NYC Local Law 144 Compliance Software
Automated bias auditing for employment decision tools
DecisionLedger AI provides the bias auditing infrastructure employers need to comply with NYC Local Law 144 — from disparate impact analysis and SHAP explainability to candidate notice tracking and immutable audit trails.
This page describes platform capabilities. It does not constitute compliance certification with NYC Local Law 144. Organizations must engage a qualified independent auditor for LL144 compliance and obtain required certifications independently.
How DecisionLedger Maps to NYC LL144
Every requirement of NYC Local Law 144 is addressed by built-in platform capabilities designed for HR and employment decision compliance.
Bias Audit
Automated statistical bias detection across race, sex, and intersectional categories. Calculate selection rates and disparate impact ratios for every AEDT-driven employment decision, with continuous monitoring that flags bias drift before it becomes a compliance issue.
Published Results Summary
Generate audit summary reports with selection rates, impact ratios, and demographic breakdowns formatted for public disclosure. One-click export of bias audit results in the format required for your organization's website publication.
Candidate Notice
Document and track that candidates were notified about AEDT use, the type of data collected, and the availability of an alternative selection process. Maintain timestamped notice records for every candidate interaction with your automated decision tools.
Independent Audit Trail
Immutable audit logs showing complete AEDT decision history for independent auditor review. Every scoring decision, input variable, model version, and output is logged with full provenance — ready for third-party auditor access at any time.
Annual Audit Cycle
Continuous bias monitoring with annual audit report generation and trend analysis. Track bias metrics over time, detect seasonal or demographic shifts, and generate year-over-year comparison reports that satisfy the annual audit requirement.
Data Retention
S3 Object Lock WORM storage for all AEDT audit records, decisions, and bias audit reports. Tamper-proof retention ensures audit evidence cannot be modified or deleted, meeting the law's record-keeping requirements with cryptographic integrity.
6
Requirements Mapped
Every LL144 section addressed
Automated
Bias Auditing
Continuous disparate impact analysis
Auditor-Ready
Evidence Quality
Exportable compliance packages
100%
Notice Tracking
Timestamped candidate records
NYC LL144 Compliance in Practice
Real scenarios showing how teams use DecisionLedger to meet NYC Local Law 144 requirements.
Preparing for the annual independent bias audit of all automated employment decision tools. Uses DecisionLedger to generate selection rate reports by demographic group, calculate disparate impact ratios across race and sex categories, and compile a complete audit evidence package with every AEDT decision logged — ready for the independent auditor's review.
Annual bias audit completed with zero findings, auditor commended the completeness of evidence documentation.
Needs to ensure every candidate screened by AEDT receives proper notice and that notice records are maintained. Uses DecisionLedger to track notice delivery timestamps, document the type of data collected by each AEDT, and maintain records showing alternative selection processes were offered — all with immutable, tamper-proof storage.
100% notice compliance with timestamped records for every candidate interaction, stored in WORM-compliant audit trail.
Why Choose DecisionLedger for NYC LL144 Compliance
Beyond Compliance
Don't just check the box — detect and remediate bias continuously. Proactive monitoring catches disparate impact shifts before your annual audit surfaces them.
HR-Native Models
30+ HR decision models designed for bias-aware employment decisions. Attrition risk, pay equity, workforce planning — all built with fairness constraints from day one.
Auditor-Ready Evidence
Generate complete audit packages that independent auditors can verify. Selection rates, impact ratios, model documentation, and decision logs — all in one exportable bundle.