Ratti, Emanuele and Termine, Alberto and Facchini, Alessandro (2025) Machine Learning and Theory-Ladenness: A Phenomenological Account. [Preprint]

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Abstract

We provide an analysis of theory-ladenness in machine learning (ML) in science, where ‘theory’ (that we call 'domain-theory') refers to the domain knowledge of the scientific discipline where ML is used. By constructing an account of ML models based on a comparison with phenomenological models, we show (against recent trends in philosophy of science) that ML model-building is mostly indifferent to domain-theory, even if the model remains theory-laden in a weak sense, which we call theory-infection. These claims, we argue, have far-reaching consequences for the transferability of ML across scientific disciplines, and shift the priorities of the debate on theory-ladenness in ML from descriptive to normative.

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Item Type:	Preprint
Creators:	Creators Email ORCID Ratti, Emanuele mnl.ratti@gmail.com 0000-0003-1409-8240 Termine, Alberto alberto.termine@unimi.it 0000-0001-5993-0948 Facchini, Alessandro alessandro.facchini@idsia.ch 0000-0001-7507-116X
Additional Information:	Draft. Comments are welcome.
Keywords:	machine learning theory-ladenness phenomenological models scientific modelling
Subjects:	General Issues > Data Specific Sciences > Artificial Intelligence > Machine Learning General Issues > Models and Idealization General Issues > Technology General Issues > Theory Change General Issues > Theory/Observation
Depositing User:	Dr Emanuele Ratti
Date Deposited:	02 Oct 2025 10:40
Last Modified:	02 Oct 2025 10:40
Item ID:	26802
Subjects:	General Issues > Data Specific Sciences > Artificial Intelligence > Machine Learning General Issues > Models and Idealization General Issues > Technology General Issues > Theory Change General Issues > Theory/Observation
Date:	2025
URI:	https://philsci-archive.pitt.edu/id/eprint/26802

Available Versions of this Item

• Machine Learning and Theory-Ladenness: A Phenomenological Account. (deposited 05 Sep 2024 12:51)
  • Machine Learning and Theory-Ladenness: A Phenomenological Account. (deposited 22 Aug 2025 14:36)
    • Machine Learning and Theory-Ladenness: A Phenomenological Account. (deposited 02 Oct 2025 10:40) [Currently Displayed]

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