The Multidimensional Epistemology of Computer Simulations: Novel Issues and the Need to Avoid the Drunkard’s Search Fallacy
Computers have transformed science and help to extend the boundaries of human knowledge. However, does the validation and diffusion of results of computational inquiries and computer simulations call for a novel epistemological analysis? I discuss how the notion of novelty should be cashed out to investigate this issue meaningfully and argue that a consequentialist framework similar to the one used by Goldman to develop social epistemology can be helpful at this point. I highlight computational, mathematical, representational, and social stages on which the validity of simulation-based belief-generating processes hinges, and emphasize that their epistemic impact depends on the scientific practices that scientists adopt at these different stages. I further argue that epistemologists cannot ignore these partially novel issues and conclude that the epistemology of computational inquiries needs to go beyond that of models and scientific representations and has cognitive, social, and in the present case computational, dimensions.
KeywordsComputer simulations Novelty Epistemology Validation Goldman Consequentialism Social epistemology Random numbers Computational values Monte Carlo Random number generator Modeling norms Modularity Opacity Verification Reproducibility Models Invisibleness of failure Naturalism
Past interactions with Roman Frigg, Stephan Hartmann, and Paul Humphreys about various issues discussed in this chapter were extremely stimulating, and I probably owe them more than I am aware of. I am also very grateful to the editors, whose comments contributed significantly to improving this chapter.
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