Bill Text: NJ A1021 | 2026-2027 | Regular Session | Introduced
Bill Title: Creates standards for independent bias auditing of automated employment decision tools.
Sponsorship: Partisan Bill (Democrat 1)
Status: (Introduced) 2026-01-13 - Introduced, Referred to Assembly Science, Innovation and Technology Committee [A1021 Detail]
Download: New_Jersey-2026-A1021-Introduced.html
STATE OF NEW JERSEY
222nd LEGISLATURE
PRE-FILED FOR INTRODUCTION IN THE 2026 SESSION
Sponsored by:
Assemblyman BALVIR SINGH
District 7 (Burlington)
SYNOPSIS
Creates standards for independent bias auditing of automated employment decision tools.
CURRENT VERSION OF TEXT
Introduced Pending Technical Review by Legislative Counsel.
An Act concerning automated employment decision tools and supplementing Title 34 of the Revised Statutes.
Be It Enacted by the Senate and General Assembly of the State of New Jersey:
1. As used in P.L. , c. (C. ) (pending before the Legislature as this bill):
"Automated employment decision tool" means a machine-based system that can, for a set of human-defined objectives provided by an employer or an individual acting on behalf of an employer, make predictions, recommendations, or decisions influencing recruitment, workforce, or employment decisions.
"Bias audit" means an impartial evaluation conducted by an independent auditor, including but not limited to:
a. rigorous assessment of an automated employment decision tool to determine its impact on persons of any category;
b. identification and documentation of any biases, risks, or potential discriminatory outcomes that arise from the automated employment decision tool's design, implementation, or use; and
c. clear actionable recommendations to avoid, manage, or mitigate, identified biases and risks, and to ensure the sage, secure and trustworthy use of the automated employment decision tool in employment decisions.
"Candidate for employment" means a person who has applied for a specific employment position by submitting the necessary information or items in the format required by the employer or employment agency.
"Category" means race, color, national origin, ethnicity, sex, gender identity, sexual orientation, age, religion, marital or familial status, disability, and deriving income from any public assistance program.
"Covered individual" means a candidate for employment or current employee being assessed by an automated employment decision tool to make an employment decision.
"Employer" includes any individual, partnership, association, corporation, and the State and any county, municipality, or school district in the State, or any agency, authority, department, bureau, or instrumentality thereof, employing any person.
"Employment decision" means to screen a candidate for employment or otherwise to help decide compensation or any other terms, conditions, or privileges of employment.
"Employment agency" means the same as that term is defined in section 1 of P.L.1989, c.331 (C.34:8-43).
"Impact ratio" means:
a. the ratio of the protected class that receives a favorable outcome and the proportion of the control class that receives a favorable outcome when the decision being made is binary, including but not limited to the decision to hire or not and the decision to promote or not; or
b. the ratio of the difference between the average protected class outcome and the average control class outcome to a measure of the standard deviation of the outcome across the overall population when the decision being made is not binary, including but not limited to the decision to increase base salary or compensation of an employee.
"Independent auditor" means a person or group that is capable of exercising objective and impartial judgment on all issues within the scope of a bias audit of an automated employment decision tool. An auditor shall not be considered independent if the auditor:
a. Is or was involved in using, developing, or distributing the automated employment decision tool;
b. At any point during the bias audit, has an employment relationship with an employer or employment agency that seeks to use or continue to use the automated employment decision tool or with a vendor that developed or distributes the automated employment decision tool; or
c. At any point during the bias audit, has a direct financial interest or a material indirect financial interest in an employer or employment agency that seeks to use or continue to use the automated employment decision tool or in a vendor that developed or distributed the automated employment decision tool.
"Machine learning, statistical modeling, data analytics, or artificial intelligence" means a group of rule-based, mathematical, or computation techniques:
a. that generate a prediction, prescription, recommendation, or decision, meaning an expected outcome for an observation, such as an assessment of a covered individual's fit or likelihood of success, or that generate a classification, meaning an assignment of an observation to a group, such as categorizations based on skill sets or aptitude; and
b. for which a computer program implementing the mathematical or computational technique, at least in part identifies the inputs, the relative importance placed on those inputs, and, if applicable, other parameters for the models in order to improve the accuracy of the task performed by the technique.
"Scoring rate" means the rate at which individuals in a category receive a score above the sample's median score, where the score has been calculated by an automated employment decision tool.
"Screen" means to make a favorable or unfavorable determination about whether a candidate being considered for employment or employee being considered for promotion, termination, or performance review should be selected or advanced in the hiring or promotion process.
"Selection rate" means the rate at which favorable or adverse reactions are taken regarding individuals in a category in the employment decision process by an automated employment decision tool. This rate may be calculated by dividing the number of individuals with favorable or unfavorable outcomes in the category by the total number of individuals in the category.
"Test data" means data used to conduct a bias audit that is not training data.
"Training data" means data used in an employer or employment agency's use of an automated employment decision tool to assess candidates for employment, termination, compensation changes, performance improvement, or employees for promotion.
2. a. An employer or employment agency shall not use or continue to use an automated employment decision tool if more than one year has passed since the most recent bias audit of the automated employment decision tool.
b. A bias audit shall, at a minimum:
(1) calculate the selection rate for each category or the scoring rate if the outcome is continuous for each category;
(2) calculate the impact ratio for each category;
(3) ensure that the calculations required in paragraphs (1) and (2) of this subsection separately calculate the impact of the automated employment decision tool on:
(a) sex categories, such as the impact ratio for selection of male candidates versus female candidates;
(b) race, color, national origin, and ethnicity categories, such as the impact ratio for selection of Hispanic or Latino candidates versus Black or African American Non-Hispanic or Non-Latino candidates;
(c) age categories, such as the impact ratio for selection of older covered individuals versus younger covered individuals;
(d) marital or familial status categories, such as the impact ratio for selection of married covered individuals versus unmarried covered individuals;
(e) disability categories, such as the impact ratio for selection of covered individuals with disabilities versus covered individuals without disabilities;
(f) religion categories; such as the impact ratio for selection of Hindu covered individuals versus Buddhist covered individuals;
(g) sexual orientation categories, such as the impact ratio for selection of heterosexual covered individuals versus covered individuals of other sexual orientations;
(h) gender identity categories, such as the impact ratio for selection of cisgender covered individuals versus transgender covered individuals;
(i) income source categories, such as the impact ratio for selection of covered individuals whose income is derived from any public assistance program versus covered individuals whose income is not derived from any public assistance program; and
(j) intersectional categories of sex, ethnicity, and race, such as the impact ratio for selection of Hispanic or Latino male candidates versus Non-Hispanic or Non-Latino Black or African American female candidates;
(4) ensure that the calculations in paragraphs (1), (2), and (3) of this subsection are performed for each group; and
(5) indicate the number of individuals the automated employment decision tool assessed that are not included in the required calculations because they fall within an unknown category.
c. Notwithstanding the requirements of paragraphs (2) and (3) of subsection b. of this section, an independent auditor may exclude a category that represents less than two percent of the data being used for the bias audit from the required calculations for impact ratio. Where such a category is excluded, the summary of results shall include the independent auditor's justification for the exclusion, as well as the number of applicants and scoring rate or selection rate for the excluded category.
3. a. A bias audit conducted pursuant to section 2 of P.L. , c. (C. ) (pending before the Legislature as this bill) shall use training data of the automated employment decision tool. The training data used to conduct a bias audit may be from one or more employers or employment agencies that use the automated employment decision tool. However, an individual employer or employment agency may rely on a bias audit of an automated employment decision tool that uses the training data of other employers or employment agencies only in the following circumstances:
(1) if that employer or employment agency provided training data from its own use of the automated employment decision tool to the independent auditor conducting the bias audit; or
(2) if that employer or employment agency has never used the automated employment decision tool.
b. Notwithstanding the requirements of subsection a. of this section, an employer or employment agency may rely on a bias audit that uses test data if insufficient training data is available to conduct a statistically significant bias audit. If a bias audit uses test data, the summary of results of the bias audit shall explain why training data was not used and describe how the test data used was generated and obtained.
4. This act shall take
effect on the first day of the seventh month next following the date of
enactment, except that the Commissioner of Labor and Workforce Development may
take any anticipatory administrative action in advance as shall be necessary
for the implementation of P.L. , c. (C. ) (pending before the
Legislature as this bill).
STATEMENT
This bill provides standards for the use of an independent bias audit if an employer elects to use an automated employment decision tool (AEDT) for an employment decision.
The bill defines AEDT to mean a machine-based system that can, for a set of human-defined objectives provided by an employer or an individual acting on behalf of an employer, make predictions, recommendations, or decisions influencing recruitment, workforce, or employment decisions.
The bill defines "bias audit" to mean an impartial evaluation conducted by an independent auditor, including but not limited to:
a. rigorous assessment of an AEDT to determine its impact on persons of any category, including race, color, national origin, ethnicity, sex, gender identity, sexual orientation, age, religion, marital or familial status, disability, and deriving income from any public assistance program;
b. identification and documentation of any biases, risks, or potential discriminatory outcomes that arise from the AEDT's design, implementation, or use; and
c. clear actionable recommendations to avoid, manage, or mitigate, identified biases and risks, and to ensure the sage, secure and trustworthy use of the AEDT in employment decisions.
Under the bill, an employer or employment agency is prohibited from using or continuing to use and AEDT if more than one year has passed since the most recent bias audit of the AEDT.
The bill includes minimum requirements for bias audits.
The bill also requires bias audits to use training data of the AEDT except in certain circumstances and provides requirements for when an individual employer or employment agency may use training data of other employers or employment agencies for the bias audit.
