'Big Data, Open Data, Privacy Regulations, Intellectual Property and Competition Law in an Internet of Things World' by Bjorn Lundqvist
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The interface between the legal systems triggered by the creation, distribution and consumption of Data is difficult to grasp, and this paper therefore tries to dissect this interface by following information, i.e. ‘the data’ from its sources, to users and re-users and ultimately to its consumers in an ‘Internet of Things’, or Industrial Internet, setting. The paper starts with the attempt to identify what legal systems are applicable this process, with special focus on when competition law may be useful for accessing data. The paper conclude that general competition law may not be readily available for accessing generic (personal or non-personal) Data, except for the situation where the Data set is indispensable to access an industry or a relevant market; while sector specific regulations seem to emerge as a tool for accessing Data held by competitors and third parties. However, the main issue under general competition law in the Data industry, at its current stage of development, is to create a levelled playing field by trying to facilitate the implementation of Internet of Things.
'A Critical Axiology for Big Data Studies' by Saif Shahin in (2016) 19(4)
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Big Data is having a huge impact on journalism and communication studies. At the same time, it has raised a plethora of social concerns ranging from mass surveillance to the legitimization of prejudices such as racism. This article develops an agenda for critical Big Data research. It discusses what the purpose of such research should be, what pitfalls it should guard against, and the possibility of adapting Big Data methods to conduct empirical research from a critical standpoint. Such a research program will not only enable critical scholarship to meaningfully challenge Big Data as a hegemonic tool, but will also make it possible for scholars to draw upon Big Data resources to address a range of social issues in previously impossible ways. Te article calls for methodological innovation in combining emerging Big Data techniques with critical/qualitative methods of research, such as ethnography and discourse analysis, in ways that allow them to complement each other.
The techno-euphoria spurred by the advent of Big Data (e.g. Anderson, 2008) is slowly giving way to uneasiness about the social effects of enormous datasets and the algorithms used to compile and analyze them (boyd & Crawford, 2012; Crawford, Miltner, and Gray, 2014; Mahrt and Scharkow, 2013; Manovich, 2012; Shahin, 2016a). Reports of malpractices by major Big Data-enabled enterprises such as Facebook and Google that compromise user privacy (Dwyer, 2011; Rubenstein and Good, 2012), along with Edward Snowden’s revelation that the U.S. government was running surveillance programs on a global scale in collusion with technology companies (Bauman et al., 2014; Lyon, 2014), have made it plain that Big Data is not the panacea for all human problems that it is sometimes made out to be. Instead, Big Data may be reinforcing social divides and exacerbating a variety of social concerns.
A ProPublica investigation revealed that a criminal risk assessment algorithm developed by a commercial enterprise, widely used by courts and law enforcement officials across the United States, “was particularly likely to falsely flag black defendants as future criminals, wrongly labeling them this way at almost twice the rate as white defendants” (Angwin et al., 2016, para. 16). A New York Times article highlighted a series of “mistakes” committed by commonly used Big Data technologies, including Google Photos tagging black people as “gorillas,” Nikon cameras asking Asians – who often have small eyes compared with Caucasians – if they were “blinking” (Crawford, 2016). Meanwhile, reports continue to emerge about social media companies becoming ever more intrusive, collecting increasing amounts of users’ personal data to serve advertisers and even running experiments manipulating user sentiments (Dewey, 2016).
What do these concerns mean for journalism and communication research, a field in which Big Data is having a huge impact? Scholars in our field quickly took to Big Data studies: partly because much of Big Data is generated by media and communication technologies – mobile telephones, social media, and so on – and partly because Big Data started altering the economic and operational dynamics of established media institutions especially news organizations. The surge of interest in Big Data research, and awareness of its game-changing potential, is evident in the deluge of Big Data articles being published in communication journals; special is-sues on Big Data that several journals of note have come up with, including the Journal of Communication; Journalism and Mass Communication Quarterly; Journal of Broadcasting and Electronic Media; International Journal of Communication; and Media, Culture and Society; and the emergence of new journals devoted to Big Data research, such as Big Data and Society and Social Media + Society.
This article provides an assessment of what Big Data research has come to mean in journalism and communication studies, identifying two expansive categories: research with Big Data and research on Big Data. Ten, drawing on Gitlin’s (1978) well-known critique of Katz and Lazarsfeld’s (1955) two-step flow theory as the “dominant paradigm” in media studies, the article examines the ideological underpinnings of Big Data research – now regarded as a “paradigm” in its own right (Burgess, Bruns, & Hjorth, 2013). Building on this critique, the article charts an agenda for critical Big Data research, discussing what the purpose of such research should be, what pitfalls it should guard against, and the possibility of adapting Big Data methods themselves to conduct critical research. It argues that a critical approach to Big Data is necessary not only because the problems posed by Big Data need to be explicitly examined in line with critical theory and methods, but also because developing such a research agenda can help critical scholarship in journalism and communication studies draw upon Big Data resources to address a broad range of social concerns in previously impossible ways.
