Report
The frame problem in quantitative practice: ontological uncertainty and epistemic humility in an age of automated inference
| Title: | The frame problem in quantitative practice: ontological uncertainty and epistemic humility in an age of automated inference |
|---|---|
| Authors: | Fauriat, William |
| Contributors: | DAM Île-de-France (DAM/DIF), Direction des Applications Militaires (DAM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA) |
| Source: | https://cea.hal.science/cea-05627052 ; 2026. |
| Publisher Information: | CCSD |
| Publication Year: | 2026 |
| Collection: | HAL-CEA (Commissariat à l'énergie atomique et aux énergies alternatives) |
| Subject Terms: | epistemic humility, frame problem, ontological uncertainty, automated inference, uncertainty quantification, machine learning, statistical decision theory, conformal prediction, model adequacy, [STAT.ME]Statistics [stat]/Methodology [stat.ME], [STAT.OT]Statistics [stat]/Other Statistics [stat.ML] |
| Description: | Quantitative practice across statistics, engineering, and machine learning has been transformed by the automation of inference. Predictions are produced, validated, and deployed at scale and speed that human-mediated reasoning could not match. This shift intersects with a structural limit of reasoning that no methodological refinement dissolves: every inference rests on a finite specification of conditions, and what falls outside the specification does not appear as a widened uncertainty band -it does not appear at all. The choice of specification -the frame -is upstream of the inference and cannot be audited from inside the system that uses it. This paper offers a synthetic, application-oriented review. We argue that three categories of uncertainty operate in quantitative practice -aleatory, epistemic, and frame (or ontological) -and that the third, the residue of finite specification, is structurally invisible to formal analysis within the chosen frame and is the locus of most consequential failures. We trace why the limit applies equally to deductive and inductive reasoning, why no meta-level procedure dissolves the regress, and why current conditions of automated inference make epistemic humility -the practical disposition this argument supports -more, not less, important. We articulate the argument's specific resonances for five typical figures of contemporary quantitative work -the engineer, the statistician, the mathematician, the machine-learning practitioner, and the non-specialist recipient of expert claims -showing how the structural argument bears on each practice's natural defenses. The argument is not against rigor or against quantification; it is for distinguishing rigor earned within a frame from rigor with respect to the frame. |
| Document Type: | report |
| Language: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/arxiv/2605.23614; ARXIV: 2605.23614 |
| Availability: | https://cea.hal.science/cea-05627052 https://cea.hal.science/cea-05627052v1/document https://cea.hal.science/cea-05627052v1/file/frame_problem_article_WF.pdf |
| Rights: | https://creativecommons.org/licenses/by/4.0/ ; info:eu-repo/semantics/OpenAccess |
| Accession Number: | edsbas.A0691C5A |
| Database: | BASE |
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