Unified Integrity Standard: Requirements, Scoring, and Enforcement
Integrity Requirements
AI systems must be built on lawful and verifiable data origins.
Organizations must maintain transparent governance and oversight of AI development and deployment.
Institutions must demonstrate responsible procurement practices and verify vendor claims.
AI deployments must be documented and traceable across their lifecycle.
Synthetic data, if used, must be responsibly managed and clearly disclosed.
Organizations must retain the ability to exit or replace vendors without obstruction.
Systems must operate within a framework that supports accountability and long‑term stewardship.
Integrity Scoring Model
ATIC assigns each system an Integrity Score based on seven dimensions:
1. Provenance Completeness
Whether all data sources have documented, lawful origins.
2. Lineage Transparency
Whether dataset transformations are fully traceable and auditable.
3. Contamination Risk
The presence of illegal, duplicated, or misattributed data.
4. Synthetic Exposure
The degree to which synthetic data is used, labeled, isolated, and controlled.
5. Structural Integrity
The dataset’s internal consistency, duplication rate, and corruption risk.
6. Vendor Independence
Whether the institution can migrate or replace the system without obstruction.
7. Governance Maturity
Documentation quality, audit readiness, and internal oversight.
The Integrity Score determines:
certification eligibility
certification tier
placement in the Public Registry of Certified Systems
Compliance & Enforcement
Institutions certified under the Standard must:
maintain complete documentation
undergo periodic audits
report material changes to datasets or models
renew certification annually
disclose any integrity failures or contamination events
Non‑compliance results in:
score reduction
certification suspension
public registry updates
revocation in severe cases
ATIC enforces the Standard independently and without commercial influence.