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Cited by 262Digital Economy and Work TransformationLegal and Labor StudiesEthics and Social Impacts of AI

The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.

The trainer, the verifier, the imitator: Three ways in which human platform workers support artificial intelligence

Open access
Tubaro, Paola, Casilli, Antonio A, Coville, Marion·2020·Big Data & Society
DOI 10.1177/2053951720919776
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Abstract

This paper sheds light on the role of digital platform labour in the development of today’s artificial intelligence, predicated on data-intensive machine learning algorithms. Focus is on the specific ways in which outsourcing of data tasks to myriad ‘micro-workers’, recruited and managed through specialized platforms, powers virtual assistants, self-driving vehicles and connected objects. Using qualitative data from multiple sources, we show that micro-work performs a variety of functions, between three poles that we label, respectively, ‘artificial intelligence preparation’, ‘artificial intelligence verification’ and ‘artificial intelligence impersonation’. Because of the wide scope of application of micro-work, it is a structural component of contemporary artificial intelligence production processes – not an ephemeral form of support that may vanish once the technology reaches maturity stage. Through the lens of micro-work, we prefigure the policy implications of a future in which data technologies do not replace human workforce but imply its marginalization and precariousness.

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Research works printed but not linked: 4

  1. Casilli A, 2019, En attendant les robots: Enquête sur le travail du clic
  2. Chui M, 2016, McKinsey Q, 2016, 1
  3. De Stefano V, 2016, Comparative Labor Law & Policy Journal, 37
  4. Silberman S, 2016, Comparative Labor Law & Policy Journal, 37

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Metadata

Authors
Tubaro, P., Casilli, A. A., & Coville, M.
Affiliations
  • Centre National de la Recherche Scientifique (FR)
  • Télécom Paris (FR)
  • Université de Poitiers (FR)
Corresponding author
Tubaro, Paola
ORCID
Venue
Big Data & Society
Publisher
SAGE Publications
Published
2020-01
Volume
7
Issue
1
Pages
205395172091977
ISSN
2053-9517 (ISSN-L)
DOI
10.1177/2053951720919776
OpenAlex
W3018104257
Cited by
262
References
26
Citations by year
2026: 44 · 2025: 61 · 2024: 48 · 2023: 38 · 2022: 45 · 2021: 19 · 2020: 7
FWCI
36.46
Type
journal article
Language
en
Open access
Licence
Locations
  • Big Data & Society (publishedVersion, cc-by-nc-nd)
  • RePEc: Research Papers in Economics (submittedVersion)
  • HAL (submittedVersion, other-oa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • France Stratégie
  • MSH Paris Saclay (17-MA07)
  • Force Ouvrière - Institut de recherches économiques et sociales
Topics
  • Social Sciences › Sociology and Political Science › Digital Economy and Work Transformation
  • Social Sciences › Business, Management and Accounting › Industrial relations › Legal and Labor Studies
  • Physical Sciences › Computer Science › Artificial Intelligence › Ethics and Social Impacts of AI
Keywords
AI development, data annotation, machine learning training data, precarious employment, AI verification

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