Mechanistic explanation in engineering science
European Journal for Philosophy of Science 5 (3):349-375 (2015)
Abstract
In this paper I apply the mechanistic account of explanation to engineering science. I discuss two ways in which this extension offers further development of the mechanistic view. First, functional individuation of mechanisms in engineering science proceeds by means of two distinct sub types of role function, behavior function and effect function, rather than role function simpliciter. Second, it offers refined assessment of the explanatory power of mechanistic explanations. It is argued that in the context of malfunction explanations of technical systems, two key desiderata for mechanistic explanations, ‘completeness and specificity’ and ‘abstraction’, pull in opposite directions. I elaborate a novel explanatory desideratum to accommodate this explanatory context, dubbed ‘local specificity and global abstraction’, and further argue that it also holds for mechanistic explanations of malfunctions in the biological domain. The overall result is empirically-informed understanding of mechanistic explanation in engineering science, thus contributing to the ongoing project of understanding mechanistic explanation in novel or relatively unexplored domains. I illustrate these claims in terms of reverse engineering and malfunction explanations in engineering scienceDOI
10.1007/s13194-015-0111-3
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Citations of this work
Explaining Engineered Computing Systems’ Behaviour: the Role of Abstraction and Idealization.Nicola Angius & Guglielmo Tamburrini - 2017 - Philosophy and Technology 30 (2):239-258.
On the Structure and Epistemic Value of Function Ascriptions in Biology and Engineering Sciences.Erik Weber, Dingmar van Eck & Julie Mennes - 2019 - Foundations of Science 24 (3):559-581.
Six Theses on Mechanisms and Mechanistic Science.Stuart Glennan, Phyllis Illari & Erik Weber - 2022 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie 53 (2):143-161.
Integrating Artificial Intelligence in Scientific Practice: Explicable AI as an Interface.Emanuele Ratti - 2022 - Philosophy and Technology 35 (3):1-5.
Mechanist idealisation in systems biology.Dingmar van Eck & Cory Wright - 2020 - Synthese 199 (1-2):1555-1575.
References found in this work
Making Things Happen: A Theory of Causal Explanation.James Woodward - 2003 - Oxford University Press.
Explaining the Brain: Mechanisms and the Mosaic Unity of Neuroscience.Carl F. Craver - 2007 - Oxford University Press, Clarendon Press.
Thinking about mechanisms.Peter Machamer, Lindley Darden & Carl F. Craver - 2000 - Philosophy of Science 67 (1):1-25.