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.
%0 Journal Article
%1 tubaro2020trainer
%A Tubaro, Paola
%A Casilli, Antonio A
%A Coville, Marion
%D 2020
%I SAGE Publications
%J Big Data & Society
%K artificial_intelligence datafied_production_processes digital_platform_labour machine_learning micro-work microtasks platform_work
%N 1
%P 205395172091977
%R 10.1177/2053951720919776
%T The trainer, the verifier, the imitator: Three ways in which human platform workers support artificial intelligence
%U https://doi.org/10.1177%2F2053951720919776
%V 7
%X 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.
@article{tubaro2020trainer,
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.},
added-at = {2020-04-27T11:14:54.000+0200},
author = {Tubaro, Paola and Casilli, Antonio A and Coville, Marion},
biburl = {https://www.bibsonomy.org/bibtex/2781b97891d3745d233ca2703a1c37f84/meneteqel},
doi = {10.1177/2053951720919776},
interhash = {123dfa58d2296a870b483631aca9abdd},
intrahash = {781b97891d3745d233ca2703a1c37f84},
journal = {Big Data {\&} Society},
keywords = {artificial_intelligence datafied_production_processes digital_platform_labour machine_learning micro-work microtasks platform_work},
language = {eng},
month = jan,
number = 1,
pages = 205395172091977,
publisher = {{SAGE} Publications},
timestamp = {2020-04-27T11:15:23.000+0200},
title = {The trainer, the verifier, the imitator: Three ways in which human platform workers support artificial intelligence},
url = {https://doi.org/10.1177%2F2053951720919776},
volume = 7,
year = 2020
}