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New Jersey's Senate Bill S2964 mandates independent bias audits for automated employment decision tools (AEDTs) to ensure compliance with discrimination laws. This legislation aims to enhance transparency and accountability in automated hiring practices.
Key Provisions
Employers must conduct bias audits of AEDTs at least annually.
Audits must include calculations for selection rates and impact ratios by demographic categories.
Employers cannot use an AEDT if more than one year has passed since the last audit.
Test data may be used for audits if historical data is insufficient.
Latest Legislative Action
Introduced in the Senate, Referred to Senate Labor Committee
Bill Sponsors
Name
Role
District
Andrew ZwickerD
Sponsor
SD-016
Compliance Checklist
Conduct an independent bias audit of your AEDT Who: Employers and employment agencies using AEDTs Deadline: Annually Penalty: Cannot use AEDT if audit is not conducted
Post audit results on your website Who: Employers and employment agencies Deadline: Within 30 days of audit completion Penalty: Non-compliance may lead to restrictions on AEDT use
Notify candidates about AEDT usage Who: Employers and employment agencies Deadline: At least 10 business days before using an AEDT Penalty: Potential legal challenges or complaints
Senate Bill S2964 requires employers and employment agencies in New Jersey to conduct independent bias audits of any automated employment decision tools (AEDTs) they use. These audits must be performed at least annually, and employers cannot use an AEDT if more than one year has passed since the last audit. The bill outlines specific calculations that must be included in the audits, such as selection rates and impact ratios across various demographic categories, ensuring that the tools do not discriminate based on sex, race, or ethnicity. The bill defines key terms such as 'automated employment decision tool' and 'bias audit,' establishing a framework for compliance. It emphasizes the importance of using historical data for audits but allows for the use of test data if historical data is insufficient.
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