This paper delves into the human factors in the “back-office” of artificial intelligence and of its data-intensive algorithmic underpinnings. We show that the production of AI is a labor-intensive process, which particularly needs the little-qualified, inconspicuous and low-paid contribution of “micro-workers” who annotate, tag, label, correct and sort the data that help to train and test smart solutions. We illustrate these ideas in the high-profile case of the automotive industry, one of the largest clients of digital data-related micro-working services, notably for the development of autonomous and connected cars. This case demonstrates how micro-work has a place in long supply chains, where tech companies compete with more traditional industry players. Our analysis indicates that the need for micro-work is not a transitory, but a structural one, bound to accompany the further development of the sector; and that its provision involves workers in different geographical and linguistic areas, requiring the joint study of multiple platforms operating at both global and local levels.
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Autor, D. H. (2015). Why are there still so many jobs? The history and future of workplace automation. Journal of Economic Perspectives, 29(3), 3–30.
Bastin, G., & Tubaro, P. (2018). Le moment big data des sciences sociales. Revue française de sociologie, 59(3), 375–394.
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. Report, Geneva: ILO.
Braverman, H. (1974). Labor and monopoly capital: The degradation of work in the twentieth century. New York: Monthly Review Press.
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. New York: Norton.
Casilli, A. A. (2017). Digital labor studies go global: Toward a digital decolonial turn. International Journal of Communication, 11, 3934–3954.
Casilli, A. A. (2019). En attendant les robots. Enquête sur le travail du clic. Paris: Editions du Seuil.
Cognilytica Research. (2019). Data Engineering, Preparation, and Labeling for AI. Report.
Difallah, D., Filatova, E., & Ipeirotis, P. G. (2018). Demographics and dynamics of Mechanical Turk workers. In Proceedings of WSDM 2018: The eleventh ACM international conference on web search and data mining (pp. 135–143). ACM.
Ekbia, H., & Nardi, B. (2017). Heteromation, and other stories of computing and capitalism. Cambridge: MIT Press.
Forde, C., Stuart, M. Joyce, S., Oliver, L., Valizade, D., Alberti, G., Hardy, K., Trappmann, V., Umney, C., & Carson, C. (2017). The social protection of workers in the collaborative economy. Report for European Parliament Employment and Social Affairs Committee.
Frey, C., & Osborne, M. (2017). The future of employment: How susceptible are jobs to computerisation? Technological Forecasting and Social Change, 114(C), 254–280.
Fuchs, C. (2019). Karl Marx in the age of big data capitalism. In D. Chandler & C. Fuchs (Eds.), Digital objects, digital subjects: Interdisciplinary perspectives on capitalism, labour and politics in the age of big data (pp. 53–71). London: University of Westminster Press.
Graham, M., Hjorth, I., & Lehdonvirta, V. (2017). Digital labour and development: impacts of global digital labour platforms and the gig economy on worker livelihoods. Transfer: European Review of Labour and Research, 23(2), 135–162.
Gray, M., & Suri, S. (2017). The humans working behind the AI curtain. Harvard Business Review, 9, 2–5.
Irani, L. (2015). Difference and dependence among digital workers: The case of Amazon Mechanical Turk. South Atlantic Quarterly, 114, 225–234.
Irani, L. (2016). The labor that makes AI “magic”. White House and NYU: AINow Summit.
Kuek, S., Paradi-Guilford, C., Fayomi, T., Imaizumi, S., & Ipeirotis, P. (2015). The global opportunity in online outsourcing. Report, World Bank.
Le Ludec, C., Tubaro, P., & Casilli, A. (2019). How many people microwork in France? Estimating the size of a new labor force. Working paper. arXiv:1901.03889 [econ.GN].
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.
Ohnemus, J., Erdsiek, D., & Viete, S. (2016). Nutzung von Crowdworking durch Unternehmen: Ergebnisse einer ZEW-Unternehmensbefragung. Report, BMAS Forschungsbericht 473. Bundesministerium für Arbeit und Soziales.
Ricardo, D. (1951 ). On the principles of political economy and taxation. In P. Sraffa & M. H. Dobb (Eds.) Works of David Ricardo (Vol. 1). Cambridge University Press, Cambridge.
Rochet, J., & Tirole, J. (2003). Platform competition in two-sided markets. Journal of the European Economic Association, 1, 990–1029.
Schmidt, F. A. (2019). Crowdproduktion von Trainingsdaten: Zur Rolle von Online-Arbeit beim Trainieren autonomer Fahrzeuge. Report, Hans-Böckler-Stiftung.
Star, S. L., & Strauss, A. (1999). Layers of silence, arenas of voice: The ecology of visible and invisible work. Computer Supported Cooperative Work, 8(1–2), 9–30.
Data used in this study are from the DiPLab (“Digital Platform Labor”) research project, co-funded by Maison des Sciences de l’Homme Paris-Saclay (2017); Force Ouvrière (2017), a workers’ union, through IRES (Social and Economic Research Institute); and France Stratégie (2018), a service of the French Prime Minister. We also thank Foule Factory and IsAHit for logistical support, and Inria for complementary funding.
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Tubaro, P., Casilli, A.A. Micro-work, artificial intelligence and the automotive industry. J. Ind. Bus. Econ. 46, 333–345 (2019). https://doi.org/10.1007/s40812-019-00121-1
- Artificial intelligence
- Automotive industry
- Digital platform economy
- Organization of work