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Cited by 45Ethics and Social Impacts of AICultural Identity and RepresentationCybernetics and Technology in Society

The return of the social: Algorithmic identity in an age of symbolic demise

Kotliar, Dan M.·2020·New Media & Society
DOI 10.1177/1461444820912535
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Abstract

This article explores the socio-algorithmic construction of identity categories based on an ethnographic study of the Israeli data analytics industry. While algorithmic categorization has been described as a post-textual phenomenon that leaves language, social theory, and social expertise behind, this article focuses on the return of the social—the process through which the symbolic means resurface to turn algorithmically produced clusters into identity categories. I show that such categories stem not only from algorithms’ structure or their data, but from the social contexts from which they arise, and from the values assigned to them by various individuals. I accordingly argue that algorithmic identities stem from epistemic amalgams—complex blends of algorithmic outputs and human expertise, messy data flows, and diverse inter-personal factors. Finally, I show that this process of amalgamation arbitrarily conjoins quantitative clusters with qualitative labels, and I discuss the implausibility of seeing named algorithmic categories as explainable.

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63 of 63 references verified0 citation errors · 0 not checkable

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  • Recent ethnographic works describe a re-socialization process of algorithmic categories: to become usable in the organization's routines, audience categories are reprocessed, blended with existing organizational knowledge, renamed, translated into explicable concepts, etc.

    “Recent ethnographic works on data analytic organizations describe a re-socialization process of algorithmic categories: to become usable in the organization's routines, audience categories are reprocessed, blended with existing organizational knowledge, renamed, translated into explicable concepts, etc. (Kotliar, 2020;Kotras, 2020).”

    From How online advertising targets consumers: The uses of categories and algorithmic tools by audience planners (2024) · cites this paper as Kotliar, 2020

  • When algorithmic categories come to be used on a regular basis inside organizations, they require an important work of translation.

    “Research suggests that when some of these categories come to be used on a regular basis inside organizations, they require an important work of translation (Kotliar, 2020).”

    From How online advertising targets consumers: The uses of categories and algorithmic tools by audience planners (2024) · cites this paper as Kotliar, 2020

  • Unexplainable algorithmic categories get labeled with approximate but workable social descriptors, an operation Kotliar (2020) analyses as a 'return of the social'.

    “Kotliar (2020) analyses this operation as a “return of the social,” by which unexplainable categories get labeled with approximate but workable social descriptors.”

    From How online advertising targets consumers: The uses of categories and algorithmic tools by audience planners (2024) · cites this paper as Kotliar (2020)

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Authors
Kotliar, D. M.
Affiliations
Hebrew University of Jerusalem (IL)
Corresponding author
Kotliar, Dan M.
ORCID
Kotliar, Dan M.
Venue
New Media & Society
Publisher
SAGE Publications
Published
2020-07
Volume
22
Issue
7
Pages
1152-1167
ISSN
  • 1461-4448 (ISSN-L)
  • 1461-7315
DOI
10.1177/1461444820912535
OpenAlex
W3044158199
Cited by
45
References
65
Citations by year
2026: 5 · 2025: 9 · 2024: 9 · 2023: 10 · 2022: 5 · 2021: 3 · 2020: 3 · 2017: 1
FWCI
7.16
Type
journal article
Language
en
Open access
closed
Licence
journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations
New Media & Society (publishedVersion)
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Arts and Humanities › Philosophy › Cultural Identity and Representation
  • Social Sciences › Arts and Humanities › History and Philosophy of Science › Cybernetics and Technology in Society
Keywords
algorithmic identity, human expertise, algorithmic explainability

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