Argyro P. Karanasiou

My Quantified Self, my FitBit and I

The rise of wearable tech, namely devices with sensors measuring the user’s daily activities and habits seems to be suggesting a paradox in the post-Snowden era: On one hand, it is generally accepted that unauthorised use, storage and processing of the user’s private data by the state directly clashes with our fundamental rights for privacy; on the other, the user seems to be keen on self-recording and storing one’s own data by willingly using sensors, enabling him to learn more about one’s habits, general health status or even personality. In the era of wearable tech we seem to be accepting that measuring data is not a privacy infringement but a self-surveillance exercise in a quest to get to know ourselves better, most acute to exercising one’s right to free expression. Yet, how is this addressed in legal terms? The focal point for this paper is to address the nascent phenomenon of users actively partaking in the QS movement by wilfully sharing health related datasets. Part 1 notes the transition from the “right to be let alone” to the right to own one’s data as the underlying rational for QS: is it a form of expression regarding a tradable commodity in a free market or a matter of greater public importance? Part 2 dissects the dilemma in sharing health data for public health and/or research purposes exceeding the strict limits of private sphere. The unfortunate case of Google Health, the unconstitutional purchase of Iceland’s national datasets by deCODE and the mishap of the Care.data are studied to shed light to the many faces of our Quantified Selves: Is the current legislative approach fit for facilitating the QS movement, as a type of self-expression? The paper critically examines self-measurement technologies from a legal perspective and calls for urgent reforms in self-measured data protection.

The changing face of protests in the digital age: on occupying cyberspace and Distributed-Denial-of-Services DDoS attacks

On 7th January 2013 the Anonymous hacking collective launched a White House petition asking the Obama administration to recognize DDoS1 attacks as a valid form of protest, similar to the Occupy protests. The ‘Occupy’ movement against financial inequality has become an international protest phenomenon stirring up the debate on the legal responses to acts of civil disobedience. At the same time, online attacks in the form of DDoS are considered by many as the digital counterparts of protesting. While the law generally acknowledges a certain level of protection for protesting as a manifestation of the rights to free speech and free assembly, it is still unclear whether DDoS attacks could qualify as free speech. This paper examines the analogies between offline protests and DDoS attacks, discusses legal responses in both cases and seeks to explore the scope for free speech protection.

A study into the layers of automated decision-making: emergent normative and legal aspects of deep learning

ABSTRACT The paper dissects the intricacies of automated decision making (ADM) and urges for refining the current legal definition of artificial intelligence (AI) when pinpointing the role of algorithms in the advent of ubiquitous computing, data analytics and deep learning. Whilst coming up with a toolkit to measure algorithmic determination in automated/semi-automated tasks might be proven to be a tedious task for the legislator, our main aim here is to explain how a thorough understanding of the layers of ADM could be a first good step towards this direction: AI operates on a formula based on several degrees of automation employed in the interaction between the programmer, the user, and the algorithm. The paper offers a fresh look at AI, which exposes certain vulnerabilities in its current legal interpretation. To highlight this argument, analysis proceeds in two parts: Part 1 strives to provide a taxonomy of the various levels of automation that reflects distinct degrees of human–machine interaction. Part 2 further discusses the intricate nature of AI algorithms and considers how one can utilize observed patterns in acquired data. Finally, the paper explores the legal challenges that result from user empowerment and the requirement for data transparency.

Never Mind the Data: The Legal Quest over Control of Information & the Networked Self

The paper discusses the theory of “propertization of data”, namely the proposition that data can be owned and constitute ones property, in the light of big data and the quantified self (QS) movement. Can we really own our own data? Part 1 discusses the issue of commodification of personal data and part 2 dissects this further by examining how personal data is treated at each stage of the big data processing cycle. Parts 3 and 4 complete the argument put forth here, namely that raw data -once seen out of context and as a part of a dataset can indeed be considered as property, able to be owned and traded.