⚠️ NYC LL144: Active Enforcement EU AI Act: Fairness Mandatory for High-Risk AI Test Your AI for Bias →
4) Bias, Fairness & Risk Testing 📚 DPT Playbook (Data Provenance Tracking) 11 Compliance Checks
⚖️

Automated Bias Testing

NYC LL144 80% rule testing, demographic parity analysis, and EU AI Act fairness assessment

11
Compliance Checks
DPT
Professional Playbook
80%
NYC LL144 Rule
4-6
Weeks to Complete

Why Bias Testing is Critical

Algorithmic discrimination is the #1 enforcement priority for regulators globally

The Bias Problem

📊 Industry Data:

  • $10M+ penalties for NYC LL144 violations (active enforcement)
  • €35M or 7% revenue for EU AI Act fairness violations
  • 78% of AI systems show some form of bias (MIT Study)
  • Class action lawsuits averaging $50M+ settlements

🚨 Real-World Examples:

  • Hiring AI: Amazon scrapped ML recruiting tool showing gender bias
  • Credit Decisions: Apple Card faced investigation for gender discrimination
  • Healthcare AI: Algorithms showed racial bias in treatment recommendations
  • Criminal Justice: COMPAS algorithm challenged for racial bias

⚖️ Regulatory Requirements:

  • NYC LL144: Mandatory annual bias audit (80% rule)
  • EU AI Act Article 10: Training data quality & bias assessment
  • EU AI Act Annex VII: Fairness metrics required for high-risk AI
  • ISO 42001 Section 6.2.4: Fairness assessment & mitigation

Business Impact of AI Bias

💰 Financial Risks:

  • $10M fines per NYC LL144 violation
  • €35M penalties for EU AI Act fairness violations
  • $50M+ settlements for discrimination class actions
  • Lost revenue from deployment delays

⚠️ Legal & Reputation Risks:

  • Discrimination lawsuits from affected individuals
  • Class action exposure for systemic bias
  • Brand damage from public bias revelations
  • Customer trust erosion affecting sales

🎯 Operational Risks:

  • Can't deploy AI in NYC without bias audit
  • EU market blocked without fairness assessment
  • Competitive disadvantage from compliance delays
  • Ongoing monitoring costs for bias drift

What You Get with Automated Bias Testing

Comprehensive fairness assessment using proven DPT Playbook methodology

🎯

NYC LL144 Compliance

  • ✓ 80% rule calculation (selection rate ratio)
  • ✓ Impact ratio analysis by protected class
  • ✓ Statistical significance testing
  • ✓ Annual audit certification
  • ✓ Candidate notice generation
  • ✓ Public results publication
⚖️

EU AI Act Fairness

  • ✓ Training data bias assessment
  • ✓ Demographic parity analysis
  • ✓ Equalized odds testing
  • ✓ Bias mitigation recommendations
  • ✓ Fairness metrics tracking
  • ✓ Technical documentation (Annex IV)
📊

Audit-Ready Reports

  • ✓ NYC LL144 Bias Audit Summary
  • ✓ EU AI Act Fairness Assessment
  • ✓ ISO 42001 Compliance Report
  • ✓ Statistical Analysis Details
  • ✓ Mitigation Action Plan
  • ✓ Executive Dashboard

Deliverables Timeline

Week 1: Data collection, protected class definition, statistical design
Week 2: Testing execution, 80% rule calculation, fairness metrics
Week 3: Report generation, mitigation planning, regulatory submission prep
Annual: NYC LL144 requires annual bias audits (we handle ongoing)

Why TrustRail is Different

DPT Playbook methodology vs generic fairness tools

Capability Generic Fairness Tools TrustRail (DPT Playbook)
NYC LL144 Testing Generic fairness metrics
Not specific to NYC LL144 requirements
NYC LL144 20-871 exact compliance
80% rule, impact ratios, notice requirements
Data Collection Upload your dataset
No guidance on what data needed
DPT Playbook guided assessment
Professional methodology shows exact data requirements
Protected Classes You define categories
Risk of non-compliant definitions
NYC LL144 + EU AI Act definitions
Legally compliant categorizations
Statistical Methods Black box algorithms
Can't explain to regulators
Transparent statistical tests
Chi-square, Fisher's exact, documented
Bias Mitigation "Bias detected" alerts
No actionable remediation plan
Structured mitigation playbook
DPT Playbook: Professional remediation strategies
Regulatory Reports Export metrics to CSV
You format for compliance
NYC LL144 + EU AI Act ready
Accepted by regulators from day 1
Training Data Analysis Model outputs only
Misses data source bias
Full data provenance tracking
Source bias, collection bias, labeling bias
Expert Support Online documentation
DIY statistical analysis
Professional services available
We conduct your first bias audit
Time to Compliance 3-6 months (DIY)
Figure out requirements yourself
4-6 weeks (guided)
DPT Playbook accelerates completion
📚

DPT Playbook Methodology

Data Provenance Tracking (DPT) Playbook provides comprehensive coverage from data collection through bias mitigation.

  • ✓ NYC LL144 exact compliance mapped
  • ✓ EU AI Act fairness requirements
  • ✓ Statistical rigor documented
🎯

Regulatory-First Approach

Built for NYC LL144 and EU AI Act compliance, not generic "fairness." Every metric maps to specific legal requirement.

  • ✓ 80% rule exactly as written
  • ✓ Protected class definitions from law
  • ✓ Reports accepted by regulators

Jump Start Available

Professional services team conducts your first bias audit with you. Transfer knowledge to your team.

  • ✓ 4-6 weeks vs 3-6 months DIY
  • ✓ Annual audits handled
  • ✓ Training included

How Bias Testing Works

DPT Playbook guides you through comprehensive bias testing and fairness assessment

Assessment Process

Our proprietary DPT Playbook guides you through comprehensive bias testing and fairness assessment:

Scope Definition & Planning

Define AI system scope, NYC LL144 applicability, and testing approach aligned with regulatory requirements

Data Collection & Preparation

Gather test data, identify protected attributes, and establish demographic baselines for statistical testing

Statistical Bias Testing

Execute NYC LL144 80% rule calculations, demographic parity analysis, and statistical significance testing

Mitigation Planning

Identify root causes and develop structured remediation strategies for any bias detected

Regulatory Reporting

Generate NYC LL144 compliant bias audit reports and EU AI Act fairness documentation

Professional Assessment Experience

Our DPT Playbook provides comprehensive guidance for NYC LL144 and EU AI Act compliant bias testing:

✓ NYC LL144 Compliance

Professional methodology ensures exact compliance with 20-871 bias audit requirements including 80% rule calculation and protected class definitions

✓ Statistical Rigor

Documented statistical testing approach with significance calculations and confidence intervals

✓ Mitigation Guidance

Structured approach to identifying bias root causes and developing actionable remediation strategies

💡 Every step mapped to NYC LL144 and EU AI Act specific requirements for regulatory acceptance

Typical Implementation Timeline

1

Week 1: Setup

  • • Scope definition
  • • Data collection
  • • Protected class definition
  • • Test design
2

Week 2: Testing

  • • 80% rule calculation
  • • Statistical tests
  • • Fairness metrics
  • • Mitigation planning
3

Week 3: Reporting

  • • Audit report generation
  • • Regulatory submission
  • • Public notice
  • • Ongoing monitoring setup

11 Compliance Checks Addressed

Bias testing addresses the most critical fairness requirements

EU AI Act (4 checks)

EU-004: Data Governance & Management Requirements
Article 10 - Training data quality and provenance
EU-005: Bias & Fairness Risk Assessment
Article 10(2)(f) - Examine bias in training data
EU-006: Training & Validation Data Quality Assessment
Article 10(3) - Data quality criteria
EU-010: Accuracy & Performance Readiness
Article 15 - Accuracy, robustness across groups

NYC LL144 (3 checks)

NYC-001: Bias Audit Requirement
20-870 - Mandatory annual bias audit
NYC-002: Annual Bias Audit
20-871(a) - Independent auditor testing
NYC-005: Public Notice Requirements
20-871(b)(3) - Publish audit results

ISO 42001 & NIST (4 checks)

ISO-011: AI Data Management & Governance
Section 6.2.6 - Data quality and bias
ISO-012: Fairness Assessment
Section 6.2.4 - Fairness evaluation
NIST-005: Data Quality (MAP 3.1)
Training data suitability and quality
NIST-006: Bias Testing (MEASURE 2.2)
AI system tested for biases

DPT Playbook: What's Inside

Data Provenance Tracking Playbook - Comprehensive bias testing methodology

Playbook Structure

  • 📖
    Comprehensive Multi-Section Framework
    From scope definition through ongoing monitoring
  • 📋
    Extensively Documented Methodology
    NYC LL144 and EU AI Act compliance fully mapped
  • Professional Assessment Screens
    Guided data collection and testing workflow
  • 🎯
    11 Compliance Requirements Mapped
    Every test tied to specific regulation
  • 📊
    Professional Report Templates
    NYC LL144, EU AI Act, ISO 42001 ready

Why DPT Works

✓ NYC LL144 Exact Compliance

Built specifically for 20-871 bias audit requirements

✓ EU AI Act Aligned

Article 10 training data bias assessment covered

✓ Statistical Rigor

Chi-square, Fisher's exact, significance testing documented

✓ Continuously Updated

Incorporates latest regulatory guidance and case law

Sample Report Outputs

📊 NYC LL144 Bias Audit Summary

20-871 compliant report including:

  • • Selection rates by protected class
  • • Impact ratios (80% rule)
  • • Statistical significance
  • • Pass/fail determination
  • • Public notice text
  • • Auditor certification

⚖️ EU AI Act Fairness Assessment

Article 10 documentation showing:

  • • Training data bias analysis
  • • Protected attribute impacts
  • • Demographic parity metrics
  • • Mitigation measures taken
  • • Technical documentation (Annex IV)
  • • Ongoing monitoring plan

🎯 Mitigation Action Plan

Remediation strategy including:

  • • Root cause analysis
  • • Data rebalancing approach
  • • Algorithm modifications
  • • Testing results pre/post
  • • Implementation timeline
  • • Success metrics

Get Started with Bias Testing

NYC LL144 annual audit or one-time EU AI Act assessment

Platform Only

$2,500/mo

Self-service access to DPT Playbook

  • Full DPT Playbook access
  • Guided testing screens
  • Statistical calculators
  • Report generation
  • No expert support
Start Free Trial
RECOMMENDED

Platform + Services

$30,000+

Expert-led bias audit + platform access

  • Everything in Platform
  • We conduct your audit
  • Statistical analysis by experts
  • Regulatory submission support
  • 4-6 weeks to completion
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Annual Program

Custom

NYC LL144 annual audit program

  • Everything in Services
  • Annual audit conducted
  • Ongoing monitoring
  • Regulatory updates
  • Multi-year contracts
Contact Sales

Ready to Test for Bias?

NYC LL144 compliant bias audit in 4-6 weeks with expert guidance

Free consultation • NYC LL144 & EU AI Act compliant • 2-3 week typical timeline