It’s all in your head—naturalness arguments do not require aleatoric uncertainty
2026/04/20 by Andrew Fowlie · 1 voice
Arts and Humanities · Computer Science · Physics and Astronomy · #Bayesian inference #Bayesian probability #Bayesian statistics #Epistemology, Ethics, and Metaphysics #Frequentist probability #Gaussian Processes and Bayesian Inference #Head (geology) #Naturalness #Philosophy and History of Science #hep-ph #physics.data-an #physics.hist-ph
paper · pdf · doi:10.1007/s11229-026-05573-2
published in Synthese 207(5) (Springer Science+Business Media)
arxiv published 2026/04/20 · arxiv updated 2026/04/20 · openalex created_date 2026/04/24 · openalex publication_date 2026/05/04 · openalex updated_date 2026/08/05
Abstract
Prompted by misconceptions in the recent literature, we review the justifications for naturalness arguments and Occam's razor found in Bayesian statistics. We discuss the automatic Occam's razor that emerges in Bayesian formalism, bringing together points of view from diverse fields, including statistics, social sciences, physics and machine learning. In pedagogical calculations, we demonstrate that this automatic razor disfavors unnatural models in which predictions must be fine-tuned to agree with observation.
Citations
- The Intrinsic and Extrinsic Hierarchy Problems
- What is the Hierarchy Problem?
- Why probability probably doesn’t exist (but it is useful to act like it does)
- Diagnosing the Misuse of the Bayes Factor in Applied Research
- Bayesian Model Selection, the Marginal Likelihood, and Generalization
- Workflow Techniques for the Robust Use of Bayes Factors
- The Practice of Naturalness: A Historical-Philosophical Perspective
- Two Notions of Naturalness
- Finetuned Cancellations and Improbable Theories
- Naturalness, Extra-Empirical Theory Assessments, and the Implications of Skepticism
- Screams for Explanation: Finetuning and Naturalness in the Foundations of Physics
- Bayesian analysis and naturalness of (Next-to-)Minimal Supersymmetric Models
- Bayesian naturalness, simplicity, and testability applied to the B-L MSSM GUT
- Naturalness made easy: two-loop naturalness bounds on minimal SM extensions
- Naturalness of the relaxion mechanism
- The expected demise of the Bayes factor
- Naturalness Under Stress
- Is the CNMSSM more credible than the CMSSM?
- CMSSM, naturalness and the "fine-tuning price" of the Very Large Hadron Collider
- Bayesian naturalness of the CMSSM and CNMSSM
- Naturalness and the Status of Supersymmetry
- Should we still believe in constrained supersymmetry?
- Quantified naturalness from Bayesian statistics
- MSSM forecast for the LHC
- Bayes, Jeffreys, Prior Distributions and the Philosophy of Statistics
- Which fine-tuning arguments are fine?
- Bayesian approach and naturalness in MSSM analyses for the LHC
- Harold Jeffreys’s Theory of Probability Revisited
- Naturally Speaking: The Naturalness Criterion and Physics at the LHC
- New measure of fine tuning
- Natural priors, CMSSM fits and LHC weather forecasts
- Naturalness Priors and Fits to the Constrained Minimal Supersymmetric Standard Model
- Naturalness of supersymmetric models
- Natural ranges of supersymmetric signals
- Naturalness bounds on gauge mediated soft terms
- Statistical Inference, Occam's Razor and Statistical Mechanics on The Space of Probability Distributions
- Measures of fine tuning
- One-Loop Analysis of the Electroweak Breaking in Supersymmetric Models and the Fine-Tuning Problems
- Information-Based Objective Functions for Active Data Selection
- A Practical Bayesian Framework for Backpropagation Networks
- On the Self-Energy and the Electromagnetic Field of the Electron
- Bayesian Inductive Inference and Maximum Entropy
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