Abstract
This paper addresses two methodological paths in Artificial Intelligence: the paths of Babbage and anti-Cartesianism. While those researchers who have followed the latter have attempted to reverse the Cartesian dictum according to which machines cannot think in principle, Babbage’s path, which has been partially neglected, implies that the replacement of humans—and not the creation of minds—should provide the foundation of AI. In view of the examined paths, the claim that we support here is this: in line with Babbage, AI researchers have recently concentrated upon the replacement of human labour, and thus upon the creation of Machine Learning systems. After presenting and analysing the paths, we characterise Machine Learning via its developments and an illustrative example. Then, we put forward an argument that shows that total replacement of human labour will not be feasible for practical and conceptual reasons despite the successful developments in recent AI systems. Our discussion finally leads to optimism and awareness: AI’s advances allow humans to dedicate themselves to higher level tasks, but these advances also require that we be vigilant about the responsibilities granted to ML-based systems.

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One can even argue that a rich technocrat might decide to fully automate the factory, from the most basic operation task to the top-level decision-making manager position. If this were to be achieved, the purpose of automation still follows from a human intention: the wealthy madman is the head of this endeavour sitting at the top of the idealised factory that has been automated for the sole purpose of fulfilling his desires.
As suggested by an anonymous reviewer, although there always be work (as in the film Nomadland, 2020), that does not allay concerns about mass social displacement by automation. However, the point is whether such concerns are justified, not from our psychlogical distress, but from the existence of facts.
Paraphrasing Milton Friedman’s comment to an Asian bureaucrat on a construction site which used manual labour instead of modern tractors as part of a jobs programme.
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Acknowledgement
We are very grateful to John Preston (University of Reading) for asking thought-provoking questions that helped shape the current version of this article. We also thank Anita Tobar-Henríquez (University of Edinburgh) and Matı́as Mattamala (University of Oxford) for feedback on earlier versions of this work. This work was supported by the Google-APRU project Artificial Intelligence for Everyone and ANID grants AFB170001 (CMM), FB0008 (AC3E) and Fondecyt-Iniciación 11171165.
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Tobar, F., González, R. On machine learning and the replacement of human labour: anti-Cartesianism versus Babbage’s path. AI & Soc 37, 1459–1471 (2022). https://doi.org/10.1007/s00146-021-01264-3
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DOI: https://doi.org/10.1007/s00146-021-01264-3