The digital labour of AI in Latin America

Another article has just been published! Another one that is based on a DiPLab-based group collaboration (with A.A. Casilli, M. Fernández Massi, J. Longo, J. Torres Cierpe and M. Viana Braz) and that uses data from multiple countries. It is entitled ‘The digital labour of artificial intelligence in Latin America: a comparison of Argentina, Brazil, and Venezuela’ and is part of a special issue of Globalizations on ‘The Political Economy of AI in Latin America’. This article lifts the veil on the precarious and low-paid data workers who, from Latin America, engage in AI preparation, verification, and impersonation, often for foreign technology producers. Focusing on three countries (Argentina, Brazil, and Venezuela), we use original mixed-method data to compare and contrast these cases in order to reveal common patterns and expose the specificities that distinguish the region.

The analysis unveils the central place of Latin America in the provision of data work. To bring costs down, AI production thrives on countries’ economic hardship and inequalities. In Venezuela and to a lesser extent Argentina, acute economic crisis fuels competition and favours the emergence of ‘elite’ (young and STEM-educated) data workers, while in more stable but very unequal Brazil, this activity is left to relatively underprivileged segments of the workforce. AI data work also redefines these inequalities insofar as, in all three countries, it blends with the historically prevalent informal economy, with workers frequently shifting between the two. There are spillovers into other sectors, with variations depending on country and context, which tie informality to inequality.


Our study has policy implications at global and local levels. Globally, it calls for more attention to the conditions of AI production, especially workers’ rights and pay. Locally, it advocates solutions for the recognition of skills and experience of data workers, in ways that may support their further professional development and trajectories, possibly also facilitating some initial forms of worker organization.


The version of record is here, while an open-access preprint is available here.

Brazil in the global AI supply chains: the role of micro-workers

AI is not just a Silicon Valley dream. It relies among other things, on inputs from human workers who generate and annotate data for machine learning. They record their voice to augment speech datasets, transcribe receipts to provide examples to OCR software, tag objects in photographs to train computer vision algorithms, and so on. They also check algorithmic outputs, for example, by noting whether the outputs of a search engine meet users’ queries. Occasionally, they take the place of failing automation, for example when content moderation software is not subtle enough to distinguish whether some image or video is appropriate. AI producers outsource these so-called “micro-tasks” via international digital labor platforms, who often recruit workers in Global-South countries, where labor costs are lower. Pay is by piecework, without any no long-term commitment and without any social-security scheme or labor protection.

In a just-published report co-authored with Matheus Viana Braz and Antonio A. Casilli, as part of the research program DiPlab, we lifted the curtain on micro-workers in Brazil, a country with a huge, growing, and yet largely unexplored reservoir of AI workers.

We found among other things that:

  • Three out of five Brazilian data workers are women, while in most other previously-surveyed countries, women are a minority (one in three or less in ILO data).
  • 9 reais (1.73 euros) per hour is the average amount earned on platforms.
  • There are at least 54 micro-working platforms operating in Brazil.
  • One third of Brazilian micro-workers have no other source of income, and depend on microworking platforms for subsistence.
  • Two out of five Brazilian data workers are (apart from this activity) unemployed, without professional activity, or in informality. In Brazil, platform microwork arises out of widespread unemployment and informalization of work.
  • Three out of five of data workers have completed undergraduate education, although they mostly do repetitive and unchallenging online data tasks, suggesting some form of skill mismatch.
  • The worst microtasks involve moderation of violent and pornographic contents on social media, as well as data training in tasks that workers may find uncomfortable or weird, such as taking pictures of dog poop in domestic environments to train data for “vacuuming robots”.
  • Workers’ main grievances are linked to uncertainty, lack of transparency, job insecurity, fatigue and lack of social interaction on platforms.

To read the report in English, click here.

To read the report in Portuguese, click here.