Troubleshooting: Control 2.11 - Bias Testing and Fairness Assessment
Last Updated: January 2026
Common Issues
| Issue | Cause | Resolution |
|---|---|---|
| Insufficient test data | Small sample sizes | Expand test dataset |
| Cannot classify outcomes | Subjective responses | Define clear criteria |
| Persistent bias | Model/prompt issues | Adjust prompts or topics |
| Metrics not meaningful | Wrong metrics for use case | Select appropriate metrics |
Detailed Troubleshooting
Issue: Test Dataset Too Small
Symptoms: Metrics not statistically significant
Resolution:
- Generate more synthetic test cases
- Ensure minimum 500-1000 per group
- Balance across all protected classes
- Document methodology
Issue: Bias Detected in Results
Symptoms: Significant disparity between groups
Resolution:
- Analyze response patterns for bias source
- Review knowledge sources for biased content
- Adjust system prompts for fairness
- Add explicit fairness instructions
- Re-test after changes
Escalation Path
- AI Governance Lead - Testing methodology
- Data Science Team - Statistical analysis
- Compliance Officer - Regulatory alignment
- Legal - Fair lending requirements
Known Limitations
| Limitation | Impact | Workaround |
|---|---|---|
| LLM responses variable | Same input may give different output | Run multiple iterations |
| Synthetic data limitations | May not reflect real patterns | Supplement with production sampling |
| Outcome classification subjective | Inconsistent results | Use multiple reviewers |
| No standard FSI fairness tools | Must build custom | Document methodology |
Back to Control 2.11 | Portal Walkthrough | PowerShell Setup | Verification Testing