Recessive Objects

The Snowden files are recessive objects: things that promise to extend our knowability but, in doing so, catalyze speculation and doubt. Drawing on media phenomenology, this chapter connects this recessivity to the surveillance systems themselves and the war on terror. The effort to predict the “lone wolf” terrorist, from the Boston bomber to the Las Vegas shooter, paradoxically becomes a site for smuggling in old racial prejudices about the monstrous Other. The convenient myth of “pure” data here encounters the far older and troubling project of national, territorial, and racial purity.

Bodies into Facts

The rapid expansion of machinic knowledge provokes new kinds of speculative heuristics, offering deferred and simulated ways of feeling like we know. Examining sting operations, zero-tolerance rhetoric, and drone warfare, this chapter traces three such techniques of fabrication: subjunctivity, an “as if” form of reasoning; interpassivity, the designation of an other who knows in my stead; and zero-degree risk, where the language of calculable risk is used to paper over the incalculable uncertainties surrounding surveillance and terrorism.

Data’s Intimacy

Today, machines observe, record, and sense the world—not just for us but also often instead of us and indifferently to our meaning. The intertwined problems of technological knowledge and (our) knowledge of technology manifest in the growing industry of smart machines, the Internet of Things, and other means for self-tracking. The automation of the care of the self is buoyed by a popular fantasy of data’s intimacy, of machines that know you better than yourself. Yet as the technology becomes normalized, the hacker ethic gives way to a market-driven shift in which more and more of “my” personal truth is colonized by machines (and the people behind the machines) that I cannot question.

The Indefinite Archive

The Snowden affair dramatizes a growing contradiction: technologies such as the National Security Agency’s surveillance systems increasingly withdraw from public visibility, even as they promise better knowledge for a more rational public. This asymmetry provokes new patterns of paranoid and speculative politics, where the faith in transparency as disinfect places impossible expectations on the public to “know for themselves.”

Introduction

Technologies of datafication pursue the familiar modern promise of better knowledge—and, in doing so, reshape what counts as knowledge in their own image. The fantasy of raw data, objective truth, and predictive control licenses a new array of fabrications: approximations are solidified into facts; algorithmic biases, endowed with neutrality; and uncertainties, upgraded into predictions. Big data and smart machines are technologies of speculation that are establishing new societal defaults for what counts as truth.

Conclusion

The recurring disappointments of technological fantasies, and data-driven knowledge’s destabilization of the liberal subject, produce urgent political and ethical questions around the technological pursuit of better knowledge. These questions cannot be answered through metrics, such as efficiency and accuracy, tools offered by technology to assess its own legitimacy. Critique must take up the task of disrespecting the rationality of technology, a rationality that is increasingly “not for us” and to build the external moral standards through which it can be held to account.

Honeymoon Objectivity

Technologies of datafication exert their societal influence through a recurring modern fantasy of “honeymoon objectivity,” wherein technoscience might purify complex social problems and human biases to produce a stable grounding for judgment. Although fulfillment is constantly deferred, this fantasy enrolls society in a fast-expanding data market. Problems of criminal justice, political will, self-knowledge, and economic success are subordinated to the logic of surveillance capitalism and its search for meaning-indifferent, commercially recombinable data.

Data-Sense and Non-Sense

Data-driven knowledge is increasingly produced without regard to human cognition and sensibility, yet this conflagration of machinic non-sense also demands that we adapt to its rationality. Data-sense describes the popular expectation that a posthuman future is inevitable, compelling human subjects to orient their personal lives and truths in ways most compatible with machine learning and other regimes of data-driven analysis. The pursuit of the human nonconscious as a source of objective truth erodes the ground beneath the feet of the good liberal subject and concomitant ideals of agency, freedom, and self-determination.