Data & Governance
Collect vocational data securely and consider techniques such as anonymization. Track data versions and maintain clear consent records.
Establish clear data-retention schedules and encryption protocols so that client information remains secure throughout the AI lifecycle.
Model Design & Fairness
Use fairness metrics to monitor performance across disability groups. Libraries like Fairlearn can help identify disparities.
Deployment & Monitoring
Secure containers, accessible front ends, and regular audits are important for reliable systems. Monitor changes in model behavior over time.
Document each model release with a versioned changelog and capture feature-importance reports so counselors can track how decision factors evolve.
Integrating accessibility testing into CI pipelines ensures that user interfaces remain navigable as new functionality is added.