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What kind of learning is machine learning?
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Reigeluth, Tyler and Castelle, Michael (2020) What kind of learning is machine learning? In: Roberge, Jonathan and Castelle, Michael, (eds.) The Cultural Life of Machine Learning : An Incursion into Critical AI Studies. Cham, Switzerland: Palgrave Macmillan, pp. 79-115. ISBN 9783030562854
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Official URL: https://doi.org/10.1007/978-3-030-56286-1_3
Abstract
While theories of human learning have proliferated in the last century, machine learning is a rather less reflexive enterprise. What conception of learning do the techniques of machine learning—especially in its recent connectionist forms—imply or induce? To answer this question, we explore the perspectives of the Soviet cultural-historical psychologist Lev Vygotsky, contrasting his socially-grounded understandings of mediated concept learning and the “zone of proximal development” with the methodologies of supervised and unsupervised machine learning. Such a comparison highlights the dependence of machine learning on microgenesis (repetitive, behaviorist training processes) and phylogenesis (the architectural “evolution” of models) at the expense of ontogenesis (the lifelong, interactional development of an individual in society), and thus provides new insights into the fundamental limits of contemporary artificial intelligence.
Item Type: | Book Item | ||||
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Subjects: | H Social Sciences > HM Sociology Q Science > Q Science (General) |
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Divisions: | Faculty of Social Sciences > Centre for Interdisciplinary Methodologies | ||||
Library of Congress Subject Headings (LCSH): | Machine learning, Learning, Psychology of, Artificial intelligence | ||||
Publisher: | Palgrave Macmillan | ||||
Place of Publication: | Cham, Switzerland | ||||
ISBN: | 9783030562854 | ||||
Book Title: | The Cultural Life of Machine Learning : An Incursion into Critical AI Studies | ||||
Editor: | Roberge, Jonathan and Castelle, Michael | ||||
Official Date: | 1 December 2020 | ||||
Dates: |
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Number of Pages: | 289 | ||||
Page Range: | pp. 79-115 | ||||
DOI: | 10.1007/978-3-030-56286-1_3 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Date of first compliant deposit: | 27 April 2022 | ||||
Date of first compliant Open Access: | 27 April 2022 | ||||
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