Creates standards for independent bias auditing of automated employment decision tools.

A1021

ASSEMBLY, No. 1021

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.