Get in Touch

Course Outline

Overview of Artificial Intelligence and Machine Learning Concepts

  • Definitions and scope of artificial intelligence (AI)
  • The role of machine learning as a core component of AI systems
  • Classifications of AI technologies: narrow, general, generative, supervised, and unsupervised approaches

Operational Application of AI Throughout the Agency

  • Current deployment of AI and machine learning across business functions
  • Applications in process automation, decision support systems, public-facing services, and data analytics
  • Case studies within human resources, financial management, operational efficiency, and regulatory compliance for government entities

Key Governance Challenges

  • Alignment with established data protection principles
  • Ensuring lawfulness, fairness, and transparency in automated processing
  • Addressing requirements for accuracy, data minimization, and retention limits

Foundations of Information and Data Management

  • Records management practices specific to AI systems
  • The critical role of metadata standards and audit trails in maintaining accountability
  • Ensuring the quality and integrity of data used for model training

Strategies for Addressing Information Governance Issues

  • Developing governance controls for AI and machine learning workflows
  • Implementing human oversight mechanisms and explainability standards
  • Establishing cross-functional teams to manage governance responsibilities

Execution of Data Protection Impact Assessments for AI/ML

  • Regulatory mandates and objectives of Data Protection Impact Assessments (DPIAs)
  • Methodology for evaluating proposed AI/ML deployments
  • Documentation standards for risk analysis, mitigation strategies, and decision justifications

Governance Frameworks and Risk Management Approaches

  • Survey of recognized AI governance frameworks
  • Comparison of guidelines from ISO, NIST, the Information Commissioner’s Office (ICO), and OECD
  • Maintenance of risk registers and associated policy documentation for government operations

Cultural Integration and Alignment with Broader Frameworks

  • Fostering an organizational culture centered on responsible AI utilization
  • Aligning AI governance with cybersecurity, ethical guidelines, and environmental, social, and governance (ESG) objectives
  • Commitment to continuous monitoring and process improvement

Conclusion and Recommended Actions

Requirements

  • Comprehensive knowledge of institutional information governance frameworks
  • Proficiency in applicable data protection and privacy statutes
  • Basic familiarity with artificial intelligence or machine learning principles is advantageous

Intended Audience

  • Information governance practitioners
  • Data protection officers and compliance officials
  • Leaders in digital transformation or IT governance for government entities
 7 Hours

Number of participants


Price per participant

Upcoming Courses

Related Categories