Get in Touch
 Duration 7 hours

Course Outline

Navigating AI-Specific Risks in Government Environments

  • Distinguishing AI risks from traditional IT and data risks
  • Classifying AI risks: technical, operational, reputational, and ethical
  • Managing 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 AI Management System Standard
  • Additional sector-specific and international guidance (e.g., OECD, UNESCO)

Security Threats Facing AI Systems

  • Adversarial inputs, data poisoning, and model inversion attacks
  • Risks associated with the exposure of sensitive training data
  • Supply chain and third-party model vulnerabilities

Governance, Auditing, and Control Mechanisms

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

Risk Assessment and Mitigation Strategies

  • Developing risk registers for specific AI use cases
  • Collaborating with procurement, legal, and service design teams
  • Performing pre- and post-deployment evaluations

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

Summary and Future Steps

Requirements

  • Background in IT operations, risk management, cybersecurity, or compliance within government settings
  • Understanding of organizational security measures and digital service provision
  • No prior technical expertise in AI systems is necessary

Target Audience

  • Government IT teams managing digital services and system integration
  • Cybersecurity and risk specialists in public institutions
  • Public sector staff responsible for audit, compliance, and governance

Testimonials (1)

Related Categories