Is Ockham’s razor losing its edge? New perspectives on the principle of model parsimony
Marina Dubova mdubova@santafe.edu, Suyog Chandramouli, Gerd Gigerenzer, +11 , and Sabina J. Sloman
Edited by Wilson Geisler, The University of Texas at Austin, Austin, TX; received March 8, 2024; accepted November 19, 2024
January 27, 2025
122 (5) e2401230121
https://doi.org/10.1073/pnas.2401230121
The preference for simple explanations, known as the parsimony principle, has long guided the development of scientific theories, hypotheses, and models. Yet recent years have seen a number of successes in employing highly complex models for scientific inquiry (e.g., for 3D protein folding or climate forecasting). In this paper, we reexamine the parsimony principle in light of these scientific and technological advancements. We review recent developments, including the surprising benefits of modeling with more parameters than data, the increasing appreciation of the context-sensitivity of data and misspecification of scientific models, and the development of new modeling tools. By integrating these insights, we reassess the utility of parsimony as a proxy for desirable model traits, such as predictive accuracy, interpretability, effectiveness in guiding new research, and resource efficiency. We conclude that more complex models are sometimes essential for scientific progress, and discuss the ways in which parsimony and complexity can play complementary roles in scientific modeling practice.
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