🌐 SAIGM™ — Szabo AI Governance Matrix

A Unified AI Governance Framework for High-Risk Sectors

Published by EAIG™ — EythicaAI™ Institute for AI Governance

# What is SAIGM™?

The Szabo AI Governance Matrix (SAIGM™) is a comprehensive governance framework designed to help organizations deploy Artificial Intelligence safely, ethically, and responsibly — especially in high-risk sectors such as:

Healthcare
Federal agencies
Finance
AI vendors
Regulated industries

SAIGM™ unifies:

Ethical AI principles
Privacy & data protection
Risk, security, and compliance
AI lifecycle governance

Into one practical, actionable framework.

# Why SAIGM™ Was Created

AI introduces new risks that traditional frameworks (HIPAA, GDPR, NIST, ISO) were not built to manage:

Inference privacy
Emergent model behavior
Model drift
Algorithmic bias
Autonomous decisions
PHI/PII sensitivity
Regulatory uncertainty

SAIGM™ fills this gap by integrating ethics, privacy, security, and lifecycle controls into one model.

# The Four Dimensions of SAIGM™

1️⃣ Ethical Foundations

Anchoring AI in human values, dignity, and fairness.
Includes: transparency, explainability, oversight, accountability.

2️⃣ Privacy & Data Protection

Ensuring lawful, ethical, and privacy-preserving use of data.
Includes: minimization, PHI/PII controls, inference risk reduction, lineage.

3️⃣ Risk, Security & Compliance

Protecting organizations from threats, legal exposure, and operational failures.
Includes: threat modeling, robustness, safety, vendor oversight, HIPAA/GDPR/NIST/ISO alignment.

4️⃣ AI Lifecycle Governance

Governing AI from idea → development → deployment → monitoring → retirement.
Includes: testing, validation, drift detection, continuous monitoring.

# SAIGM™ Matrix Overview

DimensionPurposeExamplesEthical FoundationsGround AI in human valuesFairness, transparency, oversightPrivacy & Data ProtectionReduce privacy + inference riskData minimization, lineage, PHI/PII controlsRisk, Security & ComplianceReduce threats + legal riskHIPAA/GDPR mapping, safety, vendor governanceAI Lifecycle GovernanceGovern AI end-to-endTesting, monitoring, drift, decommissioning

# Healthcare Addendum (SAIGM-HC™)

Healthcare faces unique AI risks:

Clinical decision support impact
PHI inference + re-identification
Bias affecting patient outcomes
FDA SaMD alignment
HIPAA + state law considerations

SAIGM-HC™ includes controls for:

Clinical AI validation
Model safety oversight
PHI governance
Bias + equity audits
Clinical transparency
Patient-facing explainability

# Use Cases

✔ Healthcare systems — radiology AI, CDS, predictive analytics
✔ Federal agencies + contractors — NIST AI RMF alignment
✔ AI vendors — governance-by-design, lifecycle documentation
✔ Financial institutions — AML/KYC, fraud, risk scoring

# SAIGM™ Maturity Model

Level 1 — Ad Hoc
Little or no governance.

Level 2 — Emerging
Basic policies; inconsistent practices.

Level 3 — Managed
Defined roles + repeatable processes.

Level 4 — Integrated
Cross-functional governance + monitoring.

Level 5 — Optimized
Continuous improvement; CAIGO™-trained workforce.

# CAIGO™ — Certified AI Governance Officer

SAIGM™ is the foundation for the CAIGO™ certification — the first credential focused entirely on AI governance.

CAIGO™ validates competencies in:

Ethical AI
Privacy & inference risk
Regulatory compliance (HIPAA, GDPR, ISO 42001)
AI lifecycle oversight
Bias + fairness
Monitoring & drift management
Governance program design

Issued by EAIG™ — EythicaAI™ Institute for AI Governance
Founding Cohort Coming Soon

# About EAIG™

The EythicaAI™ Institute for AI Governance (EAIG™) is a professional standards organization dedicated to:

Ethical AI
Governance frameworks
Certification programs
Research & publications
AI maturity modeling