Why Simpler Computer Simulation Models Can Be Epistemically Better for Informing Decisions

2020/09/04 by Casey Helgeson, Vivek Srikrishnan, Klaus Keller +1 · 1 voice · 1 citation
Arts and Humanities · Social Sciences · #Climate Change Communication and Perception #Epistemology, Ethics, and Metaphysics #Philosophy and History of Science

paper · pdf · doi:10.1086/711501

openalex publication_date 2020/09/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

For computer simulation models to usefully inform climate risk management, uncertainties in model projections must be explored and characterized. Because doing so requires running the model many times over, and because computing resources are finite, uncertainty assessment is more feasible using models that demand less computer processor time. Such models are generally simpler in the sense of being more idealized, or less realistic. So modelers face a trade-off between realism and uncertainty quantification. Seeing this trade-off for the important epistemic issue that it is requires a shift in perspective from the established simplicity literature in philosophy of science.

Citations

• How to Tell When Simpler, More Unified, or LessAd HocTheories will Provide More Accurate Predictions
• The representative concentration pathways: an overview
• Exploratory Modeling for Policy Analysis
• On The Quantitative Definition of Risk

Cited by

• Investing in open and FAIR practices for more usable and equitable climate-risk research

Discussions

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