Initially coined by Weizenbaum in 1976, ‘alien' thought refers to the radical difference with which ‘thinking machines’ approach the process of thinking. The contemporary paradox of over-determination and indeterminacy—caused largely by algorithmic decision-making in the civic realm—makes these differences both more entangled and more difficult to navigate. In this essay, I trace over-determination to Leibniz and Turing’s axiomatic procedures and to instrumental rationality, and I trace indeterminacy to the mid-twentieth century co-development of computers and neurosciences to advance the following proposition: (...) understanding alien thought requires understanding incomputability, temporal swarming, and inscriptive-significational errance. Understanding these phenomena in turn requires understanding thinking by doing, distributed thinking, and ontological indeterminacy. All are present in machinic operations as well as in the twentieth century experimental artistic practices of artists such as Duchamp, Cage, and Xu. These practices rely on indeterminate procedures and function as diagrammatic machines. A diagrammatic machine is neither abstract nor particular; neither an idea that is determining in the supreme instance, nor an infrastructure that is determining in the last instance, but rather instantiates a real yet to come (Deleuze and Guattari in A thousand plateaus: capitalism and schizophrenia: Trans. Massumi B, University of Minnesota Press, Minneapolis, 1987). In this essay, indeterminate artistic practices are used as an entry into alien thought and its correlates—infinity and complexity—by way of aesthetic analogy. (shrink)

A common theme in social science studies of algorithms is that they are profoundly opaque and function as “black boxes.” Scholars have developed several methodological approaches in order to address algorithmic opacity. Here I argue that we can explicitly enroll algorithms in ethnographic research, which can shed light on unexpected aspects of algorithmic systems—including their opacity. I delineate three meso-level strategies for algorithmic ethnography. The first, algorithmic refraction, examines the reconfigurations that take place when computational software, people, and institutions interact. (...) The second strategy, algorithmic comparison, relies on a similarity-and-difference approach to identify the instruments’ unique features. The third strategy, algorithmic triangulation, enrolls algorithms to help gather rich qualitative data. I conclude by discussing the implications of this toolkit for the study of algorithms and future of ethnographic fieldwork. (shrink)

In our contemporary moment, when machine learning algorithms are reshaping many aspects of society, the work of N. Katherine Hayles stands as a powerful corpus for understanding what is at stake in a new regime of computation. A renowned literary theorist whose work bridges the humanities and sciences among her many works, Hayles has detailed ways to think about embodiment in an age of virtuality ( How We Became Posthuman, 1999), how code as performative practice is located ( My Mother (...) Was a Computer, 2005), and the reciprocal relations among human bodies and technics ( How We Think, 2012). This special issue follows the 2017 publication of her book Unthought: The Power of the Cognitive Nonconscious, in which Hayles traces the nonconscious cognition of biological life-forms and computational media. The articles in the special issue respond in different ways to Hayles’ oeuvre, mapping the specific contours of computational regimes and developing some of the ‘inflection points’ she advocates in the deep engagement with technical systems. (shrink)

In noise we hear the possibility of a signal, indeed different signals, and in the multiplicity of signals we hear noise. With variation and selection comes dynamic evolution, a contingent state, one that could be otherwise. The term ‘polemogenous’ (from the French, polémogène) means that which generates polemics. And polemics are creative. If everyone, every system, were to reason in the same way, there would be silence. Every remark would be redundant, having no informational value. Thus noise is not bad. (...) The essence of finance economics, like all that is social in nature, is a forming of meaning. Whatever cannot be formed meaningfully is not available to the system. This unavailability, as ‘noise’, is the dynamic difference (noise/information) that scintillates the system. Information, like morality, is polemogenous – it stirs contention. Without noise and the possibility of its conversion to information there would be no opportunities to exploit. This paper applies a systems theoretical understanding of observation to conceive of finance economics as the economy’s means of observing its noise and capitalizing on that polemic. Niklas Luhmann’s method is utilized to explicate some ideas on noise by financial economist Fischer Black, who suggests the incomprehensible is computable. This is finance. The fact that logical grounds, absolute deductions, and clear calculations are claimed to be rare in finance is no barrier to understanding it. Rather, this polyphonic and polemogenous information-selection is the ‘ground’ of finance, not as totalizing logic, but as different difference-production for the sake of deriving economic opportunity. (shrink)

Certain strands of contemporary media theory are concerned with the ways in which computational environments exploit the ‘missing half-second’ of human perception and thereby influence, control or exploit humans at an affective level. The ‘technological unconscious’ of our times is often understood to work at this affective level, and high-frequency trading is regularly provided as a primary illustrative example of the contagious dynamics it produces. We challenge and complicate this account of the relation between consciousness, affect and media technologies by (...) drawing on the recent work of N. Katherine Hayles and by focusing in detail on the ways in which the ‘costs of consciousness’ are accounted for and negotiated in high-frequency trading. We suggest that traders actively develop modes of awareness accounting for the costs of consciousness, and that the necessary ‘stupidity’ of high-frequency trading algorithms as well as competition pose limits to the full automation of financial markets. (shrink)