The law focuses on regulating the use of Automated Employment Decision Tools (AEDTs). AEDTs are computational processes, such as machine learning, statistical modeling, data analytics, or artificial intelligence, that provide simplified output like scores, classifications, or recommendations. These tools are used to assist or replace discretionary decision-making in employment-related decisions that impact individuals.
Employers or employment agencies using AEDTs to screen candidates or employees for employment decisions must ensure that these tools have undergone a bias audit. The bias audit is an impartial evaluation conducted by an independent auditor to assess the AEDT's potential disparate impact on individuals based on protected categories.
Employers are required to make publicly available on their website a summary of the most recent bias audit results for the AEDT, along with the distribution date of the tool. This disclosure should be made prior to the use of the AEDT, allowing transparency and informing individuals about the potential biases associated with the tool.
We conduct thorough audits of your existing AEDT systems to identify potential biases and discriminatory patterns.
In accordance with NYC Local Law 144, we work with historical data provided by you. In the absence of sufficient historical data, we use cutting edge proprietary technologies to generate test data that covers all possible potential latent bias patterns and provide you with expert justification for the use of test data.
We provide audit summaries that are ready to for you to publish, as NYC Local Law 144 requires.
We retain your organization's information, documentation, and testing framework to make your yearly audits easy and efficient.
Our consulting group can advise you on strategies for mitigating bias in your AEDTs and any other machine learning models used by your organization.