Winnie Soon, Geoff Cox: Aesthetic Programming: A Handbook of Software Studies (2020)

14 February 2021, dusan

Aesthetic Programming explores the technical as well as cultural imaginaries of programming from its insides. It follows the principle that the growing importance of software requires a new kind of cultural thinking — and curriculum — that can account for, and with which to better understand the politics and aesthetics of algorithmic procedures, data processing and abstraction. It takes a particular interest in power relations that are relatively under-acknowledged in technical subjects, concerning class and capitalism, gender and sexuality, as well as race and the legacies of colonialism. This is not only related to the politics of representation but also nonrepresentation: how power differentials are implicit in code in terms of binary logic, hierarchies, naming of the attributes, and how particular worldviews are reinforced and perpetuated through computation.

Using p5.js, it introduces and demonstrates the reflexive practice of aesthetic programming, engaging with learning to program as a way to understand and question existing technological objects and paradigms, and to explore the potential for reprogramming wider eco-socio-technical systems. The book itself follows this approach, and is offered as a computational object open to modification and reversioning.”

Publisher Open Humanities Press, 2020
Creative Commons BY-SA License
ISBN 9781785420948
293 pages

Project website


Warren Sack: The Software Arts (2019)

19 March 2020, dusan

“In The Software Arts, Warren Sack offers an alternative history of computing that places the arts at the very center of software’s evolution. Tracing the origins of software to eighteenth-century French encyclopedists’ step-by-step descriptions of how things were made in the workshops of artists and artisans, Sack shows that programming languages are the offspring of an effort to describe the mechanical arts in the language of the liberal arts.

Sack offers a reading of the texts of computing—code, algorithms, and technical papers—that emphasizes continuity between prose and programs. He translates concepts and categories from the liberal and mechanical arts—including logic, rhetoric, grammar, learning, algorithm, language, and simulation—into terms of computer science and then considers their further translation into popular culture, where they circulate as forms of digital life. He considers, among other topics, the “arithmetization” of knowledge that presaged digitization; today’s multitude of logics; the history of demonstration, from deduction to newer forms of persuasion; and the post-Chomsky absence of meaning in grammar. With The Software Arts, Sack invites artists and humanists to see how their ideas are at the root of software and invites computer scientists to envision themselves as artists and humanists.”

Publisher MIT Press, 2019
ISBN 9780262039703, 0262039702
xx+375 pages


PDF (19 MB)

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