Minds and Machines 20 (2):277-289 (2010)
| Abstract |
This article reveals that explanatory practice in software engineering is in accordance with pragmatic explanatory pluralism, which states that explanations should at least partially be evaluated by their practical use. More specifically, I offer a defense of the idea that several explanation-types are legitimate in software engineering, and that the appropriateness of an explanation-type depends on (a) the engineer’s interests, and (b) the format of the explanation-seeking question he asks, with this format depending on his interests. This idea is defended by considering examples that are representative for explanatory practice in software engineering. Different kinds of technological explanation are spelled out, and the dependence of their appropriateness on interests and question-formats is extensively illustrated
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| Keywords | Engineering Epistemic interests Explanation Explanatory pluralism Explanatory power |
| Categories | (categorize this paper) |
| DOI | 10.1007/s11023-010-9190-2 |
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References found in this work BETA
The Scientific Image.William Demopoulos & Bas C. van Fraassen - 1982 - Philosophical Review 91 (4):603.
The Cement of the Universe: A Study of Causation.John Leslie Mackie - 1974 - Oxford, England: Oxford, Clarendon Press.
The Common Mind: An Essay on Psychology, Society, and Politics.Philip Pettit - 1993 - Oxford University Press.
A Pragmatist Defense of Non-Relativistic Explanatory Pluralism in History and Social Science.Jeroen van Bouwel & Erik Weber - 2008 - History and Theory 47 (2):168–182.
Symposium on Explanations and Social Ontology 3: Can We Dispense with Structural Explanations of Social Facts?Erik Weber & Jeroen Van Bouwel - 2002 - Economics and Philosophy 18 (2):259-275.
View all 15 references / Add more references
Citations of this work BETA
A Pragmatic Account of Mechanistic Artifact Explanation.Jan De Winter - 2011 - Studies in History and Philosophy of Science Part A 42 (4):602-609.
What Do We Want From Explainable Artificial Intelligence (XAI)? – A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research.Markus Langer, Daniel Oster, Timo Speith, Lena Kästner, Kevin Baum, Holger Hermanns, Eva Schmidt & Andreas Sesing - 2021 - Artificial Intelligence 296:103473.
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