The algorithmic big Other: using Lacanian theory to rethink control and resistance in platform work

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dc.contributor.authorSalter LA
dc.contributor.authorDutta MJ
dc.date.accessioned2023-10-30T00:56:08Z
dc.date.accessioned2023-11-03T05:06:27Z
dc.date.available2023-10-30T00:56:08Z
dc.date.available2023-11-03T05:06:27Z
dc.date.issued2023-01-01
dc.description.abstractDespite burgeoning literature on platform work, there has been a lack of scholarship which carefully considers what we mean by the terms control and (particularly) resistance in the context of algorithmic management. This article draws on Lacanian psychoanalytic theory to take a step back and interrogate what exactly we mean by these terms in a setting where increasingly the entity being resisted against is an artificially intelligent machine. This approach offers a nuanced way of thinking through the subjective effects of having an algorithm as a boss, and we argue for its benefits and applicability in the age of the algorithmic episteme. Through the key concept of the Algorithmic big Other, we update Lacan’s classic concept to consider what happens when the Other no longer articulates master signifiers through discourse. What we term collective hysterical resistance, aimed at creating spaces for new forms of knowledge and subjectivity, should re-orient towards enlarging the incomputable, the blind spot of the algorithmic episteme.
dc.identifier.citationSalter LA, Dutta MJ. (2023). The algorithmic big Other: using Lacanian theory to rethink control and resistance in platform work. Distinktion.
dc.identifier.doi10.1080/1600910X.2023.2224521
dc.identifier.eissn2159-9149
dc.identifier.elements-typejournal-article
dc.identifier.issn1600-910X
dc.identifier.urihttps://mro.massey.ac.nz/handle/10179/69053
dc.relation.isPartOfDistinktion
dc.relation.urihttps://www.tandfonline.com/doi/full/10.1080/1600910X.2023.2224521
dc.titleThe algorithmic big Other: using Lacanian theory to rethink control and resistance in platform work
dc.typeJournal article
massey.relation.uri-descriptionPublished version
pubs.elements-id479279
pubs.organisational-groupMassey Business School
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