Taxonomy of Artificial Standing Failure
Abstract
This paper presents a taxonomy of artificial standing failure. It classifies the distinct, exhaustive modes by which artificial epistemic agents lose standing, showing that failures are structural rather than behavioral or performance-based. Each class is defined by violations of admissibility, scope invariance, or standing conservation, and all apparent hybrids or partial failures are reduced to these categories by exhaustion. The taxonomy demonstrates why standing failure is binary, non-local, and non-repairable across architectures. No diagnostic algorithms, remediation steps, or implementation guidance are provided; the result is classificatory and necessity-based.
Fields of Study & Subjects
Ethics and Social Impacts of AI
Logic
Reasoning
and Knowledge
Epistemology
Ethics
and Metaphysics
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 8 February 2026