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A Critical Reflection on Automated ScienceInstrumental Perspectivism: Is AI Machine Learning Technology Like NMR Spectroscopy?

A Critical Reflection on Automated Science: Instrumental Perspectivism: Is AI Machine Learning... [The question, “Will science remain human?” expresses a worry that deep learning algorithms will replace scientists in making 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. Can the same norms that apply in that case be used to judge the reliability of Artificial Intelligence deep learning algorithms?] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Critical Reflection on Automated ScienceInstrumental Perspectivism: Is AI Machine Learning Technology Like NMR Spectroscopy?

Part of the Human Perspectives in Health Sciences and Technology Book Series (volume 1)
Editors: Bertolaso, Marta; Sterpetti, Fabio

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References (46)

Publisher
Springer International Publishing
Copyright
© Springer Nature Switzerland AG 2020
ISBN
978-3-030-25000-3
Pages
27 –42
DOI
10.1007/978-3-030-25001-0_3
Publisher site
See Chapter on Publisher Site

Abstract

[The question, “Will science remain human?” expresses a worry that deep learning algorithms will replace scientists in making 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. Can the same norms that apply in that case be used to judge the reliability of Artificial Intelligence deep learning algorithms?]

Published: Feb 6, 2020

Keywords: Instrumental perspectivism; Machine learning; Nuclear magnetic resonance spectroscopy; Artificial intelligence

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