Predictive Epistemology: Complexity, Evolutionary Epistemology, and the Anticipation of Scientific Change

Predictive Epistemology is developed here as a philosophical framework for identifying structural signs that an established scientific framework is becoming increasingly difficult to sustain before major theoretical reorganization occurs. Building on Effective Complexity and its constrained formalization, the framework asks how the minimum theoretical complexity required to preserve a specified level of explanatory or empirical adequacy changes as empirical demands accumulate. Theoretical stress is defined as a sustained baseline-relative increase in this constrained explanatory cost. Epistemic fragility is treated separately as reduced robustness of a framework’s capacity to preserve adequacy under further relevant demands; a tipping-region diagnosis therefore requires theoretical stress together with independent evidence of declining robustness. The framework does not seek to predict the content or exact timing of successor theories. It is situated as a complement to evolutionary epistemology and examined through evolutionary biology as a reflexive test case. Three possibilities are distinguished: productive extension, stable pluralism, and theoretical stress. A minimal qualitative illustration based on niche construction shows why increased theoretical content does not by itself constitute stress, while a worked longitudinal reconstruction of the old quantum theory illustrates how the diagnostic procedure can distinguish productive extension from a later period of increasing accommodation cost. Predictive Epistemology thus offers a prospective, context-dependent, and in-principle testable framework for investigating the changing stability of scientific theories.

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Journal
Philosophies
Published
2026-11-01
DOI
https://doi.org/10.3390/philosophies11060203
Primary Topic
Philosophy and History of Science
Type
article
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article

Predictive Epistemology: Complexity, Evolutionary Epistemology, and the Anticipation of Scientific Change

Miguel Fuentes
Philosophies
Philosophy and History of Science
article

Predictive Epistemology: Complexity, Evolutionary Epistemology, and the Anticipation of Scientific Change

Miguel Fuentes
article en

Abstract

Predictive Epistemology is developed here as a philosophical framework for identifying structural signs that an established scientific framework is becoming increasingly difficult to sustain before major theoretical reorganization occurs. Building on Effective Complexity and its constrained formalization, the framework asks how the minimum theoretical complexity required to preserve a specified level of explanatory or empirical adequacy changes as empirical demands accumulate. Theoretical stress is defined as a sustained baseline-relative increase in this constrained explanatory cost. Epistemic fragility is treated separately as reduced robustness of a framework’s capacity to preserve adequacy under further relevant demands; a tipping-region diagnosis therefore requires theoretical stress together with independent evidence of declining robustness. The framework does not seek to predict the content or exact timing of successor theories. It is situated as a complement to evolutionary epistemology and examined through evolutionary biology as a reflexive test case. Three possibilities are distinguished: productive extension, stable pluralism, and theoretical stress. A minimal qualitative illustration based on niche construction shows why increased theoretical content does not by itself constitute stress, while a worked longitudinal reconstruction of the old quantum theory illustrates how the diagnostic procedure can distinguish productive extension from a later period of increasing accommodation cost. Predictive Epistemology thus offers a prospective, context-dependent, and in-principle testable framework for investigating the changing stability of scientific theories.

PhilosophiesVol. 11(6)
Santa Fe Institute (US), Sociedad Argentina de Análisis Filosófico (AR)
Openalex Percentile: Top 4%
Philosophy and History of Science
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