arise for its user.

Data property and data appropriation

Among other data-related conflicts, the tension between the cloud and the edge can be described using Strowel’s “data appropriation triangle”. The three “corner-questions” of the data appropriation are: How much data regulation should be contractually modifiable? What needs to be laid down as binding law? And where are the limits of legal regulation – where is privacy by technological design necessary?

In other words, the triangle comprises three perspectives on data protection: property rights, contrac-tual means, and technological or practical measures.

Strowel subsequently focussed on the “property rights”- corner. According to Strowel, the data sub-ject’s rights, such as the right to data portability under Article 20 of the General Data Protection Regu-lation (GDPR),  are part of a property-characterised understanding of data. In this context, the audi-ence also discussed ways of categorising data. According to Strowel, the current EU legislation land-scape mostly distinguishes between confidential data and public data as well as personal data and non-personal data. However, Strowel is convinced that these categories are too broad and that we should be more precise with data distinction.

Types of data and data regulation in the EU

As an example of current developments in EU data legislation, Strowel picked the case of text and data mining (TDM) in light of the Draft Directive on copyright in the Digital Single Market.  TDM is the process of extracting data and patterns from large datasets. If applied to image recognition, this tool brings data “from the eye to the machine”.

Strowel argued that TDM should not be covered by copyright. For example, autonomous cars in Lon-don will usually create visual representations of the well-known red double-decker buses. Some imag-es with that motive are protected by copyright.  However, the car does not care whether it encounters a suitable motive for works of London-cliché photography. It merely recognises the bus as an object that is best not to be driven into.

Copyright law pursues the objective of protecting the exploitation of work in its capacity as a work. TDM, on the contrary, does not reproduce work “as a work” but only extracts selected data sets (size and position of the obstacle). Hence, TDM does not qualify as an exploitation of protected works.

Relevance of data regulation in today’s world

The subsequent group discussion covered a broad spectrum of topics, including the categorisation of data, the problems of overly complicated privacy guidelines, and the possibilities and limitations of models such as the data appropriation triangle. The lively discussion illustrated once more how relevant and how pressing the questions of data protection law are in today’s world.

Thomas Buocz/Katja Schirmer, October 2018


Der Bericht im PDF-Format ist hier verfügbar.

Human Control of Machine Intelligence

Human Control of Machine Intelligence

  • "Human control of machine intelligence", an LTS lecture by Professor Joanna Bryson (University of Bath)
  • 13 December 2018
  • 12:00 - 13:30
  • Guttenberghaus, Seminar Room SR 03, Ground Floor
    Feistmantelstraße 4, 1180 Wien
    University of Natural Resources and Life Sciences, Vienna (BOKU)

The lecture will be followed by an open discussion. In Anglo-American tradition, catering will be provided during the lecture. The event is open for everyone and participation is free of charge.

Please register until 10 December 2018 via law(at)boku.ac.at.

Although not a universally-held goal, maintaining human control of artificial intelligence is probably essential for society’s long-term stability. Fortunately, the legal and technological problems of maintaining control are actually fairly well understood and amenable to engineering. The real problem is establishing the social and political will for assigning and maintaining accountability for artefacts when these artefacts are generated or used. In this talk I will discuss why we should maintain not only control but responsibility for AI, whether we have control now, and what technological and regulatory steps we can take to improve the present situation for the benefit of the very long term.

Joanna J. Bryson is a transdisciplinary researcher on the structure and dynamics of human- and animal-like intelligence. Her research covering topics from artificial intelligence, through autonomy and robot ethics, and on to human cooperation has appeared in venues ranging from a reddit to Science. She holds degrees in Psychology from Chicago and Edinburgh, and Artificial Intelligence from Edinburgh and MIT. She has additional professional research experience from Princeton, Oxford, Harvard, and LEGO, and technical experience in Chicago's financial industry, and international management consultancy. Bryson is presently a Reader (associate professor) at the University of Bath.

You can find a PDF of the announcement here.

Strafbarkeit beim Einsatz autonomer Systeme – Neue Impulse für das Konzept der Fahrlässigkeit?

Strafbarkeit beim Einsatz autonomer Systeme – Neue Impulse für das Konzept der Fahrlässigkeit?

  • "Strafbarkeit beim Einsatz autonomer Systeme – Neue Impulse für das Konzept der Fahrlässigkeit?", eine LTS Vorlesung von Professor Dr. Susanne Beck (Leibniz Universität Hannover)
  • 17. Dezember 2018
  • 12:00 - 13:30
  • Oskar-Simony-Haus, Seminarraum SR 19/1, Dachgeschoß
    Peter-Jordan-Straße 65, 1180 Wien
    Universität für Bodenkultur Wien (BOKU)

Nach den Vorträgen laden wir zur öffentlichen Diskussion ein. In anglo-amerikanischer Tradition wird für Verpflegung gesorgt. Die Veranstaltung ist frei zugänglich; die Teilnahme ist kostenlos.

Wir ersuchen um Anmeldung bis 12. Dezember 2018 unter law(at)boku.ac.at.

Die zunehmende Autonomie von Maschinen stellt das Recht vor viele neue Herausforderungen. Die Entwicklung bringt bisher unbekannte Risiken mit sich. Die Entscheidung der Maschine im Einzelfall wird unvorhersehbar und unkontrollierbar. Im Nachhinein ist eine eindeutige Zurechnung eines schädigenden Ereignisses zu einem spezifischen Fehlverhalten selten möglich. All dies erschwert eine eindeutige Zuordnung im Bereich der Fahrlässigkeit und klare Festlegung von Verhaltensregeln. Aber passt das traditionelle Fahrlässigkeitskonzept überhaupt noch zu derart globalen, unvorhersehbaren technologischen Entwicklungen? Oder können diese Entwicklungen gerade dazu beitragen, althergebrachte und vielleicht veraltete Strukturen aufzubrechen und neue Lösungen zu entwickeln?

Susanne Beck, Master of Law (LSE), Promotion und Habilitation an der Universität Würzburg (2006 und 2013) ist seit 2013 Professorin für u.a. Strafrecht und Rechtsphilosophie an der Leibniz Universität Hannover. Seit über zehn Jahren befasst sie sich mit verschiedenen rechtlichen Fragen der Entwicklungen im Bereich Robotik und KI, auch als Mitglied bei acatech, der Plattform Lernende Systeme oder der Foundation for Responsible Robotics.

Die Ankündigung als PDF finden Sie hier.