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 Duration 7 hours

Course Outline

Grasping AI-Specific Risks in Government Environments

  • Distinguishing AI risks from conventional IT and data risks
  • Classifying AI risks: technical, operational, reputational, and ethical
  • Navigating public accountability and risk perception in the government sector

AI Risk Management Frameworks

  • The NIST AI Risk Management Framework (AI RMF)
  • ISO/IEC 42001:2023 — The Standard for AI Management Systems
  • Additional sector-specific and international guidelines (e.g., OECD, UNESCO)

Security Threats Facing AI Systems

  • Adversarial inputs, data poisoning, and model inversion attacks
  • Leaks of sensitive training data
  • Risks associated with supply chains and third-party models

Governance, Auditing, and Control Mechanisms

  • Human-in-the-loop processes and accountability structures
  • Ensuring auditable AI through documentation, version control, and interpretability
  • Internal controls, oversight roles, and compliance milestones

Risk Assessment and Mitigation Strategies

  • Creating risk registers for various AI use cases
  • Coordinating with procurement, legal, and service design teams
  • Performing pre-deployment and post-deployment assessments

Incident Response and Public-Sector Resilience

  • Managing AI-related incidents and security breaches
  • Effective communication with stakeholders and the general public
  • Integrating AI risk practices into cybersecurity playbooks

Recap and Recommended Next Steps

Requirements

  • Background in IT operations, risk management, cybersecurity, or compliance within government settings
  • Knowledge of organizational security protocols and digital service delivery
  • No prior technical experience with AI systems is necessary

Target Audience

  • Government IT units handling digital services and system integration
  • Cybersecurity and risk experts within public institutions
  • Public sector staff involved in audit, compliance, and governance

Testimonials (1)

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