Nanna Bonde Thylstrup: The Politics of Mass Digitization (2018)

1 February 2019, dusan

“A new examination of mass digitization as an emerging sociopolitical and sociotechnical phenomenon that alters the politics of cultural memory.

Today, all of us with internet connections can access millions of digitized cultural artifacts from the comfort of our desks. Institutions and individuals add thousands of new cultural works to the digital sphere every day, creating new central nexuses of knowledge. How does this affect us politically and culturally? In this book, Nanna Bonde Thylstrup approaches mass digitization as an emerging sociopolitical and sociotechnical phenomenon, offering a new understanding of a defining concept of our time.

Arguing that digitization has become a global cultural political project, Thylstrup draws on case studies of different forms of mass digitization—including Google Books, Europeana, and the shadow libraries Monoskop,, and Ubuweb—to suggest a different approach to the study of digital cultural memory archives. She constructs a new theoretical framework for understanding mass digitization that focuses on notions of assemblage, infrastructure, and infrapolitics. Mass digitization does not consist merely of neutral technical processes, Thylstrup argues, but of distinct subpolitical processes that give rise to new kinds of archives and new ways of interacting with the artifacts they contain. With this book, she offers important and timely guidance on how mass digitization alters the politics of cultural memory to impact our relationship with the past and with one another.”

Publisher MIT Press, 2018
ISBN 9780262039017, 026203901X
ix+200 pages

Commentary: Seb Chan (2019).



A Peer-Reviewed Journal About, 7(1): Research Values (2018)

20 September 2018, dusan

“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
ISSN 2245-7755


Adrian Mackenzie: Machine Learners: Archaeology of a Data Practice (2017)

22 June 2018, dusan

“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
272 pages
via A.B.


PDF (removed on 2018-8-20 upon request from publisher)
Draft and code samples on GIT