Learners in the loop: hidden human skills in machine intelligence

Journal title SOCIOLOGIA DEL LAVORO
Author/s Paola Tubaro
Publishing Year 2022 Issue 2022/163
Language English Pages 20 P. 110-129 File size 236 KB
DOI 10.3280/SL2022-163006
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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.

Keywords: Digital labour platforms, Artificial intelligence, Skills, Spanish-speaking countries

  1. Altenried M. (2020). The platform as factory: Crowdwork and the hidden labour behind artificial intelligence. Capital & Class, 44(2): 145-158. DOI: 10.1177/030981681989941
  2. Berg J., Furrer M., Harmon E., Rani U., Silberman M.S. (2018). Digital labour platforms and the future of work: Towards decent work in the online world. Geneva: ILO Report. -- Available at: www.ilo.org/global/publications/books/WCMS_645337/lang—en/index.htm.
  3. Casilli A.A. (2019). En attendant les robots: Enquête sur le travail du clic. Paris: Seuil.
  4. Casilli A.A., Tubaro P., Le Ludec C., Coville M., Besenval M., Mouhtare T.. Wahal E. (2019). Le micro-travail en France. Derrière l’automatisation, de nouvelles précarités au travail? Paris, Report of the Digital Platform Labor (DiPLab) project. -- Available at: https://hal.inria.fr/hal-02139528/.
  5. Chicchi F. (2020). Beyond the ‘salary institution’: on the ‘society of performance’ and the platformisation of the employment relationship. Work Organisation, Labour & Globalisation, 14(1): 15-31.
  6. Cognilytica (2020). Data preparation and labeling for AI 2020. Report CGR-DLP20. Washington DC: Cognilytica.
  7. Crouch C. (1997). Skills-based full employment: the latest philosopher’s stone. British Journal of Industrial Relations, 35(3): 367-391.
  8. Crouch C., Finegold D., Sako M. (2001). Are Skills the Answer? The Political Economy of Skill Creation in Advanced Industrial Countries. Oxford: Oxford University Press.
  9. Denton E., Hanna A., Amironesei R., Smart A., Nicole H. (2021). On the genealogy of machine learning datasets: A critical history of ImageNet. Big Data & Society, 8(2). DOI: 10.1177/20539517211035955
  10. Difallah D., Filatova E., Ipeirotis P. (2018). Demographics and dynamics of Mechanical Turk workers. Proceedings of WSDM 2018: the Eleventh ACM International Conference on Web Search and Data Mining, ACM: 135-143.
  11. Ekbia H.R., Nardi B.A. (2017). Heteromation, and Other Stories of Computing and Capitalism. Cambridge (MA): MIT Press.
  12. ENCOVI (2018). Encuesta Nacional de Condiciones de Vida. Caracas: Universidad Católica Andrés Bello.
  13. ENCOVI (2021). Encuesta Nacional de Condiciones de Vida. Documento técnico. Caracas: Universidad Católica Andrés Bello.
  14. Graham M., Anwar M. (2019). The global gig economy: towards a planetary labour market? First Monday, 24(4).
  15. Gray M., Suri S. (2019). Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass. Boston, MA: Houghton Mifflin Harcourt.
  16. Grohmann R., Fernandes Araújo W. (2021). Beyond Mechanical Turk: The work of Brazilians on global AI platforms. In: P. Verdegem, ed., AI for Everyone? Critical Perspectives, University of Westminster Press, pp. 247-266.
  17. Heuer H., Jarke J., Breiter A. (2021). Machine learning in tutorials – Universal applicability, underinformed application, and other misconceptions. Big Data & Society, 8(1). DOI: 10.1177/20539517211017593
  18. Honneth A. 1995 [1992]. The Struggle for Recognition: The Moral Grammar of Social Conflicts. Cambridge: Polity Press.
  19. ILO (2021). World Employment and Social Outlook 2021: The role of digital labour platforms in transforming the world of work. Report. Geneva: ILO.
  20. Ipeirotis P. (2010). Demographics of Mechanical Turk. NYU Working Paper, CEDER-10-01.
  21. Irani L. (2015). The cultural work of microwork. New Media & Society, 17(5): 720-739. DOI: 10.1177/146144481351192
  22. Kässi O., Lehdonvirta V., Stephany F. (2021). How many online workers are there in the world? A data-driven assessment [version 4; peer review: 4 approved]. Open Research Europe, 1:53.
  23. Lehdonvirta V., Kässi O., Hjorth I., Barnard H., Graham M. (2019). The global platform economy: A new offshoring institution enabling emerging-economy microproviders. Journal of Management, 45(2): 567-599. DOI: 10.1177/014920631878678
  24. Lindquist J. (2018). Illicit economies of the Internet: Click farming in Indonesia and beyond. Made in China Journal, 3(4): 88-91.
  25. OECD (2021). Education at a Glance 2021. Report. Paris: OECD.
  26. Margaryan A. (2019a). Comparing crowdworkers’ and conventional knowledge workers’ self-regulated learning strategies in the workplace. Human Computation, 6: 83-97.
  27. Margaryan A. (2019b). Workplace learning in crowdwork: Comparing microworkers’ and online freelancers’ practices. Journal of Workplace Learning, 31(4): 250-273. DOI: 10.1108/JWL-10-2018-012
  28. Margaryan A., Charlton-Czaplicki T., Gadiraju U. (2020). Learning and Skill Development in Online Platform Work: Comparing Microworkers’ and Online Freelancers’ Practices. CBS Report.
  29. Mavridis P., Gross-Amblard D., Miklós Z. (2016). Using hierarchical skills for optimized task assignment in knowledge-intensive crowdsourcing. Proceedings of the 25th International Conference on World Wide Web, 843-853.
  30. Mehrotra S. (2018). From the informal to the formal economy: Skills initiatives in India. In A. Sakamoto, J. Sung, eds., Skills and the future of work: Strategies for inclusive growth in Asia and the Pacific. Geneva: International Labour Organization, pp. 364-390.
  31. Miceli M., Schuessler M., Yang T. (2020). Between subjectivity and imposition: Power dynamics in data annotation for computer vision, Proceedings of the ACM on Human-Computer Interaction, 4, CSCW2, 115, DOI: 10.1145/341518
  32. Mothobi O., Gillwald A., Schoentgen A. (2018). What Is The State Of Microwork in Africa? A View from Seven Countries. Report, Research ICT Africa.
  33. Newlands G. (2021). Lifting the curtain: Strategic visibility of human labour in AI-as-a-Service. Big Data and Society, 8(1). DOI: 10.1177/2053951721101602
  34. Palmer R. (2017). Jobs and skills mismatch in the informal economy. Geneva: International Labour Organization.
  35. Posada J. (2022, online first). Embedded reproduction in platform data work. Information, Communication & Society. DOI: 10.1080/1369118X.2022.2049849
  36. Schmidt F. (2019). Crowdproduktion von Trainingsdaten: Zur Rolle von Online-Arbeit beim Trainieren autonomer Fahrzeuge. Report, Düsseldorf: Hans-Böckler-Stiftung.
  37. Tomaskovic-Devey D., Avent-Holt D. (2019). Relational Inequalities: An Organizational Approach. Oxford: Oxford University Press.
  38. Tubaro P., Casilli A.A. (2019). Micro-work, artificial intelligence and the automotive industry. Journal of Industrial and Business Economics, 46(3): 333-345.
  39. Tubaro P., Casilli A.A., Coville M. (2020a). The trainer, the verifier, the imitator: Three ways in which human platform workers support artificial intelligence. Big Data & Society, 7(1). DOI: 10.1177/205395172091977
  40. Tubaro P., Le Ludec C., Casilli A.A. (2020b). Counting ‘micro-workers’: societal and methodological challenges around new forms of labour. Work Organisation, Labour & Globalisation, 14(1), 67-82.
  41. Tubaro P. (2021). Disembedded or deeply embedded? A multi-level network analysis of online labour platforms. Sociology, 55(5): 927-944. DOI: 10.1177/003803852098608
  42. Tubaro P., Casilli A.A. (2022). Human listeners and virtual assistants: privacy and labor arbitrage in the production of smart technologies. In: F. Ferrari, M. Graham, eds., Digital Work in the Planetary Market, Cambridge (MA): MIT Press, pp. 175-190.
  43. Tubaro P., Coville M., Le Ludec C., Casilli A.A. (2022). Hidden inequalities: the gendered labour of women on micro-tasking platforms. Internet Policy Review, 11(1). DOI: 10.14763/2022.1.162
  44. UNESCO Institute for Statistics. (2022). Sustainable Development Goals Data. Available at: http://data.uis.unesco.org/.
  45. Wood A.J., Graham M., Lehdonvirta V., Hjorth I. (2019). Networked but commodified: The (dis)embeddedness of digital labour in the gig economy. Sociology, 53(5): 931-950. DOI: 10.1177/003803851982890

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    DOI: 10.3389/feduc.2023.1186731
  • Dis//assemblages of AI: repair labor and resistance in the automated workplace Dominique A. Montiel Valle, Samantha Shorey, in Information, Communication & Society /2024 pp.2022
    DOI: 10.1080/1369118X.2024.2371794

Paola Tubaro, Learners in the loop: hidden human skills in machine intelligence in "SOCIOLOGIA DEL LAVORO " 163/2022, pp 110-129, DOI: 10.3280/SL2022-163006