The Coloniality of Data Work in Latin America
Open accessAbstract
This presentation for the AIES '21 doctoral consortium examines the Latin American crowdsourcing market through a decolonial lens. This research is based on the analysis of the web traffic of ninety-three platforms, interviews with Venezuelan data workers of four platforms, and analysis of the documentation issued by these organizations. The findings show that (1) centuries-old global divisions of labor persist, in this case, with requesters located in advanced economies and workers in the Global South. (2) That the platforms' configuration of the labor process constrains the agency of these workers when producing annotations. And, (3) that ideologies originating from the Global North serve to legitimize and reinforce this global labor market configuration.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
This data work is routinely offshored to workers in Africa, South and Southeast Asia, and Latin America.
“Across both intermediaries, this work is routinely offshored to workers in Africa, South and Southeast Asia, and Latin America [108].”
From 'The plan is just survival': Data Work in Kenya and the Regime of Entrapment (2026) · cites this paper as [108]
The paper says data-annotation tasks are often outsourced worldwide through crowdsourcing platforms (ACM Reference Format, p. 1), and its geographical analysis finds demand mainly in advanced economies and labor supply in the Global South (The Coloniality of Data Work in Latin America, p. 1). It identifies Venezuelan workers but does not establish the claim’s specific destinations in Africa, South Asia, and Southeast Asia or address both intermediaries. (LLM, conf=0.86)
Experimental — accuracy not yet measuredThe organization of contemporary AI data work is entangled with longer histories of colonial extraction and racialized dispossession that shape where value is produced and whose labor is rendered interchangeable.
“The organization of contemporary AI data work is entangled with longer histories of colonial extraction and racialized dispossession that shape where value is produced and whose labor is rendered interchangeable.”
From 'The plan is just survival': Data Work in Kenya and the Regime of Entrapment (2026) · cites this paper as [108]
The paper (p. 1) links contemporary AI data work to centuries-long exploitative relations and describes wealthy institutions in advanced economies benefiting from cheap labor in developing countries. It also describes labor being exchanged as a commodity. Our copy does not specifically establish the claim about racialized dispossession or say that workers are rendered interchangeable. (LLM, conf=0.83)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
No references could be resolved yet.
Research works printed but not linked: 4
- [2][2] Antonio A. Casilli and Julian Posada. 2019. The Platformisation of Labor and Society. In Society and the Internet (vol. 2 ed.), Mark Graham and William H. Dutton (Eds.). Oxford University Press, Oxford. -
- [4][4] Walter D. Mignolo. 2007. Introduction: Coloniality of power and de-colonial thinking. Cultural Studies 21, 2-3 (mar 2007), 155-167. [https://doi.org/10.1080/09502380601162498](https://doi.org/10.1080/09502380601162498) - · DOI
- [6][6] Aníbal Quijano. 1992. Colonialidad y modernidad/racionalidad. Perú Indígena 13, 29 (1992), 11-20. -
- [7][7] Jamie Woodcock and Mark Graham. 2020. The Gig Economy: A Critical Introduction . Polity Press, London. 160 pages.
Cited by
Sorted by citations
'The plan is just survival': Data Work in Kenya and the Regime of Entrapment
Kapania, S., Yang, T., Abdelkadir, N. A., Scheuerman, M. K., Miceli, M., Taylor, A. S., & Fox, S. E. (2026) · Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3772318.3791097 · Cited by 2 · see citing works
“Attending to Posada’s [108] scholarship on coloniality in data work is especially instructive.”
Stevens, N., & Gieseking, J. J. (2026) · Transactions of the Institute of British Geographers · doi:10.1111/tran.70046 · Cited by 2 · see citing works
- Authors
- Posada, J.
- Affiliations
- University of Toronto (CA)
- Corresponding author
- Posada, Julian
- Venue
- Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society
- Publisher
- ACM
- Published
- 2021-07-21
- Pages
- 277-278
- ISSN
- 3065-8365 (ISSN-L)
- OpenAlex
- W3163794561
- Cited by
- 12
- References
- 0
- Citations by year
- 2026: 4 · 2025: 3 · 2024: 3 · 2023: 1 · 2022: 1
- FWCI
- 3.33
- Type
- conference paper
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- Proceedings of the AAAI/ACM Conference on AI Ethics and Society (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- International Development Research Centre
- 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 › Computer Science Applications › Mobile Crowdsensing and Crowdsourcing
- Keywords
- crowdsourcing, data work, decoloniality, coloniality, Global South, Global North, division of labor, worker agency, Latin America, Venezuela, data platform, ideology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
