Today’s artificial intelligence, largely based on data-intensive machine learning algorithms, relies heavily on the digital labour of invisibilized and precarized humans-in-the-loop who perform multiple functions of data preparation, verification of results, and even impersonation when algorithms fail. Using original quantitative and qualitative data, the present article shows that these workers are highly educated, engage significant (sometimes advanced) skills in their activity, and earnestly learn alongside machines. However, the loop is one in which human workers are at a disadvantage as they experience systematic misrecognition of the value of their competencies and of their contributions to technology, the economy, and ultimately society. This situation hinders negotiations with companies, shifts power away from workers, and challenges the traditional balancing role of the salary institution.
Learners in the loop: hidden human skills in machine intelligence
Résumé
en
Today’s artificial intelligence, largely based on data-intensive machine learning algorithms, relies heavily on the digital labour of invisibilized and precarized humans-in-the-loop who perform multiple functions of data preparation, verification of results, and even impersonation when algorithms fail. Using original quantitative and qualitative data, the present article shows that these workers are highly educated, engage significant (sometimes advanced) skills in their activity, and earnestly learn alongside machines. However, the loop is one in which human workers are at a disadvantage as they experience systematic misrecognition of the value of their competencies and of their contributions to technology, the economy, and ultimately society. This situation hinders negotiations with companies, shifts power away from workers, and challenges the traditional balancing role of the salary institution.
Auteur(s)
Paola Tubaro1, 2, 3, 4, 5
1
CREST -
Centre de Recherche en Économie et Statistique
( 2579 )
- 5, Avenue Henry Le Chatelier
91120 Palaiseau
- France
Ecole Nationale de la Statistique et de l'Analyse de l'Information [Bruz] ( 244399 )
;
École polytechnique ( 300340 )
;
École Nationale de la Statistique et de l'Administration Économique ( 300604 )
;
Centre National de la Recherche Scientifique UMR 9194 ( 441569 )
2
LSQ -
Laboratoire de sociologie quantitative
( 189980 )
- 60, rue Etienne Dolet 92245 Malakoff Cedex
- France
Centre de Recherche en Économie et STatistique (CREST) ( 302113 )
3
MSH Paris-Saclay -
Maison des Sciences de l'Homme - Paris Saclay
( 1051095 )
- MSH Paris-Saclay USR 3683 C/o ENS Paris-Saclay
Bâtiment Laplace
61, avenue du Président Wilson
94230 CACHAN
- France
Université de Versailles Saint-Quentin-en-Yvelines ( 81173 )
;
Université Paris-Saclay ( 419361 )
;
Centre National de la Recherche Scientifique UAR3683 / USR3683 ( 441569 )
;
Ecole Normale Supérieure Paris-Saclay ( 523723 )
4
LISN -
Laboratoire Interdisciplinaire des Sciences du Numérique
( 1061259 )
- Campus Universitaire bât 507
Rue du Belvédère
91405 Orsay cedex
et
Campus Universitaire bât 640
1 rue Raimond Castaing
91190 Gif-sur-Yvette
- France
Institut National de Recherche en Informatique et en Automatique ( 300009 )
;
CentraleSupélec ( 411575 )
;
Université Paris-Saclay ( 419361 )
;
Centre National de la Recherche Scientifique UMR9015 ( 441569 )
5
TAU -
TAckling the Underspecified
( 1066529 )
- Université Paris Saclay
Bâtiment 660 - Shannon ;
91405 Orsay Cedex
- France
Inria Saclay - Ile de France ( 118511 )
;
Institut National de Recherche en Informatique et en Automatique ( 300009 )
;
Laboratoire Interdisciplinaire des Sciences du Numérique ( 1061259 )
;
Institut National de Recherche en Informatique et en Automatique ( 300009 )
;
CentraleSupélec ( 411575 )
;
Université Paris-Saclay ( 419361 )
;
Centre National de la Recherche Scientifique UMR9015 ( 441569 )
Langue du document
Anglais
Date de production/écriture
2022
Nom de la revue
Sociologia del Lavoro
(ISSN : 0392-5048, ISSN électronique : 1972-554X)
Publié par Franco Angeli
Revue non référencée dans Sherpa-Romeo
Paola Tubaro. Learners in the loop: hidden human skills in machine intelligence. Sociologia del Lavoro, 2022, 163, pp.110-129. ⟨10.3280/SL2022-163006⟩. ⟨hal-03787017⟩