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Course Outline

Comprehending AI and Machine Learning

  • Defining Artificial Intelligence and its scope.
  • Machine Learning as a specialized subset of AI.
  • Categorizing AI types: weak, strong, generative, supervised, and unsupervised.

Practical AI Applications Across the Enterprise

  • Identifying where AI/ML currently resides within various business functions.
  • Roles in automation, decision support, customer service, and analytics.
  • Specific use cases in HR, finance, operations, and compliance.

Addressing Common Governance Challenges

  • Navigating potential conflicts with Data Protection Principles.
  • Ensuring lawfulness, fairness, and transparency in automated decision-making.
  • Managing accuracy, data minimization, and storage constraints.

Foundations of Information and Data Management

  • Approaching information and records management within AI contexts.
  • The critical role of metadata and audit trails.
  • Ensuring data quality and integrity for training datasets.

Tackling Information Governance Issues

  • Designing effective governance controls for AI/ML pipelines.
  • Implementing human oversight and model explainability.
  • Forming cross-functional governance teams.

Performing DPIAs for AI/ML

  • Understanding the legal mandates and objectives of DPIAs.
  • Methodologies for assessing proposed AI/ML implementations.
  • Documenting risk assessments, mitigation measures, and justifications.

Governance Frameworks and Risk Management

  • An overview of AI-specific governance frameworks.
  • Perspectives from ISO, NIST, ICO, and OECD.
  • Maintaining risk registers and policy documentation.

Culture, Integration, and Broader Frameworks

  • Fostering a culture of responsible AI utilization.
  • Aligning AI governance with cybersecurity, ethics, and ESG policies.
  • Pursuing continuous improvement and monitoring.

Recap and Future Directions

Requirements

  • A solid grasp of organizational information governance policies.
  • Familiarity with relevant data protection or privacy regulations.
  • Prior exposure to AI or machine learning concepts is advantageous.

Target Audience

  • Information governance specialists.
  • Data protection officers and compliance managers.
  • Leaders in digital transformation or IT governance.
 7 Hours

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