Mitchell, Sandra D. (2019) Instrumental Perspectivism: Is AI Machine Learning Technology like NMR Spectroscopy? [Preprint]
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Abstract
The question, “Will science remain human?” expresses a worry that deep learning algorithms will replace scientists in making crucial judgments of classification and inference and that something crucial will be lost if that happens. Ever since the introduction of telescopes and microscopes humans have relied on technologies to “extend” beyond human sensory perception in acquiring scientific knowledge. In this paper I explore whether the ways in which new learning technologies “extend” beyond human cognitive aspects of science can be treated instrumentally. I will consider the norms for determining the reliability of a detection instrument, nuclear magnetic resonance spectroscopy, in predicting models of protein atomic structure. Do the same norms that apply in that case be used to judge the reliability of Artificial Intelligence deep learning algorithms?
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| Item Type: | Preprint | ||||||
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| Additional Information: | in M. Bertolaso and F. Sterpetti (eds) Will Science Remain Human, Springer (forthcoming). | ||||||
| Keywords: | Deep Learning, NMR Spectroscopy, Experiment, | ||||||
| Subjects: | Specific Sciences > Chemistry Specific Sciences > Computer Science General Issues > Experimentation General Issues > Theory/Observation |
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| Depositing User: | Sandra D. Mitchell | ||||||
| Date Deposited: | 23 Feb 2019 22:09 | ||||||
| Last Modified: | 23 Feb 2019 22:09 | ||||||
| Item ID: | 15738 | ||||||
| Subjects: | Specific Sciences > Chemistry Specific Sciences > Computer Science General Issues > Experimentation General Issues > Theory/Observation |
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| Date: | 12 February 2019 | ||||||
| URI: | https://philsci-archive.pitt.edu/id/eprint/15738 |
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