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Status Submitted
Created by Guest
Created on Nov 14, 2026

UNIVERSAL ADVANCED AI System Incident Reporting and Shared Learning Project Acronym: UAASIRSL

PROBLEM: The ai system incident reporting and shared learning gap is that AI governance is usually written as policy and practised as improvisation: thresholds, overrides, and rollbacks live in chat logs and memory instead of in a governed record. Operators need a single auditable ledger before they can claim human control is real.

SOLUTION: Storage Copy Data Management would orchestrate ai system incident reporting and shared learning as a repeatable workflow with explicit human checkpoints, requiring an accountable decision to be recorded before an autonomous action can proceed or continue. It designs the control process, not the model's behaviour.

EVIDENCE BASIS: DOCUMENTED — the NIST AI Risk Management Framework (2023) and the EU AI Act (Regulation (EU) 2024/1689) set the governance duties this record would track; frontier-model safety evaluations, including published 2025 evaluations by leading labs, are documented practice. Source: NIST AI RMF; EU AI Act; published model evaluations.

Idea priority Low