Executive Briefing Course
Ethics, Governance, and Compliance in AI
Develop an AI governance review that connects accountability, data practices, impact assessment and evidence of system limitations across the lifecycle.
Course Overview
Examines ethical, governance and compliance questions across the AI lifecycle. Participants review accountability, data practices and the evidence needed to assess system impacts and limitations.
Who This Course Is For
- AI governance and compliance professionals
- Data teams reviewing responsible practices
- Technical managers overseeing AI systems
- Risk specialists assessing organisational impacts
What Participants Will Learn
Map accountability across the AI lifecycle
Review data practices and evidence requirements
Identify ethical questions in system impacts
Assess governance records against stated requirements
Present review questions and evidence gaps
Key topics
- Accountability
- Data practices
- Impact assessment
- Governance evidence
Course Modules
Back to Course OverviewAI Governance and Ethics Context
AI Governance and Ethics Context
Module overview
Review accountability, data practices, impact assessment and evidence as connected elements of AI governance.
Key topics
Accountability · Data practices · Impact assessment · Governance evidence
Learning outcome
Identify governance questions and responsibilities across an AI system lifecycle.
Learning format
Guided discussion · governance case review
Accountability and Lifecycle Responsibilities
Accountability and Lifecycle Responsibilities
Module overview
Map who makes, reviews and records decisions during AI development, deployment and operation.
Key topics
Accountable roles · Lifecycle decisions · Review responsibilities · Decision records
Learning outcome
Assign review responsibilities and identify unresolved accountability questions.
Learning format
Guided discussion · responsibility mapping
Data Practices and Review Evidence
Data Practices and Review Evidence
Module overview
Review how data is handled and identify evidence needed to assess practices against organisational requirements.
Key topics
Data practices · Handling responsibilities · Evidence requirements · Review gaps
Learning outcome
Identify data practice questions and evidence needed for governance review.
Learning format
Evidence review · governance discussion
Impacts Ethics and Limitations
Impacts Ethics and Limitations
Module overview
Assess potential system impacts and examine how limitations and stakeholder concerns inform review decisions.
Key topics
Impact assessment · Ethical questions · Stakeholder concerns · System limitations
Learning outcome
Frame an impact question and explain the evidence needed to assess it.
Learning format
Case discussion · impact review
AI Governance Case Review
AI Governance Case Review
Module overview
Review a proposed AI system and present accountability, data and impact questions with evidence requirements.
Key topics
Governance case study · Accountability review · Impact questions · Evidence gaps
Learning outcome
Participants can identify governance questions and evidence requirements for an AI system.
Learning format
Lectures, governance case studies and group review
Programme Information
Course duration, location, practical components, training-centre information and applicable certification arrangements depend on the selected programme.
Learning format: Lectures, governance case studies and group review
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