Auditing Artificial Intelligence

Course Objectives:

1. Understand the fundamentals of AI, including most commonly used artificial intelligence (AI) model types, tools and applications.
2. Identify risks associated with building AI systems responsibly, including safety, data integrity, privacy, security, and the ‘black box’ nature of AI algorithms.
3. Define internal audit's role in the organization's AI strategy.
4. Consider regulatory compliance and standards associated with the use of AI.
5. Utilize a framework based on IIA and industry best-practices for auditing AI models. 
6. Identify controls to mitigate AI risks, including Generative AI (Gen AI).

Course Topics:

1. Introduction to AI:
   • AI Overview - Understanding the fundamentals of AI and its evolution.
   • Establish a solid foundation in AI technology, including:
     • Machine learning models.
     • AI and Gen AI models.
     • Data sources.
     • Types of AI being used and explored in organizations.
2. Risk Management in AI:
   • Risk Identification and Management - Identifying and managing AI model risks and model use risks, such as safety, integrity, privacy, security.
   • Understanding the unique risks posed by the ‘black box’ nature of AI systems.
3. Internal Audit's Role in AI Strategy:
   • AI Strategic Management - Exploring how organizations plan and execute AI strategies, and oversight required.
   • Governance in AI - Understanding structures and processes for AI governance.
   • Role of internal audit - Discussing the role of internal audit in AI governance and the Three Lines Model, while leveraging internal controls in managing AI risks.
   • Integrating AI risk assessment with existing annual/quarterly risk assessments.
4. Regulatory Compliance and Standards:
   • Overview of AI-related regulatory landscape - Exploring AI related global regulations and industry frameworks.
   • Understanding organization’s policies, processes, and structures for complying with existing and upcoming regulations.
   • International standards for AI auditing.
5. AI Auditing Framework:
   • Overview of the AI Auditing Framework - Understanding the framework and associated domains and risk categories.
   • Applying the AI Auditing Framework through real-world scenarios.
     • Identify potential AI-related risks, assess their significance, and develop audit plans that address these risks effectively.
6. Controls for Mitigating AI Risks:
   • Exploring controls to manage AI model and model usage risks, such as bias, safety, data, privacy, and security.
   • Understanding controls for managing unique risks from the Gen AI models.

Who Should Attend:

This course is ideal for internal auditors, compliance professionals, risk managers, and anyone involved in auditing or governing AI initiatives within an organization.