
Download the external resources, best practice and framework for AI
Internal auditors coordinate with AI and data science teams to assess data sources, algorithms, and governance. They enforce data privacy, risk controls, and ethical compliance in AI deployments.
Audit AI algorithms by reviewing documentation, development stages, data sources, preprocessing, and bias assessment, then validate fairness, performance metrics, and ethical compliance through thorough testing and monitoring.
Internal auditors assess organizations without ai by starting with the IT function, reviewing the IT inventory, identifying ai-enabled tools, and interviewing stakeholders to understand usage and plans.
Audit data integrity, privacy, and confidentiality in artificial intelligence for valid, accurate information. Apply IEEE AI auditing framework for data hosting, third party risk management, and identity and access management.
Assess cyber security controls, encryption, antivirus, intrusion prevention, security logging, and penetration testing in AI environments to protect data privacy, confidentiality, and resilience for internal auditors.
Audit AI security by testing access controls, authentication and authorization, encryption, data masking, monitoring, and incident response to ensure compliant, secure, and resilient AI systems.
“Learn AI Auditing Skills. It will be most demanding and highly paid skill very soon!”
Welcome to the "Artificial Intelligence Auditing. AI Tools & Cybersecurity" training course! This comprehensive program is designed to equip internal auditors with the knowledge and skills needed to effectively audit AI systems within their organizations. As artificial intelligence continues to transform various industries, it is crucial for auditors to understand the complexities and risks associated with AI to ensure compliance, security, and optimal performance.
Course Outline:
1. Introduction to AI Auditing
2. AI History
3. AI Types
4. AI Risks
5. AI Internal Controls
6. Cybersecurity related AI control tests
7. AI Best Practices for its use
8. Audit Program for AI (downloadable)
Learning Objectives:
- Understand the IIA Guidance: Gain insights into the IIA’s guidelines and best practices for auditing AI systems.
- Comprehend AI Risks: Identify and assess the various risks associated with AI implementation, and develop strategies to mitigate them.
- Learn AI History and Types: Trace the development of AI and distinguish between different types of AI to better understand their applications and implications.
- Apply AI Best Practices: Implement best practices to ensure AI systems are transparent, accountable, and secure.
- Develop Audit Programs: Create comprehensive audit programs that address the unique challenges of auditing AI technologies.
Course Delivery:
The "Artificial Intelligence Auditing Framework" course is delivered through a series of engaging and informative training videos, supplemented with real-world examples, case studies, and interactive exercises. Participants will have access to downloadable resources and templates to aid in their learning journey.
Certification:
Upon successful completion of the course, participants will receive a certificate of completion that can use used as CPE Certificate.