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Course Outline

Demystifying AI and Machine Learning

  • Defining AI and understanding its scope.
  • Viewing Machine Learning as a specialized branch of AI.
  • Categorizing AI: weak, strong, generative, supervised, and unsupervised types.

Practical AI Applications in Business

  • Locating current AI/ML integration points within business functions.
  • Exploring automation, decision support, customer service, and analytics.
  • Reviewing use cases in HR, finance, operations, and compliance.

Navigating Governance Obstacles

  • Addressing potential conflicts with Data Protection Principles.
  • Ensuring lawfulness, fairness, and transparency in automated decisions.
  • Managing accuracy, data minimization, and storage limitations.

Core Principles of Information and Data Management

  • Handling information and records management specifically for AI contexts.
  • Recognizing the value of metadata and audit trails.
  • Ensuring data quality and integrity for training datasets.

Addressing Information Governance Hurdles

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

Performing DPIAs for AI/ML

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

Frameworks for Governance and Risk Management

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

Fostering Culture, Integration, and Alignment

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

Recap and Forward-Looking Actions

Requirements

  • Knowledge of organizational information governance policies.
  • Awareness of data protection or privacy regulatory requirements.
  • Basic familiarity with AI or machine learning concepts is advantageous.

Intended Audience

  • Specialists in information governance.
  • Data protection officers and compliance managers.
  • Leaders in digital transformation and IT governance.
 7 Hours

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