BiasClean v3.0 – Audit-First AI Fairness Engine
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BiasCleanv3.0

Audit-First AI Fairness Engine

Governance-aware bias detection and mitigation with pre-deployment safety audits, domain-specific weight frameworks, and optional SVM fairness enforcement.

Start Audit-First Analysis

What’s New in v3.0

BiasClean v3.0 introduces Audit-First Mode with traffic-light governance (๐ŸŸข Green / ๐ŸŸก Yellow / ๐Ÿ”ด Red) to assess dataset safety before mitigation. New features include:

  • Pre-Mitigation Audit: Traffic-light system (๐ŸŸข๐ŸŸก๐Ÿ”ด) evaluates deployment readiness
  • Three Operating Modes: Audit-First (recommended), Audit-Only, or Legacy
  • SVM Fairness Enforcement: Optional model-level fairness constraints
  • Enhanced Monitoring: Stage-wise tracking with confidence intervals
  • 7 Domain Frameworks: Justice, Healthcare, Finance, Hiring, Education, Business, Governance
  • Advanced Reporting: HTML reports, visualizations, and deployment decision support

Upload Your Dataset

Upload a CSV file to begin bias analysis with v3.0 audit-first pipeline

Domain determines feature weights and bias detection priorities
Leave blank for automatic detection. Specify the outcome/prediction column if known.

Traffic-Light Governance

๐ŸŸข Green (Safe) / ๐ŸŸก Yellow (Review) / ๐Ÿ”ด Red (Unsafe) – Clear deployment recommendations based on bias severity and vulnerable group count.

Domain-Specific Weights

7 regulatory frameworks (Justice, Healthcare, Finance, Hiring, Education, Business, Governance) with weights aligned to UK equality regulations and sector priorities.

SVM Fairness Enforcement

Optional model-level fairness constraints using Support Vector Machines. Provides fairness-aware predictions alongside BiasClean mitigated data.

Enhanced Monitoring

Stage-wise bias tracking, statistical confidence intervals, group rate monitoring, and sampling attribution for full transparency.

Comprehensive Reporting

HTML reports with visualizations, deployment decision support, feature interaction analysis, and v2.7 compatibility exports.

Integrity-Constrained

Maintains data integrity with minimal sampling (typically 101-103% retention). Weight-prioritized mitigation focuses on highest-impact features first.

Regulatory Compliance
BiasClean v3.0 aligns with UK Equality Act 2010, GDPR Article 22, and sector-specific guidelines (FCA, CQC, ICO). Audit-first mode supports evidence-based deployment decisions.
Technical Implementation
Protected attributes: Ethnicity, Gender, Age, DisabilityStatus, SocioeconomicStatus, Region, MigrationStatus. Analysis uses chi-square/Fisher exact tests (ฮฑ=0.05), weighted bias scoring, and optional SVM fairness constraints.
Data Privacy & Security
All processing occurs server-side with secure file handling. Original data is never stored permanently. Results are temporarily cached and automatically deleted after download.
Audit-First Mode
Safety audit runs before any mitigation, with a traffic-light (๐ŸŸข๐ŸŸก๐Ÿ”ด) deployment-readiness score regulators and ethics boards can read at a glance.
Domain-Specific Weight Frameworks
Feature weights and bias-detection priorities calibrated separately for Justice, Health, Finance, Education, Hiring, Business, and Governance datasets.
Optional SVM Enforcement
Support-vector-machine rebalancing preserves predictive accuracy while correcting disparities identified during the audit stage.

This tool provides fairness assessment and bias-mitigation for research and analytical purposes only and does not constitute legal or regulatory compliance advice. AI Fairness CIO · Charity Commission for England and Wales · Registered Charity No. 1218464.

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