Scenario: A rideshare company launches a driver-rating prediction tool.

Problem: The tool assigns lower scores in certain neighbourhoods due to skewed training data.

Fixes:

  • Introduced bias detection thresholds

  • Required human review for outlier ratings

  • Built dashboards for explainability

Result: Improved fairness, restored driver trust, and reduced support escalations.