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◆ Computational brain & behavior2026-09-01

Understandable Lack of Understanding.

Angelos-Miltiadis Krypotos

原始摘要(英文原文)· Original abstract
Shiffrin, Stigler, and Keil argue that scientists often overestimate the depth of their understanding, even in simple statistical contexts. While their analysis of regression and related paradoxes shows compellingly that predictive success need not imply explanatory mastery, the present commentary questions if partial understanding should necessarily be epistemically problematic. I argue that incomplete explanation is a structural feature of scientific progress rather than necessarily an illusion. The challenge is to acknowledge the limits of models without undermining science's epistemic status. In this vein, scientific education should emphasize nuanced explanation of the world while maintaining clear standards distinguishing well-grounded explanations from unfounded alternatives.
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