AI Ethics, Risk Analysis, and Governance Training Course
Formats⟩Live Virtual: 4 hrs./1 Day |In-Person: 6 hrs./1 Day
AI Ethics, Risk Analysis, and Governance Analysis equips participants with the knowledge to identify, assess, and manage the ethical and operational risks associated with AI systems. The course covers foundational AI concepts, regulatory considerations, and how AI is used to support or automate decisions within organizations. Participants will explore core ethical principles, analyze real-world cases, and apply structured approaches to evaluating risk across areas such as compliance, security, and reliability. The course also introduces governance practices, controls, and action planning to support responsible AI implementation. Participants will be able to assess AI risks and apply practical strategies to ensure ethical and compliant use.
Learning Objectives »
Understand key AI concepts, lifecycle stages, and regulation.
Apply ethical principles to evaluate AI use cases and decisions.
Categorize AI risk across legal, operational, and reputational areas.
Use structured approaches to analyze and manage AI risk.
Apply governance practices and controls for responsible AI.
Course Agenda
AI Basics, Org Context, and Regulation
AI Vocabulary
Typical Lifecycle
Monitoring
Common Mental Models
Clarity on Right Decisions
Automated Human Decisions
Key Laws, Regulations, and Standards
High-Risk vs. Low-Risk Systems
Principles, Dilemmas, Case Work
Core Principles
Real Case Examples
Ethical Dilemma Discussions
Risk Categories and Analysis Models
Risk Categories
Repeatable Risk Analysis Method
Governance, Control, & Action Planning
AI Inventory, Intake Forms, Approval
Roles and Responsibilities
Key Controls
Data Impact
Model Documentation
Transparency Artifacts
Human-in-the-Loop Review
Escalation Paths, Monitoring
AI Ethics, Risk Analysis, and Governance Training Course
Formats⟩Live Virtual: 4 hrs./1 Day |In-Person: 6 hrs./1 Day
AI Ethics, Risk Analysis, and Governance Analysis equips participants with the knowledge to identify, assess, and manage the ethical and operational risks associated with AI systems. The course covers foundational AI concepts, regulatory considerations, and how AI is used to support or automate decisions within organizations. Participants will explore core ethical principles, analyze real-world cases, and apply structured approaches to evaluating risk across areas such as compliance, security, and reliability. The course also introduces governance practices, controls, and action planning to support responsible AI implementation. Participants will be able to assess AI risks and apply practical strategies to ensure ethical and compliant use.
Learning Objectives »
Understand key AI concepts, lifecycle stages, and regulation.
Apply ethical principles to evaluate AI use cases and decisions.
Categorize AI risk across legal, operational, and reputational areas.
Use structured approaches to analyze and manage AI risk.
Apply governance practices and controls for responsible AI.
Course Agenda
AI Basics, Org Context, and Regulation
AI Vocabulary
Typical Lifecycle
Monitoring
Common Mental Models
Clarity on Right Decisions
Automated Human Decisions
Key Laws, Regulations, and Standards
High-Risk vs. Low-Risk Systems
Principles, Dilemmas, Case Work
Core Principles
Real Case Examples
Ethical Dilemma Discussions
Risk Categories and Analysis Models
Risk Categories
Repeatable Risk Analysis Method
Governance, Control, & Action Planning
AI Inventory, Intake Forms, Approval
Roles and Responsibilities
Key Controls
Data Impact
Model Documentation
Transparency Artifacts
Human-in-the-Loop Review
Escalation Paths, Monitoring
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