[Air-L] CfP: "Rethinking AI Neural Networks, Biopolitics and the New Artificial Intelligence"

Ramón Reichert ramon.reichert at univie.ac.at
Tue Aug 8 15:50:01 PDT 2017


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 at univie.ac.at and Mathias Fuchs 
mathias.fuchs at 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 at 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-page/?nodeRef=workspace://SpacesStore/ad93c65c-662e-4375-85b4-279b976be6ec

Lectrice
Département des sciences de la communication et des médias
Université de Fribourg, Suisse, http://www.unifr.ch/dcm/?page=accueil

Lecturer in Contextual Studies
School of Humanities and Social Sciences, St. Gallen, Switzerland 
http://www.unisg.ch/de/universitaet/schools/humanities+and+social+sciences

Expert evaluator on behalf of the European Commission:
https://erc.europa.eu/

Reviewer on behalf of the Federal Ministry of Education and Research:
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Current publications:
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