Dear AoIR/AoIR-Grad list members, enclosed please find the second call for proposals for: "Rethinking AI Neural Networks, Biopolitics and the New Artificial Intelligence" Digital Culture & Society Abstract submission: 01 September, 2017 Ramón Reichert, Mathias Fuchs (eds.) Rethinking AI Neural Networks, Biopolitics and the New Artificial Intelligence Ramón Reichert, Mathias Fuchs (eds.) The meaning of AI has undergone drastic changes during the last 60 years of AI discourse(s). What we talk about when saying “AI” is not what it meant in 1958, when John McCarthy, Marvin Minsky and their colleagues started using the term. Take game design as an example: When the Unreal game engine introduced "AI" in 1999, they were mainly talking about pathfinding. For Epic Megagames, the producers of Unreal, an AI was just a bot or monster whose pathfinding capabilities had been programmed in a few lines of code to escape an enemy. This is not "intelligence" in the Minskyan understanding of the word (and even less what Alan Turing had in mind when he designed the Turing test). There are also attempts to differentiate between AI, classical AI and "Computational Intelligence" (Al-Jobouri 2017). The latter is labelled CI and is used to describe processes such as player affective modelling, co-evolution, automatically generated procedural environments, etc. Artificial intelligence research has been commonly conceptualised as an attempt to reduce the complexity of human thinking. (cf. Varela 1988: 359-75) The idea was to map the human brain onto a machine for symbol manipulation – the computer. (Minsky 1952; Simon 1996; Hayles 1999) Already in the early days of what we now call “AI research” McCulloch and Pitts commented on human intelligence and proposed in 1943 that the networking of neurons could be used for pattern recognition purposes (McCulloch/Pitts 1943). Trying to implement cerebral processes on digital computers was the method of choice for the pioneers of artificial intelligence research. The “New AI” is no longer concerned with the needs to observe the congruencies or limitations of being compatible with the biological nature of human intelligence: “Old AI crucially depended on the functionalist assumption that intelligent systems, brains or computers, carry out some Turing-equivalent serial symbol processing, and that the symbols processed are a representation of the field of action of that system.” (Pickering 1993, 126) The ecological approach of the New AI has its greatest impact by showing how it is possible “to learn to recognize objects and events without having any formal representation of them stored within the system.” (ibid, 127) The New Artificial Intelligence movement has abandoned the cognitivist perspective and now instead relies on the premise that intelligent behaviour should be analysed using synthetically produced equipment and control architectures (cf. Munakata 2008). Kate Crawford (Microsoft Research) has recently warned against the impact that current AI research might have, in a noteworthy lecture titled: AI and the Rise of Fascism. Crawford analysed the risks and potential of AI research and asked for a critical approach in regard to new forms of data-driven governmentality: “Just as we are reaching a crucial inflection point in the deployment of AI into everyday life, we are seeing the rise of white nationalism and right-wing authoritarianism in Europe, the US and beyond. How do we protect our communities – and particularly already vulnerable and marginalized groups – from the potential uses of these systems for surveillance, harassment, detainment or deportation?” (Crawford 2017) Following Crawford’s critical assessment, this issue of the Digital Culture & Society journal deals with the impact of AI in knowledge areas such as computational technology, social sciences, philosophy, game studies and the humanities in general. Subdisciplines of traditional computer sciences, in particular Artificial Intelligence, Neuroinformatics, Evolutionary Computation, Robotics and Computer Vision once more gain attention. Biological information processing is firmly embedded in commercial applications like the intelligent personal Google Assistant, Facebook’s facial recognition algorithm, Deep Face, Amazon’s device Alexa or Apple’s software feature Siri (a speech interpretation and recognition interface) to mention just a few. In 2016 Google, Facebook, Amazon, IBM and Microsoft founded what they call a Partnership on AI. (Hern 2016) This indicates a move from academic research institutions to company research clusters. We are in this context interested in receiving contributions on the aspects of the history of institutional and private research in AI. We would like to invite articles that observe the history of the notion of “artificial intelligence” and articles that point out how specific academic and commercial fields (e.g. game design, aviation industry, transport industry etc.) interpret and use the notion of AI. Against this background, the special issue Rethinking AI will explore and reflect the hype of neuroinformatics in AI discourses and the potential and limits of critique in the age of computational intelligence. (Johnston 2008; Hayles 2014, 199-210) We are inviting contributions that deal with the history, theory and the aesthetics of contemporary neuroscience and the recent trends of artificial intelligence. (cf. Halpern 2014, 62ff) Digital societies increasingly depend on smart learning environments that are technologically inscribed. We ask for the role and value of open processes in learning environments and we welcome contributions that acknowledge the regime of production as promoted by recent developments in AI. We particularly welcome contributions that are historical and comparative or critically reflective about the biological impact on social processes, individual behaviour and technical infrastructure in a post-digital and post-human environment? What are the social, cultural and ethical issues, when artificial neuronal networks take hold in digital cultures? What is the impact on digital culture and society, when multi-agent systems are equipped with license to act? Submissions might cover the following topics or extend beyond that: A historical perspective of object/pattern recognition/identification/detection and AI Artificial intelligence recognition algorithms Computer vision Deep learning Device ecology Digital education governance Epistemology of learning in artificial neural networks Evolutionary computation Fuzzy systems and neural networks Games and virtual worlds Genetic algorithms Human enhancement and transhumanism Media archaeology Philosophical Posthumanism Philosophy of robotics Prognostics and predictive modelling Science history of neural nets and deep learning Socio-cultural Posthumanism Deadlines and contact information - Expressions of interest/Initial abstracts (max. 300 words) and short biographical note (max. 100 words) are due on: September 04, 2017. - Authors will be notified by September 10, 2017, whether they are invited to submit a full paper. - Full papers are due on: November 20, 2017. - Notifications to authors of referee decisions: January 15, 2018. - Final versions due: March 01, 2018. - Please send your abstract and short biographical note to Ramón Reichert ramon.reichert@univie.ac.at and Mathias Fuchs mathias.fuchs@leuphana.de. About the Journal: Digital Culture & Society seeks contributions that display a clear, inspiring engagement with media theory and/or methodological issues. Emphasising the relevance of new practices and technology appropriation for theory as well as methodology debates, the journal also encourages empirical investigations. For more info please visit: http://digicults.org/callforpapers/cfp-rethinking-ai/ For more information, see the official journal website: http://digicults.org/callforpapers/cfp-rethinking-ai/ With best wishes, Ramón -- Ramón Reichert tfm | Department for Theatre, Film and Media Studies Vienna University Althanstraße 14 1090 Vienna E-Mail: ramon.reichert@univie.ac.at Twitter: Ramón Reichert Skype: ramon_reichert NEW: CfP „Rethinking AI: Neural Networks, Biopolitics and the New Artificial Intelligence”. Spring Issue of Digital Culture & Society. Abstract deadline: July 10, 2017, http://digicults.org/callforpapers/cfp-rethinking-ai/ Co-Editor Journal Digital Culture & Society: http://www.transcript-verlag.de/zeitschriften/digital-culture-und-society/ Head of the post-graduate master’s course Data Studies at the Danube University Krems: http://www.donau-uni.ac.at/en/studium/data-studies/index.php European Project Researcher "Visual/video literacies", Erasmus+: http://ec.europa.eu/programmes/erasmus-plus/projects/eplus-project-details-p... 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