Lifting the curtain: Strategic visibility of human labour in AI-as-a-Service

Artificial Intelligence-as-a-Service (AIaaS) empowers individuals and organisations to access AI on-demand, in either tailored or ‘off-the-shelf’ forms. However, institutional separation between development, training and deployment can lead to critical opacities, such as obscuring the level of human...

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Vydané v:Big data & society Ročník 8; číslo 1
Hlavný autor: Newlands, Gemma
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London, England SAGE Publications 01.01.2021
Sage Publications Ltd
SAGE Publishing
Predmet:
Artificial intelligence
Deployment
Humans
Information services
Labor
Lifting
Narratives
Secrets
Training
Unpaid
Vendors
Visibility
hidden work
AI-as-a-Service
machine learning
artificial intelligence
commercial logics
transparency
ISSN:2053-9517, 2053-9517
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Shrnutí:Artificial Intelligence-as-a-Service (AIaaS) empowers individuals and organisations to access AI on-demand, in either tailored or ‘off-the-shelf’ forms. However, institutional separation between development, training and deployment can lead to critical opacities, such as obscuring the level of human effort necessary to produce and train AI services. Information about how, where, and for whom AI services have been produced are valuable secrets, which vendors strategically disclose to clients depending on commercial interests. This article provides a critical analysis of how AIaaS vendors manipulate the visibility of human labour in AI production based on whether the vendor relies on paid or unpaid labour to fill interstitial gaps. Where vendors are able to occlude human labour in the organisational ‘backstage,’ such as in data preparation, validation or impersonation, they do so regularly, further contributing to ongoing techno-utopian narratives of AI hype. Yet, when vendors must co-produce the AI service with the client, such as through localised AI training, they must ‘lift the curtain’, resulting in a paradoxical situation of needing to both perpetuate dominant AI hype narratives while emphasising AI’s mundane limitations.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2053-9517
2053-9517
DOI:10.1177/20539517211016026