Software Intensive Science

Philosophy and Technology 27 (3):461-477 (2014)
Authors
John Symons
University of Kansas
Abstract
This paper argues that the difference between contemporary software intensive scientific practice and more traditional non-software intensive varieties results from the characteristically high conditionality of software. We explain why the path complexity of programs with high conditionality imposes limits on standard error correction techniques and why this matters. While it is possible, in general, to characterize the error distribution in inquiry that does not involve high conditionality, we cannot characterize the error distribution in inquiry that depends on software. Software intensive science presents distinctive error and uncertainty modalities that pose new challenges for the epistemology of science
Keywords Models  Simulations  Software  Epistemology  Complexity  Post-human science
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DOI 10.1007/s13347-014-0163-x
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References found in this work BETA

How Scientific Models Can Explain.Alisa Bokulich - 2011 - Synthese 180 (1):33 - 45.
Idealization and Modeling.Robert Batterman - 2009 - Synthese 169 (3):427-446.
The Foundations of Scientific Inference.Wesley C. Salmon - 1966 - University of Pittsburgh Press.

View all 18 references / Add more references

Citations of this work BETA

Reply to Angius and Primiero on Software Intensive Science.Jack Horner & John Symons - 2014 - Philosophy and Technology 27 (3):491-494.

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