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Big Data Subjectivity.

Affsprung, Daniel.

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Big Data Subjectivity.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Big Data Subjectivity./
Author:	Affsprung, Daniel.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
Description:	153 p.
Notes:	Source: Masters Abstracts International, Volume: 81-12.
Contained By:	Masters Abstracts International81-12.
Subject:	Information technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=27994632
ISBN:	9798645450502

Big Data Subjectivity.
Affsprung, Daniel.

Big Data Subjectivity. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 153 p.

Source: Masters Abstracts International, Volume: 81-12.

Thesis (M.A.L.S.)--Dartmouth College, 2020.

This item must not be sold to any third party vendors.

Big data is much discussed in business, government, and healthcare, but the ascendance of the data-driven approach has consequences beyond these areas, detectable in both discourse and cultural practices such as self-quantification. The questions explored in this work, "Can the data speak for itself?" and "Can the data speak for us?" are sparked by discourse which positions data or numbers as a communicator or speaker. The conceptual metaphor evinced by these enunciations (e.g. "The numbers speak for themselves", "What does the data tell you?") is articulated in this work and critically examined as a supporting element of big data's claims to objectivity. That objectivity, relying as it does on the denial of human subjectivity, intention, and interpretation, becomes especially problematic in cases where the data being examined is generated by human action. Such cases employ a kind of knowledge production Antoinette Rouvroy calls data behaviorism, which crucially alters the way subjects are formed by rendering individual motivations and narratives secondary to predictive quantitative models. This work examines the data behaviorist change in subjectivation together with critical analysis of quantified self practices and Foucauldian understandings of cultural neoliberalism, and studies the relationships between these and the 4P healthcare paradigm. By looking at how data has come to speak for us, this paper evaluates the risk of diminished reflexive capacities in subjects as self-knowledge and self-expression become deficient by comparison to technologies creating user profiles or 'data doubles', and asserts that, in the examples studied, these produce 'proletarianization' by Bernard Stiegler's definition. The consequences of this are shown through a shift in perspective to Lacanian psychoanalytic examinations of the data double and profile, he subject's relation to these, and the psychic consequences of an ascendant digital order displacing the symbolic. The work concludes with a brief consideration of the limitations of automated interpretation of human action and signifying language.

ISBN: 9798645450502Subjects--Topical Terms:

532993
Information technology.
Subjects--Index Terms:

Algorithm

Big Data Subjectivity.
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