Kieval, Phillip Hintikka and Westerblad, Oscar
(2024)
Deep Learning as Method-Learning: Pragmatic Understanding, Epistemic Strategies and Design-Rules.
In: UNSPECIFIED.
Abstract
We claim that scientists working with deep learning (DL) models exhibit a form of pragmatic understanding that is not reducible to or dependent on explanation. This pragmatic understanding comprises a set of learned methodological principles that underlie DL model design-choices and secure their reliability. We illustrate this action-oriented pragmatic understanding with a case study of AlphaFold2, highlighting the interplay between background knowledge of a problem and methodological choices involving techniques for constraining how a model learns from data. Building successful models requires pragmatic understanding to apply modelling strategies that encourage the model to learn data patterns that will facilitate reliable generalisation.
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