Filed under journal | Tags: · algorithm, biometrics, cultural politics, database, environment, knowledge, research, value
“There is value and there are values. There is the measure of wealth, metrified and calculated in numerous ways, and there are ideas, ethics, preferences of taste, and customs of ideology. […] But what really happens when the two are conflated? How do we understand how the values associated with something give it value; or, how giving something a value affords certain values? And, in what ways are the conflations of value and values tied to the circulation of value and values in contemporary technical infrastructures? […] The articles published in this issue interrogate value and values in ways that respond to techno-cultural shifts and embrace the range of economies that pervade digital culture.” (from Introduction)
Contributions by Pip Thornton, Luke Munn, Mitra Azar, Lea Laura Michelsen, Francis Hunger, César Escudero Andaluz & Martín Nadal, Maria Eriksson, Dionysia Mylonaki & Panagiotis Tigas, Marc Garrett, Ashley Lee Wong, Konstanze Scheidt, Calum Bowden, and Tega Brain.
Edited by Christian Ulrik Andersen & Geoff Cox
Publisher DARC, Aarhus University, Aarhus, 2018
Creative Commons Attribution-NonCommercial-ShareAlike License
Filed under book | Tags: · abstraction, algorithm, archaeology, artificial intelligence, code, data, diagram, error, information science, information theory, knowledge, machine learning, mathematics, neural networks, programming, theory
“If machine learning transforms the nature of knowledge, does it also transform the practice of critical thought?
Machine learning—programming computers to learn from data—has spread across scientific disciplines, media, entertainment, and government. Medical research, autonomous vehicles, credit transaction processing, computer gaming, recommendation systems, finance, surveillance, and robotics use machine learning. Machine learning devices (sometimes understood as scientific models, sometimes as operational algorithms) anchor the field of data science. They have also become mundane mechanisms deeply embedded in a variety of systems and gadgets. In contexts from the everyday to the esoteric, machine learning is said to transform the nature of knowledge. In this book, Adrian Mackenzie investigates whether machine learning also transforms the practice of critical thinking.
Mackenzie focuses on machine learners—either humans and machines or human-machine relations—situated among settings, data, and devices. The settings range from fMRI to Facebook; the data anything from cat images to DNA sequences; the devices include neural networks, support vector machines, and decision trees. He examines specific learning algorithms—writing code and writing about code—and develops an archaeology of operations that, following Foucault, views machine learning as a form of knowledge production and a strategy of power. Exploring layers of abstraction, data infrastructures, coding practices, diagrams, mathematical formalisms, and the social organization of machine learning, Mackenzie traces the mostly invisible architecture of one of the central zones of contemporary technological cultures.
Mackenzie’s account of machine learning locates places in which a sense of agency can take root. His archaeology of the operational formation of machine learning does not unearth the footprint of a strategic monolith but reveals the local tributaries of force that feed into the generalization and plurality of the field.”
Publisher MIT Press, November 2017
ISBN 9780262036825, 0262036827
PDF (removed on 2018-8-20 upon request from publisher)
Draft and code samples on GIT
Filed under book | Tags: · cultural production, distributed aesthetics, distribution, knowledge, sharing
“The power of knowledge lies not only in generating ideas, but also in controlling their dispersion. For those who would seek to influence others, the dissemination of ideas is paramount. For those looking to protect the fruits of intellectual labor for reasons of profit or ethics, distribution is something to control. Either way, distribution is a key concern across the spectrum of cultural production, particularly at a time when digital networks have facilitated an unprecedented access to audiences.
Bringing together contributors from a variety of backgrounds, Distributed presents the act of distribution as a subject of significant social and economic importance and argues that it merits serious creative consideration. From the attention-seeking impulse of the “influencer” to the democratization of art via books, performances, videos or sound, the increased urge to disseminate is explored here as an elemental phenomenon of our time.”
Texts by Ahmed Ansari, Stuart Bertolotti-Bailey, Justin Clemens, Alex Coles, Jonathan Lindley, Neil Cummings, Arnaud Desjardin, Markus Miessen, Sean Dockray & Benjamin Forster, Billie Muraben, Patricia Reed, Adrian Shaughnessy, Freek Lomme, Eva Weinmayr, et al.
Publisher Open Editions, London, 2018