Failure Ontology: A Lifelong Learning Framework for Blind Spot Detection and Resilience Design
Yuan Sun, Hong Yi, Jinyuan Liu

TL;DR
This paper introduces a formal framework called Failure Ontology for detecting and addressing cognitive blind spots that lead to catastrophic failures in human life, supported by historical and individual case studies.
Contribution
It presents a novel taxonomy of blind spots, failure interaction patterns, and a theorem demonstrating the efficiency of failure-based learning over success-based learning.
Findings
Identified four types of cognitive blind spots.
Characterized five failure interaction patterns.
Proved the Failure Learning Efficiency Theorem.
Abstract
Personalized learning systems are almost universally designed around a single objective: help people acquire knowledge and skills more efficiently. We argue this framing misses the more consequential problem. The most damaging failures in human life-financial ruin, health collapse, professional obsolescence-are rarely caused by insufficient knowledge acquisition. They arise from the systematic absence of entire conceptual territories from a person's cognitive map: domains they never thought to explore because, from within their existing worldview, those domains did not appear to exist or to matter. We call such absences Ontological Blind Spots and introduce Failure Ontology (F), a formal framework for detecting, classifying, and remediating them across a human lifetime. The framework introduces three original contributions: (1) a four-type taxonomy of blind spots distinguishing domain…
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