Conference Agenda

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Session Overview
Session
RN18_01a: Algorithm, Artificial Intelligence and Technology
Time:
Wednesday, 21/Aug/2019:
11:00am - 12:30pm

Session Chair: Christian Fuchs, University of Westminster
Location: UP.4.209
University of Manchester Building: University Place, Fourth Floor Oxford Road

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Presentations

Do Algorithms have a Right to the City? Waze and Spatial Sovereignty

Eran Fisher

The Open University of Israel, Israel

Waze is an epitome of contemporary algorithmic culture: it is a web application using algorithms to render massive amounts of user-generated data into real-time, personalized driving recommendations for millions of drivers. The aggregative effects of personalized recommendations have social-wide spatial ramifications. I look at one spatial effect in order to unpack the political significance of algorithms: the diversion of heavy traffic into previously serene neighborhoods. By analyzing the discourse of three stakeholders - residents, political authorities and Waze - the paper uncovers the emergence of a new spatial-political modality. Using “the right to the city” as a socio-political framework and juxtaposing it with actor-network theory as a socio-technical framework, I examine how non-human actors participate in shaping the city. Waze offers a new spatial imaginary where roads are abstracted from their immediate space and are seen as homologous to all roads in the network. This allows to strip “local” residents of their privileged position, and reposition them in a new, de-localized space subject to the privilege of all drivers. Rather than imagining roads as nodes in the construction of space – of villages and neighborhoods – Waze imagines them as connectors between nodes in an otherwise abstract network. Algorithms assert their legitimacy as political subjects and as having a genuine right to the city by proposing a new political modality that bypasses the demographic qualities of individuals (where they live, their local culture, their subjective habitat narratives) and constructing individuals as data points in an objectified system of data, processed in order to achieve efficiency.



Educating to Cultural Complexity of Algorithms: Is It a Possible Challenge?

Lorenza Boninu

University of Pisa, Italy

Algorithmic revolution involves the schools in three different ways. First, the education system is a complex organization whose functions have progressively been implemented through procedural optimization: the identification of objectives and the ensuing recruitment, allocation, and selection of the workforce, as well as the evaluation of the system and of formative outputs fall within this purview. Secondly, classrooms are often places of dissemination for the new “algorithmic faith”, the so called “computational thinking”, seen as essentially the sole key for reading and interpreting reality (Wing, 2006). Finally, the so-called learning management systems (LMS) adopted in the schools, which are often relying upon and controlled by digital platforms as Google, Microsoft, and Apple, may be used for collecting data and profiling users, even if they are viewed as neutral tools to support and simplify teaching via digitalization (Scheff, 2014). My research examines the ongoing transformation of the education system under the influence of algorithmic modeling (O’Neill, 2017). In particular, I invite reflection on the potential disruptive effects such silent revolution may have on the cultural heritage the school has preserved and transmitted, as well as on the learning goals and outcomes it has set and produced thus far (Hayles, 2005). To conclude, I propose the possibility that the school itself may provide the necessary skills to understand and manage the man-machine integration born from the algorithmic software (Pireddu, 2017). This is the critical role that a new kind of school should take on. It is a difficult task, which requires avoiding no less any uncritical celebration than any aprioristic refusal of technology (Carrington, 2018).



Algorithmic Acceleration: Towards a Fast and Slow Journalism?

Jernej A. Prodnik

Faculty of Social Sciences, University of Ljubljana, Slovenia

In technological jargon algorithm can be considered as a "method for solving a problem." (Finn, 2017: 18) In this view, narrow problems are instrumentally defined by engineers and entrepreneurs that develop code with an aim of overcoming these problems. Even at first glance, it is clear such abstract definitions cannot explain why algorithms now play one of the central roles in almost all spheres of society, from politics and economy to culture and interpersonal relationships (Pasquale, 2015). Because technologies are inevitably embedded within the social context in which they develop, this paper first looks at the key characteristics of algorithms in competitive and inherently unstable capitalist society (Streeck, 2012). Basic features of algorithms in this context include: (1) opacity and complexity, (2) automatization, (3) dependency on big data, and (4) hyper-rationalisation. Obviously, social consequences of these characteristics are multifaceted. In the second part, the paper therefore looks specifically at social acceleration, which is mainly connected to automatization of processes and decisions. According to Rosa (2013; 2014), social acceleration is a constitutive part of modern societies; in late modernity, however, it becomes a self-propelling system "that incessantly drives itself." (2014: 31-33) Algorithms can be seen as an important part of technological acceleration, which is a dimension of this closed acceleration-cycle. In the field of journalism, acceleration raises new dilemmas that I deal with in the third part of the paper. They include: a) influence of algorithmic acceleration on journalism and its normative presumptions; b) (in)ability of journalism to respond to these challenges. I ask whether a differentiation between slow and fast journalism (Le Masurier, 2014; Rusbridger, 2018; Rauch, 2018) could help resolve any of these dilemmas.



Beyond DAPL: Drones as Counter – Narrative Tools in Journalism Practices

Gaia Casagrande, Mohamed Amine Khaddar

La Sapienza University of Rome, Italy

In the last decades, the unmanned aerial vehicles (UAVs) have turned from military to commercial product, for both professional and personal use. The different applications of UAVs in civil society are the demonstration of how drones have entered into the processes of technological convergence, becoming a physical extension remotely controllable by a mobile device.

Even if the issue remains under-investigated in academic literature, lately the interest in drone journalism or dronalism (Goldberg et al., 2013) has increased among scholars. Most of them are quite sure that “unmanned aerial vehicles are soon going to be a natural and ubiquitous part of our lives” (Gynnild A., Usakali T., 2018).

Based on these considerations, the aims of this work – in progress paper are to investigate UAVs as potential tools of counter-narrative in journalism practices and to understand how this could affect and/or involve the audience. Starting from the case of study of North Dakota Pipeline (DAPL) (Tuck S., 2018; Rafsky S., 2017), which well exemplifies contradictions and potentials of drone journalism, we would like to go deeper in the debate.

More in detail, we would like to understand if the overcoming of spatial barriers could improve a new form of journalistic storytelling, enable different forms of audience engagement, and provide a balancing asset among powers. In order to do so, we will use the theoretical concepts of media as extension (McLuhan, 1964) and of hybrid media system (Chadwick, 2013).



 
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