Audit your automated decision systems for bias and meet regulatory requirements with our comprehensive algorithmic fairness services
Expert guidance through every aspect of algorithmic fairness for organizations deploying automated decision systems
Comprehensive evaluation of your automated decision systems against fairness requirements. Our experts identify sources of bias, assess disparate impact, and develop detailed remediation plans.
Independent bias audits of Automated Employment Decision Tools (AEDTs) aligned with NYC Local Law 144 and emerging AI regulations.
Proactive monitoring and maintenance of your AI fairness program with periodic re-audits and drift detection.
End-to-end implementation of all algorithmic fairness and bias audit requirements
Robust evaluation of model outcomes across protected groups to detect and quantify bias
Technical and procedural safeguards for the data and models powering automated decisions
Comprehensive documentation and staff training programs
Structured approach to achieving and maintaining algorithmic fairness
Thorough evaluation of your model, data, and decision processes against fairness requirements
Independent execution of bias testing and statistical analysis
Continuous fairness monitoring and improvement
Strategic advantages for your organization
Build stronger trust with candidates, customers, and regulators through demonstrated commitment to fairness
Comprehensive protection against discrimination claims and regulatory violations
Improved AI operations through standardized, fair, and accountable processes
A robust, defensible methodology that protects your organization against discrimination claims as your AI evolves
Audit datasets that are complete, balanced, and diverse, built from real-world data with consent to use.
A defensible, timestamped record of every audit, ready for use in investigations and enforcement matters.
Accurate and defendable audits using complementary statistical techniques.
One audit engagement can satisfy multiple regulatory requirements simultaneously across US and global frameworks.
Every protected class is tested using disparate impact and counterfactual analysis, giving you defensible, audit-ready results aligned to key global regulations
| Protected Class | NYC LL 144 | EU AI Act | Colorado SB26-189 | Civil Rights Act (US) | California FEHA | Illinois HB 3773 |
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| Veteran Status | ||||||
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| Pregnancy & Reproductive Health | ||||||
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| Marital Status | ||||||
| Medical Condition | ||||||
| Criminal History |
Let’s talk about your AI bias audit requirements and develop a tailored approach.
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