EU AI Act Compliance Report

Generated on: 2025-03-26 14:51:31

• Intended Purpose: AI-powered candidate evaluation system for recruitment
• Architecture: Two-model cascade system
  • Extraction Model (GPT-4o-mini): Parses CVs and positions into structured data
  • Comparison Model (GPT-4o): Evaluates candidate suitability
• Risk Classification: High-risk AI system (Article 6(2) and Annex III(4)(a))

• Dataset Size: 20 candidate profiles
• Data Quality Score (R-Score): 0.00
• Data Distribution:
  • Gender: {'Female': 13, 'Male': 7}
  • Nationality: {'Nigeria': 5, 'India': 4, 'UK': 3, 'Germany': 3, 'Brazil': 3, 'US': 2}
  • Age: Mean=42.5, Std=12.3
• Data Lineage: Tracked through W&B Artifacts
• Version Control: Managed via W&B Registry

• Training Pipeline:
  • Data Preprocessing: Automated extraction and structuring
  • Model Fine-tuning: GPT-4o with custom training data
  • Hyperparameter Optimization: Automated via W&B Sweeps
• Performance Metrics:
  • Decision Accuracy: 0.00%
  • Reasoning Quality: 0.00%
  • Hallucination Rate: 0.00%
• Guardrails:
  • Hallucination Detection
  • PII Masking
  • Decision-Reasoning Alignment

• Automated Testing:
  • Decision Match Evaluation
  • Reasoning Quality Assessment
  • Hallucination Detection
• Human Oversight:
  • Manual Review Interface
  • Appeal Process
  • Feedback Collection
• Continuous Monitoring:
  • Performance Metrics
  • Bias Detection
  • Data Drift Analysis

• Model Architecture Documentation
• Training Process Details
• Evaluation Methodology
• Risk Assessment
• Mitigation Strategies
• Compliance Evidence

1. Regular bias audits and monitoring
2. Enhanced transparency documentation
3. Expanded dataset diversity
4. Improved human review process
5. Regular compliance updates
6. Automated compliance reporting