CITIZEN OR CONSUMER? THE RIGHT TO ACCESS DATA IN THE EUROPEAN UNION AND AUSTRALIA James Michael Meese This paper presents early stage findings from a research project that explores whether the provision of data access addresses concerns that have emerged with regards to data collection by private and public actors. Using the recent right to data access secured by the European Union’s General Data Protection Regulation (GDPR) as a point of departure, I examine Facebook and Twitter’s response to these regulations through the lens of their data access policies and processes. I analyse what sort of data is made available and assess what benefit the public gains from having access to their social media data. I then offer a conceptual intervention through a comparative analysis of the divergent approaches two jurisdictions take to data access. I compare the GDPR with an ongoing debate around the introduction of a consumer data access right into Australian law and analyse how these divergent legal traditions and public discourses alter the conceptualisation and enacting of the data access right (and digital rights more generally). This paper provides a timely examination of a right that has emerged in response to the increased datafication of society. As well as offering a detailed analysis of how social media platforms have responded to the data access provisions within the GDPR, the comparative analysis of the EU and Australia shows that significantly different legal foundations can animate this right, ultimately presenting two starkly different visions of internet users as either consumers or citizens.
DATA SCORES AS GOVERNANCE: USES OF CITIZEN SCORING IN PUBLIC SERVICES Lina Dencik, Arne Hintz, Joanna Redden The use of data scores to profile and rank citizens, often by attaching suspicion and risk to people without their knowledge, represents a concrete manifestation of datafication that people recognize as problematic in tangible terms, making it a useful entry-point for investigating an abstract topic that remains under-reported and poorly understood. In this paper we present the findings from a one-year project funded by the Open Society Foundation that has sought to interrogate government uses of data scoring in the UK by combining different methods and lines of inquiry. The project combines computational methods (following the model used for the Algorithmic Tips project led by Nick Diakopolous) with desk research (media reports and Freedom of Information requests) and semi-structured interviews with practitioners from government departments and local authorities and experts from civil society and the technology industry. Looking across different sectors, including education, social welfare, children’s services, immigration, health and crime, the paper will present an interactive map produced as part of the project. In presenting this map, we will outline the role of data scores in the allocation of services and risk assessments in UK public services.
PERSUASION AND THE OTHER THING: A PHENOMENOLOGICAL CRITIQUE OF BIG DATA IN THE DEMOCRATIC PROCESS Molly Rebecca Sauter This paper is a philosophical intervention in “big data” methodologies as they are deployed in electoral and representative politics in the West. This paper stakes out a phenomenological, critical perspective regarding the claims made by companies like Cambridge Analytica and the potential or reasonably foreseeable impacts of those claims and promises on democratic processes. Elish and boyd referred to these claims and promises as “the magic of big data” (Elish and boyd, 2017). This paper argues that the claims made by companies like Cambridge Analytica regarding the predictive modeling of individuals and populations in the context of Western electoral and representative politics can be read as a reflection of how the subjects of these big data analytics projects are viewed by those conducting the research, and the entitlements held by advertisers, tech firms, and researchers who deploy big data analytics in support of political campaigns or other political projects. This paper puts the claims of Cambridge Analytica other companies into dialogue with phenomenological arguments regarding the necessity of the encounter with the other, particularly claims like Kelly Oliver’s which advocate encounters that surpass or are “beyond recognition” (Oliver, 2001), meaning those encounter which jolt the participants out of habitual mental and social conversion of difference into assimilated familiarity.
This paper argues that the use of “big data” in politics strips its targets of subjectivity, turning individuals into ready-to-read “data objects,” and making it easier for those in positions of power to justify aggressive manipulation and invasive inference.
TERMS AND CONDITIONS MAY APPLY: THE EFFECT OF SOCIAL MEDIA ALGORITHMS ON PERSONAL AUTONOMY Katherina Drinkuth The paper uses a relational autonomy model (McKenzie and Stoljar, 2000) to highlight sharing and communicating as central preconditions to autonomy. Autonomy is depicted as inherently relational, and constituted within, not outside of, relationships with others and the material world. With social activities increasingly taking place online in algorithmically mediated environments (Newell and Marabelli, 2015; Taddeo and Floridi, 2015) social media platforms and their algorithms then become relevant sites for, and actors in, the constitution of personal autonomy.
The constant algorithmic mediation of the contemporary everyday (Willson, 2017) is not a mere extension of previous social processes shaping individuals' lives, but involves unique distorting factors at the structural level: novel types of big data knowledge and algorithmic logic. The paper explores how online autonomy is both enabled and constrained by social media algorithms as technological and material presence (Beer, 2017) and as socio-technical concepts.
