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Doubt and the Algorithm: On the Partial Accounts of Machine Learning

Amoore, L.

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Abstract

In a 1955 lecture the physicist Richard Feynman reflected on the place of doubt within scientific practice. ‘Permit us to question, to doubt, to not be sure’, proposed Feynman, ‘it is possible to live and not to know’. In our contemporary world, the science of machine learning algorithms appears to transform the relations between science, knowledge and doubt, to make even the most doubtful event amenable to action. What might it mean to ‘leave room for doubt’ or ‘to live and not to know’ in our contemporary culture, where the algorithm plays a major role in the calculability of doubts? I propose a posthuman mode of doubt that decentres the liberal humanist subject. In the science of machine learning algorithms the doubts of human and technological beings nonetheless dwell together, opening onto a future that is never fully reduced to the single output signal, to the optimised target.

Citation

Amoore, L. (2019). Doubt and the Algorithm: On the Partial Accounts of Machine Learning. Theory, Culture and Society, 36(6), 147-169. https://doi.org/10.1177/0263276419851846

Journal Article Type Article
Acceptance Date Nov 29, 2018
Online Publication Date Jun 26, 2019
Publication Date Nov 1, 2019
Deposit Date Dec 4, 2018
Publicly Available Date Mar 29, 2024
Journal Theory, Culture and Society
Print ISSN 0263-2764
Electronic ISSN 1460-3616
Publisher SAGE Publications
Peer Reviewed Peer Reviewed
Volume 36
Issue 6
Pages 147-169
DOI https://doi.org/10.1177/0263276419851846

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Copyright Statement
Amoore, L. (2019). Doubt and the Algorithm: On the Partial Accounts of Machine Learning. Theory, Culture & Society 36(6): 147-169. Copyright © 2018 The Author(s). Reprinted by permission of SAGE Publications.





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