Catherine D’Ignazio, Lauren F. Klein: Data Feminism (2020)

14 May 2020, dusan

“Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D’Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought.

Illustrating data feminism in action, D’Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.”

Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn’t, and about how those differentials of power can be challenged and changed.”

Publisher MIT Press, 2020
strong Ideas series
Creative Commons CC BY-NC-ND license
ISBN 9780262044004, 0262044005
xii+314 pages

Interviews with authors: Jason Forrest (Nightingale, 2019), Zoë Corbyn (The Guardian, 2020).

Book website

PDF (39 MB)

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)

Lisa Gitelman (ed.): “Raw Data” is an Oxymoron (2013)

7 May 2013, dusan

We live in the era of Big Data, with storage and transmission capacity measured not just in terabytes but in petabytes (where peta- denotes a quadrillion, or a thousand trillion). Data collection is constant and even insidious, with every click and every “like” stored somewhere for something. This book reminds us that data is anything but “raw,” that we shouldn’t think of data as a natural resource but as a cultural one that needs to be generated, protected, and interpreted. The book’s essays describe eight episodes in the history of data from the predigital to the digital. Together they address such issues as the ways that different kinds of data and different domains of inquiry are mutually defining; how data are variously “cooked” in the processes of their collection and use; and conflicts over what can—or can’t—be “reduced” to data. Contributors discuss the intellectual history of data as a concept; describe early financial modeling and some unusual sources for astronomical data; discover the prehistory of the database in newspaper clippings and index cards; and consider contemporary “dataveillance” of our online habits as well as the complexity of scientific data curation.

Essay authors:
Geoffrey C. Bowker, Kevin R. Brine, Ellen Gruber Garvey, Lisa Gitelman, Steven J. Jackson, Virginia Jackson, Markus Krajewski, Mary Poovey, Rita Raley, David Ribes, Daniel Rosenberg, Matthew Stanley, Travis D. Williams

Publisher MIT Press, 2013
Infrastructures Series
ISBN 0262518287, 9780262518284
182 pages

review (Niccolò Tempini, LSE blog)

google books

Download (removed on 2013-11-12 upon request of the publisher)