Technologies of Speculation:
The limits of knowledge in a data-driven society
(NYU Press, 2020, formerly Fabrications)

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You can also read the first two chapters here.

Virtual Book Talks:
02.Oct.20 @ Ryerson |  20.Oct.20 @ Concordia |
11.Nov.20 Nov @ Penn  |  26.Feb.21 @ SFU (Video) |
April talks to be announced soon

Short pieces about the book:
Blogpost @ NYU Press Blog
Discussion with Trevor Paglen @ Art in America |
Interview with Emily Watlington @ LA Review of Books
“Why Transparency Won’t Save Us” @ CIGI

Reviews of Technologies of Speculation:
Anthony Glyn Burton @ Int’l Journal of Communication
Rowan Melling @ Critical Studies in Media Communication
Emanuel Moss @ Journal of Cultural Economy

If you are teaching the book, you might find the Instructor’s Guide useful!

What counts as knowledge in the age of big data and smart machines?
In its pursuit of better knowledge, technology is reshaping what counts as knowledge in its own image – and demanding that the rest of us catch up to new machinic standards for what counts as suspicious, informed, employable. In the process, datafication often generates speculation as much as it does information. The push for algorithmic certainty sets loose an expansive array of incomplete archives, speculative judgments and simulated futures where technology meets enduring social and political problems.

Technologies of Speculation traces this technological manufacturing of speculation as knowledge. It shows how unprovable predictions, uncertain data and black-boxed systems are upgraded into the status of fact – with lasting consequences for criminal justice, public opinion, employability, and more. It tells the story of vast dragnet systems constructed to predict the next terrorist, and how familiar forms of prejudice seep into the data by the back door. In software placeholders like ‘Mohammed Badguy’, the fantasy of pure data collides with the old spectre of national purity. It tells the story of smart machines for ubiquitous and automated self-tracking, manufacturing knowledge that paradoxically lies beyond the human senses. Such data is increasingly being taken up by employers, insurers and courts of law, creating imperfect proxies through which my truth can be overruled.

The book situates ongoing controversies over AI and algorithms within a broader societal faith in objective truth and technological progress. It argues that even as datafication leverages this faith to establish its dominance, it is dismantling the longstanding link between knowledge and human reason, rational publics and free individuals. Technologies of Speculation thus emphasises the basic ethical problem underlying contemporary debates over privacy, surveillance and algorithmic bias: who, or what, has the right to the truth of who I am and what is good for me? If data promises objective knowledge, then we must ask in return: knowledge by and for whom, enabling what forms of life for the human subject?

Praise for Technologies of Speculation:

“Juxtaposing methods of state- and self-surveillance—from government terrorism forensics to personal biohacking projects—Sun-ha Hong illuminates the common epistemological dynamics of contemporary approaches to uncertainty and truth. Eschewing modern technological fantasies, Technologies of Speculation offers readers a prescient framework to make sense of the data-driven logics that seek to know, and shape, our lifeworlds.”
~Natasha Dow Schüll, author of Addiction By Design: Machine Gambling in Las Vegas

“Drawing luminous connections between mass surveillance and self-tracking, Technologies of Speculation incisively explores the interplay between the new capacities of data science and the often fanciful but significant castings of the power and objectivity that these sciences promise. Hong’s readings of the Snowden documents are among the smartest, freshest, and most incisive to date. He challenges our understanding of the digital terrain we traverse and that follows us forward.”
~Matthew L Jones, author of Reckoning with Matter: Calculating Machines, Innovation, and Thinking about Thinking from Pascal to Babbage