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Course Outline

Foundations of AI and Machine Learning

  • Defining Artificial Intelligence and its scope.
  • Machine Learning as a component of the broader AI landscape.
  • Categories of AI: weak, strong, generative, supervised, and unsupervised.

Practical Application of AI Across the Enterprise

  • Current presence of AI/ML within various business functions.
  • Roles in automation, decision support, customer engagement, and analytics.
  • Applications in HR, finance, operations, and compliance domains.

Key Governance Challenges

  • Potential conflicts with established Data Protection Principles.
  • Ensuring lawfulness, fairness, and transparency in automated decisions.
  • Managing accuracy, data minimization, and retention limits.

Core Principles of Information and Data Management

  • Information and records management specific to AI contexts.
  • The critical role of metadata and audit trails.
  • Ensuring the quality and integrity of training datasets.

Strategies for Addressing Governance Issues

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

Performing DPIAs for AI/ML Initiatives

  • Understanding the legal basis and objective of DPIAs.
  • Methodologies for assessing proposed AI/ML implementations.
  • Documenting risk evaluations, mitigation measures, and justifications.

Governance Frameworks and Risk Oversight

  • Survey of AI-specific governance models.
  • Perspectives from ISO, NIST, ICO, and OECD standards.
  • Maintaining risk registers and policy documentation.

Organizational Culture, Integration, and Broader Frameworks

  • Cultivating an environment of responsible AI usage.
  • Aligning AI governance with cybersecurity, ethics, and ESG policies.
  • Fostering continuous improvement and monitoring capabilities.

Recap and Future Directions

Requirements

  • Familiarity with organizational information governance policies.
  • Knowledge of data protection or privacy regulations.
  • Basic exposure to AI or machine learning concepts is beneficial.

Target Audience

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

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