The Logic of Proof of Concept Research

Abstract Proof of Concept Research (PoCR) is a prevalent facet of scientific inquiry, yet its epistemic features remain poorly understood. While novelty has been highlighted as a key characteristic, projectability—understood as the likelihood of being applicable to a broader range of contexts—is another. This study endeavours to construct a formal model that elucidates the implicit ampliative reasoning inherent in PoCR. Our model hinges on probability assumptions for target objects to simultaneously exhibit three properties: one that is a defining characteristic of these target objects; a second that is desired of them and whose demonstration is the empirical aim of PoCR; and a third that is promised in the background. Depending on assumptions about when these properties jointly obtain, we delineate paradigmatic, alternative, and tangential modes of reasoning. This classification and associated decision tree unveil distinct argumentative strategies that, despite not being deductively valid, may be employed to motivate PoCR and justify subsequent inferences upon successful proof of concept demonstration. The model and decision tree together provide a framework with which to better understand the general structure of widely used inferences in PoCR, and with which researchers and evaluators can more precisely design and assess PoCR projects.

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Publication Details

Journal
Mind
Published
2025-08-08
DOI
https://doi.org/10.1093/mind/fzaf051
Primary Topic
Philosophy and History of Science
Type
article
Field-Weighted Citation Impact
0.00
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article

The Logic of Proof of Concept Research

Philippe Nghe, Christophe Malaterre
Mind
Philosophy and History of Science
article

The Logic of Proof of Concept Research

Philippe Nghe, Christophe Malaterre
article en

Abstract

Abstract Proof of Concept Research (PoCR) is a prevalent facet of scientific inquiry, yet its epistemic features remain poorly understood. While novelty has been highlighted as a key characteristic, projectability—understood as the likelihood of being applicable to a broader range of contexts—is another. This study endeavours to construct a formal model that elucidates the implicit ampliative reasoning inherent in PoCR. Our model hinges on probability assumptions for target objects to simultaneously exhibit three properties: one that is a defining characteristic of these target objects; a second that is desired of them and whose demonstration is the empirical aim of PoCR; and a third that is promised in the background. Depending on assumptions about when these properties jointly obtain, we delineate paradigmatic, alternative, and tangential modes of reasoning. This classification and associated decision tree unveil distinct argumentative strategies that, despite not being deductively valid, may be employed to motivate PoCR and justify subsequent inferences upon successful proof of concept demonstration. The model and decision tree together provide a framework with which to better understand the general structure of widely used inferences in PoCR, and with which researchers and evaluators can more precisely design and assess PoCR projects.

Mind
École Polytechnique (FR), Université du Québec à Montréal (CA)
Peace, Justice and strong institutions
Openalex Percentile: Top 12%
Philosophy and History of Science
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