Mussgnug, Alexander (2024) AI Operationalism: The case of international development. [Preprint]

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Abstract

Machine learning is rapidly transforming how society and humans are quantified. Shared amongst some machine learning applications in the social and human sciences is the tendency to conflate concepts with their operationalization through particular tests or measurements. Existing scholarship reduces these equations of concept and operationalization to disciplinary naivety or negligence. This paper takes a close look at equations of concept and operationalization in machine learning predictions of poverty metrics. It develops two arguments. First, I demonstrate that conflations of concept and operationalization in machine learning poverty prediction cannot be reduced to naivety or negligence but can serve a strategic function. Second, I propose to understand this function in the context of philosophical and historical research on operationalism in the social sciences.

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Item Type:	Preprint
Creators:	Creators Email ORCID Mussgnug, Alexander alexander@mussgnug.de 0000-0002-5951-057X
Keywords:	AI, Philosophy of AI, Development Economics, Machine Learning, Operationalism, Operationism
Subjects:	Specific Sciences > Artificial Intelligence Specific Sciences > Economics General Issues > Ethical Issues General Issues > Operationalism/Instrumentalism
Depositing User:	Mr Alexander Mussgnug
Date Deposited:	23 Jul 2025 17:00
Last Modified:	23 Jul 2025 17:00
Item ID:	26006
Subjects:	Specific Sciences > Artificial Intelligence Specific Sciences > Economics General Issues > Ethical Issues General Issues > Operationalism/Instrumentalism
Date:	2024
URI:	https://philsci-archive.pitt.edu/id/eprint/26006

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