Ontology, neural networks, and the social sciences
Authors
Publication Date
2020-12-28Journal Title
Synthese
ISSN
0039-7857
Publisher
Springer Science and Business Media LLC
Volume
199
Issue
1-2
Pages
4775-4794
Language
en
Type
Article
This Version
VoR
Metadata
Show full item recordCitation
Strohmaier, D. (2020). Ontology, neural networks, and the social sciences. Synthese, 199 (1-2), 4775-4794. https://doi.org/10.1007/s11229-020-03002-6
Description
Funder: Cambridge Assessment, University of Cambridge
Abstract
<jats:title>Abstract</jats:title><jats:p>The ontology of social objects and facts remains a field of continued controversy. This situation complicates the life of social scientists who seek to make predictive models of social phenomena. For the purposes of modelling a social phenomenon, we would like to avoid having to make any controversial ontological commitments. The overwhelming majority of models in the social sciences, including statistical models, are built upon ontological assumptions that can be questioned. Recently, however, artificial neural networks (ANNs) have made their way into the social sciences, raising the question whether they can avoid controversial ontological assumptions. ANNs are largely distinguished from other statistical and machine learning techniques by being a representation-learning technique. That is, researchers can let the neural networks select which features of the data to use for internal representation instead of imposing their preconceptions. On this basis, I argue that neural networks can avoid ontological assumptions to a greater degree than common statistical models in the social sciences. I then go on, however, to establish that ANNs are not ontologically innocent either. The use of ANNs in the social sciences introduces ontological assumptions typically in at least two ways, via the input and via the architecture.</jats:p>
Keywords
Article, Neural networks, Philosophy of social science, Prediction, Statistical models, Ontological assumptions
Identifiers
s11229-020-03002-6, 3002
External DOI: https://doi.org/10.1007/s11229-020-03002-6
This record's URL: https://www.repository.cam.ac.uk/handle/1810/330891
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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