The Datalogical Turn

tags

Datafication

Notes

Algorithmic architectures are no longer exclusively aiming to predict or calculate probabilities but rather operate so that “any set of instructions is conditioned by what cannot be calculated,”

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entanglement of what George Steinmetz has called sociology’s “epistemological unconscious” (2005) with the systems theory of cybernetics in the post-World War II years

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opening sociality to the post-probablistic

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challenging the positivism, empiricism, and scientism that form the unconscious drive of sociological methodology and its ontology

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non- representation points to the real presence of incomputable data

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big data and the algorithmic architectures that sort it serve less as a fundamental break with the unconscious of sociology than they are an intensification of sociological methods of measuring populations

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a more fully developed realization of the unconscious drive of sociological methodology

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sociology’s unconscious drive has always been datalogical

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The concern is not so much that these technologies are being deployed in the academy, but rather that there is a usurpation of social science by instruments of capital markets

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The redistribution of the human body and the figure of the human subject into datafied terrains have underlined the discipline from its inception

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Cybernetics, of course, has been focused on the disintegration of the biophysical into the informational

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The epistemological unconscious of sociology arises in the post-World War II years with the presumption that the social world can be objectively studied

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in second order cybernetics and the critical social theories and methodologies that would arise in the 1970s and 1980s, reflexive interventions would be imagined that were meant to “correct” the dis-identification of the observer with data

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an autopoietic framework made the dis-identification of the researcher with the researched an untenable ontological position.

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No observer can be outside of the system observed, because under autopoietic conditions, the system self-organizes around and within inputs, including the observer as input

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the lessons of the second order have been taken up primarily as a simultaneous acknowledgement of one’s presence in the field of observation via “reflexivity” and then the dismissal of this presence’s importance to the overall project

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defensive insistence on the capacity and obligation of the researcher to “speak for” the researched

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Sociology no longer has a monopoly on “social” data collection and analysis; rather human lives continually pass through datafied terrains

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The “point” of the datalogical is not to describe a stabilized system or to follow a representational trail, but instead to collect information that would typically be discarded as noise

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non-representational in that they seek to prehend 2 incomputable data and thereby modulate the emergent forms of sociality in their emergence

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toward the incomputable conditioning of parametric practices

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analytic not of numbers, per se, but of parameters, leaning toward the nonrepresentational.

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What is crucial in post-cybernetic logic is not the reliable relationship between input and output but rather the capacity to generate new and interesting sets of relationships

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computing technologies can not be thought merely to be reductive: they neither quantify biophysical and cultural capacities nor are calculation or information understood simply to be grounded in such capacities

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architectural algorithms of big data make use of the unknowable or the incomputable in a non-conscious manner

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the incomputable or the incompressible information that would necessarily be excluded or bracketed in cybernetic logics is folded into algorithmic architectures such that at any time the incomputable may deracinate the whole

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Although it has been claimed that Big Data represents the “end of theory” (Anderson, 2008) we are suggesting that the datalogical turn is, rather, the end of the illusion of a human and systems-oriented sociology

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under contemporary regimes of big data and its algorithmic architectures, noise and information are ontologically inseparable

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We are suggesting that the datalogical leads less towards an articulable demographic than towards an ecology of Whiteheadian “occasions”

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big data allows for a new, prehensive mode of thought that collapses emergence into the changing parameters of computational arrangements.

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derivatives “turn the contestability of fundamental value into a tradable commodity”—a market benchmark for unknowable value”: an incomputable value that is nonetheless deployed in measure

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Radical empiricism moves past a sense- or observation- based-empiricism to look to the processes and practices by which discrete events or occasions come into being. In other words this empiricism recognizes the reality of that which is pre-individual, other or below human perception, cognition or consciousness, which as we have seen are key to datalogical production

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proposes that methods of study be rethought in terms of performativity or what Thrift refers to as “play” (2007, p. 7) or “experimentation”

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