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Professionals reviewing an AI governance framework, risk assessment and human-oversight process
Artificial Intelligence · Course #012

Responsible AI and AI Governance

Responsible AI and AI Governance is a practical course for organisations seeking to develop, procure and use Artificial Intelligence responsibly. Participants learn to establish governance roles, create policies, maintain an AI-use inventory, classify risks and conduct impact assessments. The course addresses fairness, transparency, privacy, security, human oversight, vendor management, documentation, incident response and ongoing monitoring. It also introduces major international AI governance frameworks and emerging regulatory expectations.

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Overview

Responsible AI and AI Governance is a practical course for organisations seeking to develop, procure and use Artificial Intelligence responsibly. Participants learn to establish governance roles, create policies, maintain an AI-use inventory, classify risks and conduct impact assessments. The course addresses fairness, transparency, privacy, security, human oversight, vendor management, documentation, incident response and ongoing monitoring. It also introduces major international AI governance frameworks and emerging regulatory expectations.

Course Highlights

Responsible AI principles

AI governance roles and policies

AI inventory and risk classification

Impact assessment and documentation

Human oversight and vendor management

Monitoring and incident response

Modules & Curriculum

Responsible AI Principles and Emerging Risks

AI Governance Structures, Roles and Accountability

AI Policies, Use-Case Inventories and Risk Classification

Fairness, Transparency and Explainability

Privacy, Security and Human Oversight

AI Impact Assessment and Third-Party Governance

Documentation, Monitoring and Incident Management

Organisational AI Governance Implementation Roadmap

Learning Outcomes

  • Explain the principles and organisational importance of responsible AI.
  • Define governance roles, responsibilities and accountability structures.
  • Create an inventory of organisational AI systems and use cases.
  • Classify AI applications according to impact, risk and oversight requirements.
  • Conduct an initial AI impact and risk assessment.
  • Develop practical AI policies, standards and approval processes.
  • Address fairness, transparency, privacy, security and human oversight.
  • Evaluate third-party AI providers and associated data or technology risks.
  • Plan documentation, monitoring, incident response and periodic review.

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Build a practical governance framework for responsible, secure and accountable AI use.

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