Re-coding Black Mirror
Potential risks of semantic technologies
Semantic solutions against the misuse of technologies
Semantic technologies enabling or preventing Black Mirror's dystopian future
Black Mirror is a British science fiction television anthology series created by Charlie Brooker and centred around dark and satirical themes that examine modern society, particularly with regard to the unanticipated consequences of new technologies.
Re-coding Black Mirror is a half-day workshop which aims at exploring how (semantic) web technologies could prevent or minimise potential social and ethical risks emanating from the wide use of digital advancements, as the dystopian future seen in Black Mirror's episodes.
Re-coding Black Mirror is about creating connections between researchers building semantic web technologies and interested in their potential future implication on society, and researchers studying such impact of technology interested in the societal and ethical risks of such technological advances.
We expect two different types of works to be presented at the workshop, as briefly described by the following examples. Submissions are of course not restricted to those examples, but works addressing those scenarios would be very much welcome.
Here we are looking at how ongoing research in the semantic web community could lead to technological advances similar to what is presented in one specific episode (or a set of episodes if it is a recurring trend). For example:
How could advances in semantically combining results in natural language processing and social media analysis lead to the ability to create a bot mimicking the personality of a dead person from their online contributions? S02E01 - Be right back
How could semantic technologies be used to integrate information about another person from multiple online sources (digital footprinting), providing a mean for stalking or even blackmailing them? S03E03 - Shut Up and Dance
Many of the episodes in Black Mirror rely on a practice and use of technology which is either unexpected in itself, or which consequences are unexpected. Here we are looking at how semantic web technologies could reduce those risks. For example:
How could relying on semantic relations between people and information about their network/context prevents the appearance of extreme cases in user ratings? S03E01 - Nosedive
How could semantic content and network analysis be used to reduce or counter the spread of hate on social media? S03E06 - Hated in the Nation
Please submit your contribution to the workshop by July 21st 2017 (23:59 Hawaii time) through the easychair system.
We accept three categories of submissions: full papers (max 12 pages) on research and applied technologies, short papers (max 6 pages) about visions and positions on forthcoming challenges and abstracts (max 2 pages) on the societal and ethical challenges of the aforementioned technologies.
All papers should be formatted using the Springer LNCS format.
We expect each paper to take as a starting point one futuristic scenario, either directly from Black Mirror or of a similar nature, as motivation for the work presented.
Kirstie Ball, School of Management, University of St. Andrews, United Kingdom
Pompeu Casanovas, Institute of Law and Technology, Universidad Autònoma de Barcelona, Spain
Lina Dencik, School of Journalism, Media and Cultural Studies, Cardiff University, United Kingdom
Sara Degli Esposti, Internet Interdisciplinary Institute, Universdad Oberta de Catalunya, Spain
Stefan Dietze, L3S Research Cente, University of Leipzig, Germany
Seda Guerses, COSIC Research Group, K.U. Leuven, Belgium
Pascal Hitzler, Data Semantics Laboratory, Wright State University, U.S.A.
Sabrina Kirrane, Institute for Information Business, Vienna University of Economics and Business, Austria
Matthias Leese, Center for Security Studies, ETH Zurich, Switzerland
Liisa Mäkinen, Social and Public Policy, University of Helsinki, Finland
Andrea Mannocci, Knowledge Media Institute, The Open University, United Kingdom
Angelo Antonio Salatino, Knowledge Media Institute, The Open University, United Kingdom
Raphaël Troncy, Data Science Department, EURECOM, France
Daniel Trottier, Department of Media and Communication, Erasmus University of Rotterdam, The Netherlands
Dimitris Tsapogas, Department of Computer Science, University of Oxford, United Kingdom
Nikolas Thomopoulos, Systems Management and Strategy, University of Greenwich, United Kingdom
Lachlan Urquhart, Information Technology Law, Horizon Digital Economy Research Institute, United Kingdom
Frank Van Harmelen, Network Institute, Vrije Universiteit Amsterdam, The Netherlands
Pieter Verdegem, School of Media, Arts & Design, University of Westminster, United Kingdom
Serena Villata, SPARKS-WIMMICS, INRIA, France