Amoore, L. (2019) 'Doubt and the algorithm : on the partial accounts of machine learning.', Theory, culture & society., 36 (6). pp. 147-169.
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.
|Full text:||(AM) Accepted Manuscript|
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|Publisher Web site:||https://doi.org/10.1177/0263276419851846|
|Publisher 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.|
|Date accepted:||29 November 2018|
|Date deposited:||05 December 2018|
|Date of first online publication:||26 June 2019|
|Date first made open access:||No date available|
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