New Textbook — First Edition, 2026

Governing Intelligence

Name: Governing Intelligence: Law, Privacy, Security, and Compliance in the Age of Artificial Intelligence
Author: Noah M. Kenney

Law, Privacy, Security, and Compliance in the Age of Artificial Intelligence

By Noah M. Kenney

First Edition, 2026

20 Chapters · 460+ Pages

Download Full PDF Read Online

Chapters spanning law, ethics, privacy, security, and compliance

Layers of the AI Governance Stack framework

40+

Jurisdictions and regulatory regimes analyzed

1st

Unified textbook mapping governance to the AI lifecycle

Why This Book Matters

The first comprehensive textbook on AI governance as a unified discipline.

Artificial intelligence is being deployed faster than the laws, institutions, and controls designed to govern it. Fragmented regulation across jurisdictions, rapidly evolving technical risks, and unclear accountability have left practitioners, counsel, and leaders without a shared reference for how to govern AI responsibly. Governing Intelligence closes that gap.

Drawing on years of advising regulated enterprises and teaching AI privacy engineering at the Georgia Institute of Technology, Noah M. Kenney presents a rigorous, practitioner-oriented framework that unifies legal, ethical, technical, and operational dimensions of AI governance into a single coherent discipline. The textbook translates the EU AI Act, GDPR, NIST AI RMF, ISO/IEC 42001, sector-specific regimes, and emerging state and international laws into actionable controls mapped to the AI system lifecycle.

01 / Practitioner-Ready

Built for Real Decisions

Every chapter moves from foundational concepts to implementation guidance, case studies, and discussion questions. Written for counsel, compliance officers, engineers, policymakers, and executives who must make defensible AI decisions today.

02 / Globally Scoped

One Book, Many Jurisdictions

Covers the EU AI Act, GDPR, United States federal and state regimes, the UK, China, emerging markets, and sector-specific laws in healthcare, financial services, education, and government — with explicit guidance on multi-jurisdictional compliance.

03 / Technically Grounded

Law Meets Engineering

Integrates privacy engineering, adversarial ML, model integrity, red-teaming, differential privacy, and synthetic data alongside the legal frameworks that depend on them — so technical and legal teams finally speak the same language.

The Framework

The AI Governance Stack — a five-layer model for responsible AI.

At the core of Governing Intelligence is the AI Governance Stack: a layered architecture that maps legal, ethical, and technical obligations to discrete, auditable points in the AI system lifecycle. Each layer translates abstract governance principles into concrete controls, evidence, and accountability — and each regulatory regime in the book is mapped back to these layers.

Layer 011

Data Governance — The Foundation

Provenance, lineage, lawful basis, quality, consent, and minimization. Everything downstream depends on the integrity and legitimacy of the data used to train, tune, and evaluate AI systems.

Layer 022

Model Governance

Model design, training, validation, documentation, versioning, fairness testing, and explainability — aligned to NIST AI RMF, ISO/IEC 42001, and sector standards.

Layer 033

System Integration Governance

How models are embedded into production systems, human workflows, and third-party infrastructure — including supply chain risk, vendor diligence, and API security.

Layer 044

Control & Monitoring Governance

Runtime oversight: drift detection, adversarial monitoring, incident response, human-in-the-loop controls, and the operational telemetry regulators increasingly require.

Layer 055

Audit & Evidence Governance

Documentation, model cards, impact assessments, audit trails, and the evidentiary record needed for internal audit, external regulators, and litigation.

Inside the Textbook

Twenty chapters across five integrated domains.

The textbook is structured as a progression from foundational principles through global law, privacy engineering, security, auditing, and sector-specific application — culminating in frontier model governance and the future of AI oversight.

The Imperative for AI Governance

Governance stack foundations · risk propagation

The AI Governance Stack

Five-layer implementation specification

Ethical Frameworks & Professional Responsibility

ACM Code · applied ethics · culture

The EU AI Act

Risk classification · high-risk systems · GPAI

United States AI Regulation

Federal, state, FTC, NIST, sectoral

Global AI Regulation

China, UK, emerging markets, harmonization

Intellectual Property and AI

The GDPR and AI

DPIAs · Article 22 · Schrems II · enforcement

U.S. Privacy Laws Applied to AI

CCPA/CPRA · state regimes · KOSPA · COPPA

Sector-Specific Privacy Regimes

HIPAA · GLBA · FERPA · de-identification

AI Privacy Engineering

Differential privacy · synthetic data · HE

Cybersecurity Foundations for AI Systems

ML security · model integrity · supply chain

AI-Specific Security Threats

Adversarial attacks · prompt injection · extraction

Security Frameworks & Standards

NIST AI RMF · ATLAS · ISO 42001 · OWASP

AI Auditing Methodologies

Bias audits · explainability · continuous audit

Building an AI Compliance Program

Policy · training · incident response

AI Governance in Healthcare

Clinical validation · radiology · CDS

AI Governance in Financial Services & Government

MRM · fair lending · public sector accountability

Generative AI & Frontier Model Governance

Foundation models · red-teaming · systemic risk

The Evolving AI Governance Landscape

Convergence · maturity · transformative AI

About the Author

Noah M. Kenney

Practitioner, Researcher, Educator

Founder & Principal Consultant, Digital 520 · President & Chief Scientist, Disruptive AI Lab · President, Ethical Tech Forum

Noah M. Kenney is the Founder and Principal Consultant of Digital 520, a global consultancy specializing in digital transformation, data privacy, AI governance, cybersecurity, and compliance. Digital 520 partners with regulated enterprises, high-growth companies, and mission-driven organizations to increase operational efficiency and drive organizational growth. In his role as Founder and Principal Consultant, Noah serves as fractional CTO and technology advisor to multiple organizations, has consulted on over 40 AI initiatives, and speaks globally on AI, governance, privacy, and secure systems design.

In addition to leading Digital 520, Noah serves as President and Chief Scientist of the Disruptive AI Lab, where he focuses on applying AI in high-risk and regulated environments, including healthcare and critical infrastructure. He also serves as President of the Ethical Tech Forum, a global think tank advancing responsible AI, privacy, and emerging technology governance.

Noah is recognized for his work in AI-driven medical diagnostics, including improving pneumonia detection using computationally efficient AI systems, for which he received a competitive research grant. He co-developed the country’s first AI Privacy Engineering course at the Georgia Institute of Technology. He holds over 50 advanced industry certifications, including the Certified Information Privacy Manager (CIPM) credential from the International Association of Privacy Professionals (IAPP). He earned his undergraduate degree in Economics with high honors from the Georgia Institute of Technology and a Master’s of Engineering from the University of Colorado Boulder.

CIPM — IAPP Georgia Tech, Economics (High Honors) M.Eng., CU Boulder 50+ Industry Certifications 40+ AI Engagements