AI HireTech Vendor: Case Study

Written by Shea Brown

Posted on 11/22/2023
In Case Study

AI HireTech Vendor: Case Study


NYC passed Local Law No. 144, which requires automated employment decision tools (AEDTs) to be audited for bias on a yearly basis. The audits are typically conducted through intensive hands-on technical testing by external experts, which can be expensive and time-consuming.



BABL AI conducted a criteria-based assurance process to satisfy Local Law 144’s demand for a bias audit to be an “impartial evaluation by an independent auditor.” We have synthesized our experience performing direct testing for algorithmic bias and emerging best practices and standards to develop transparent, binary audit criteria that allow employers and vendors using AEDTs to conduct their own bias testing that trained BABL AI auditors can independently verify.


Assurance that AI Hiretech vendors have satisfied the law and conform with best practices in AI governance and risk management.

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