The Eticas AI Risk Taxonomy: Open Infrastructure for Operationalizing AI Audits
The rapid deployment of AI systems across high-stakes domains has created urgent demand for standardized evaluation, yet the field remains fragmented across competing risk taxonomies that catalog risks without showing how an audit is executed. At least 74 AI risk taxonomies exist, and almost all stop at the catalog. The hard part of auditing is not naming a risk but operationalizing it: turning it into a test run against a real system, a measured value, a calibrated severity, and a defensible grade. This paper leads with that bridge. We present the operationalization layer Eticas has built and
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- Linked via arxiv authorGemma Galdon Clavell →
The Eticas AI Risk Taxonomy: Open Infrastructure for Operationalizing AI Audits
- Linked via arxiv authorPablo Accuosto →
The Eticas AI Risk Taxonomy: Open Infrastructure for Operationalizing AI Audits
- Linked via arxiv authorUsman Gohar →
The Eticas AI Risk Taxonomy: Open Infrastructure for Operationalizing AI Audits