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Course Outline

Comprehending AI and Machine Learning

  • Defining AI: What it is and its core characteristics.
  • Viewing Machine Learning as a specialized subset of AI.
  • Categorizing AI: weak, strong, generative, supervised, and unsupervised.

AI Applications Across the Enterprise

  • Mapping the current presence of AI/ML in various business functions.
  • Examining roles in automation, decision support, customer service, and analytics.
  • Reviewing specific use cases within HR, finance, operations, and compliance.

Prevailing Governance Obstacles

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

Principles of Information and Data Management

  • Managing information and records specifically within AI contexts.
  • Understanding the critical role of metadata and audit trails.
  • Preserving data quality and integrity for training datasets.

Navigating Information Governance Complexities

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

Executing DPIAs for AI/ML

  • Understanding the legal mandates and objectives of DPIAs.
  • Following steps to evaluate proposed AI/ML implementations.
  • Documenting risk assessments, mitigation measures, and justifications.

Governance Frameworks and Risk Strategy

  • Surveying AI-specific governance frameworks.
  • Exploring approaches from ISO, NIST, ICO, and the OECD.
  • Maintaining risk registers and policy documentation.

Cultural Integration and Broader Frameworks

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

Recap and Forward Planning

Requirements

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

Target Audience

  • Information governance professionals
  • Data protection officers and compliance managers
  • Digital transformation or IT governance leaders
 7 Hours

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