AI Auditor's Handbook
R$196.00
R$98.00
“AI Auditor’s Manual”, written by Paulo S.O. Carvalho, is an essential work for all those who work in digital transformation with responsibility and strategic vision. This unprecedented manual proposes a practical and normative approach for the implementation of governance systems in artificial intelligence, based on international standards such as ISO/IEC 42001, the European AI Act (EU Regulation 2024/1689) and current discussions on the Brazilian legal framework for AI (PL 2338/2023).
Aimed at auditors, innovation leaders, public and private managers, IT and compliance professionals, the book offers detailed guidelines for structuring an AI Management System (AIMS). It covers topics such as:
Organizational context and scope of AI
Risk assessment and algorithmic impact
Technical, ethical and organizational controls
Meaningful human oversight
Guidelines for non-compliance and continuous improvement
Alignment with democratic values and fundamental rights
The great difference of the work is its practical and applicable nature, using examples, checklists, templates and operational flows. With accessible language and robust foundations, the author transforms a complex topic into an indispensable governance tool for organizations seeking to lead with safety and ethics in the use of AI.
Quantity
Topics Covered
Foreword
Prologue
Methodology
1 - AI Context
Understanding the context in practice
Understanding the Expectations of Impacted People AI Scope
2 Leadership
The role of leadership in AI management
Creating an AI Policy in Practice
Artificial Intelligence Governance Policy
3 - Planning
Actions to address risks and opportunities
How I assess AI risks in practice
Risk and Opportunity Assessment in AI
Risk and Opportunity Planning in AI
Transforming risks into actions
Algorithmic Impact Assessment
AI Objectives and Planning to Achieve Them
Example OKRs for AI Planning
4 - Support
Resources, Competence and Awareness
5 - Operations
Operational Control Planning
AI Risk Treatment
6 - Performance Evaluation
Monitoring, Measurement, Analysis and Assessment
Critical analysis by management
7 - Improvement
Non-conformity and corrective action
8 - Controls A.2
Policy
Organization
Resources for AI systems
Assessment of the impacts of AI systems
AI system life cycle
Data for AI systems
Information for stakeholders
Use of AI systems
Relationship with customers and third parties
9 - Information
Organizational objectives
10 - EU ACT Regulation
EU ACT x ISO 42.001
11 - AI in Brazil
Understanding PL 2338/2023 in Practice
Final Conclusion