Alienation in the Algorithmic Labour of Search Engine Optimisation Specialists.

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Bibliographic Details
Title: Alienation in the Algorithmic Labour of Search Engine Optimisation Specialists.
Authors: Ivanova, Mirela1 (AUTHOR) mirela.ivanova@unibas.ch, Nachtwey, Oliver1 (AUTHOR), Thaa, Helene1 (AUTHOR), Hardering, Friedericke2 (AUTHOR)
Source: New Technology, Work & Employment. Nov2025, Vol. 40 Issue 3, p635-645. 11p.
Subjects: Search engine optimization, Social alienation, Management controls, Occupational prestige, Computational complexity, Google Inc., Industrial relations
Abstract: The study examines alienation in the labouring activity of Search Engine Optimisation (SEO) specialists and probes the role of Google's algorithm in these experiences. Drawing on qualitative interviews, it identifies two forms of alienation. The first form involves powerlessness and insecurity due to managerial control by objectives, making employees responsible for influencing an algorithm beyond their control. The second form, occupational status alienation, is marked by insecurity and lack of recognition, driven by a resource allocation mechanism disadvantaging SEO due to its algorithmic uncertainty. These findings enhance our understanding of alienation in algorithmic labour by emphasizing the need to examine workers' algorithmic experiences within the broader context of capital‐labour relations. In SEO's case, experiences of alienation do not arise from interactions with opaque algorithm wielding power over labour but rather from a managerial model that holds employees responsible for achieving success within an environment defined by algorithmic uncertainty. [ABSTRACT FROM AUTHOR]
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Database: Engineering Source
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Abstract:The study examines alienation in the labouring activity of Search Engine Optimisation (SEO) specialists and probes the role of Google's algorithm in these experiences. Drawing on qualitative interviews, it identifies two forms of alienation. The first form involves powerlessness and insecurity due to managerial control by objectives, making employees responsible for influencing an algorithm beyond their control. The second form, occupational status alienation, is marked by insecurity and lack of recognition, driven by a resource allocation mechanism disadvantaging SEO due to its algorithmic uncertainty. These findings enhance our understanding of alienation in algorithmic labour by emphasizing the need to examine workers' algorithmic experiences within the broader context of capital‐labour relations. In SEO's case, experiences of alienation do not arise from interactions with opaque algorithm wielding power over labour but rather from a managerial model that holds employees responsible for achieving success within an environment defined by algorithmic uncertainty. [ABSTRACT FROM AUTHOR]
ISSN:02681072
DOI:10.1111/ntwe.12341