This book provides the first comprehensive architecture for designing accountable, auditable, and enforceable AI systems. Moving beyond principles and policy debates, this book introduces lifecycle governance models, responsibility matrices, audit trail frameworks, and compliance scoring systems that embed ethics directly into system design.
The book is written for AI engineers, governance architects, regulators, and advanced graduate students. It equips readers with the tools needed to transform ethical aspiration into operational reality in an era of mandatory AI audits and liability enforcement.
The book introduces the following key modules:
This book provides the first comprehensive architecture for designing accountable, auditable, and enforceable AI systems. Moving beyond principles and policy debates, this book introduces lifecycle governance models, responsibility matrices, audit trail frameworks, and compliance scoring systems that embed ethics directly into system design.
The book is written for AI engineers, governance architects, regulators, and advanced graduate students. It equips readers with the tools needed to transform ethical aspiration into operational reality in an era of mandatory AI audits and liability enforcement.
The book introduces the following key modules:
Vijay A. Kanade
Operational AI ethics AI governance architecture Accountable AI systems AI lifecycle governance Algorithmic accountability Responsible AI implementation AI audit and compliance frameworks Ethical AI governance AI risk management frameworks Auditable AI systems AI regulatory compliance Post-deployment AI monitoring AI accountability engineering Governance frameworks for artificial intelligence Philosophy of Artificial Intelligence