Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
Understanding AI and Machine Learning
- Defining AI and understanding its core scope.
- Viewing Machine Learning as a key subset of AI.
- Exploring different types of AI: weak, strong, generative, supervised, and unsupervised.
AI in Practice Across the Organization
- Where AI/ML is currently utilized in various business functions.
- Applications in automation, decision support, customer service, and analytics.
- Practical use cases within HR, finance, operations, and compliance departments.
Common Governance Challenges
- Potential conflicts with Data Protection Principles.
- Ensuring lawfulness, fairness, and transparency in automated decision-making.
- Addressing accuracy, data minimization, and storage limitation requirements.
Foundations in Information and Data Management
- Information and records management within AI contexts.
- The critical importance of metadata and audit trails.
- Maintaining data quality and integrity for training datasets.
Approaching Information Governance Challenges
- Designing effective governance controls for AI/ML pipelines.
- Implementing human oversight and ensuring explainability.
- Building effective cross-functional governance teams.
Conducting DPIAs for AI/ML
- Understanding the legal requirements and purpose of DPIAs.
- Steps to assess proposed AI/ML implementations.
- Documenting risk assessments, mitigation strategies, and justifications.
Governance Frameworks and Risk Management
- An overview of AI-specific governance frameworks.
- Approaches from ISO, NIST, ICO, and OECD.
- Utilizing risk registers and policy documentation.
Culture, Integration, and Related Frameworks
- Fostering a culture of responsible AI use within the organization.
- Linking AI governance with cybersecurity, ethics, and ESG (Environmental, Social, and Governance) policies.
- Strategies for continuous improvement and ongoing monitoring.
Summary and Next Steps
Requirements
- A working understanding of your organization's information governance policies.
- Familiarity with data protection or privacy regulations.
- It is helpful, though not mandatory, to have some prior exposure to AI or machine learning concepts.
Audience
- Information governance professionals.
- Data protection officers and compliance managers.
- Leads responsible for digital transformation or IT governance.
7 Hours
