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  1.  98
    Bentham, Deleuze and Beyond: An Overview of Surveillance Theories from the Panopticon to Participation.Maša Galič, Tjerk Timan & Bert-Jaap Koops - 2017 - Philosophy and Technology 30 (1):9-37.
    This paper aims to provide an overview of surveillance theories and concepts that can help to understand and debate surveillance in its many forms. As scholars from an increasingly wide range of disciplines are discussing surveillance, this literature review can offer much-needed common ground for the debate. We structure surveillance theory in three roughly chronological/thematic phases. The first two conceptualise surveillance through comprehensive theoretical frameworks which are elaborated in the third phase. The first phase, featuring Bentham and Foucault, offers architectural (...)
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  2.  50
    Surveillance, Self and Smartphones: Tracking Practices in the Nightlife.Tjerk Timan & Anders Albrechtslund - 2018 - Science and Engineering Ethics 24 (3):853-870.
    This paper is the result of the EMERGING ICT FOR CITIZEN VEILLANCE-workshop organized by the JRC, Ispra, Italy, March 2014. The aim of this paper is to explore how the subject participates in surveillance situations with a particular focus on how users experience everyday tracking technologies and practices. Its theoretical points of departure stem from Surveillance Studies in general and notions of participatory surveillance and empowering exhibitionism :199–215, 2004) in particular. We apply these theoretical notions on smartphones and its users (...)
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  3.  5
    We need better images of AI and better conversations about AI.Marc Steen, Tjerk Timan, Jurriaan Van Diggelen & Steven Vethman - forthcoming - AI and Society:1-12.
    In this article, we critique the ways in which the people involved in the development and application of AI systems often visualize and talk about AI systems. Often, they visualize such systems as shiny humanoid robots or as free-floating electronic brains. Such images convey misleading messages; as if AI works independently of people and can reason in ways superior to people. Instead, we propose to visualize AI systems as parts of larger, sociotechnical systems. Here, we can learn, for example, from (...)
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