NYC AEDT Bias Audit certification scheme applies to any entity deploying an AEDT within New York City. It also applies to AEDTs deployed for employment decisions or meaningful impact to employment situations impacting the residents of the City of New York

Nearly one in four organizations already use automation or artificial intelligence (AI) to support hiring, according to a February 2022 survey from the Society for Human Resource Management.

The law defines an automated employment decision tools (AEDTs) as any computational process, derived from machine learning, statistical modeling, data analytics, or artificial intelligence, that issues simplified output, including a score, classification, or recommendation, that is used to substantially assist or replace discretionary decision making for making employment decisions that impact natural persons. The phrase “to substantially assist or replace discretionary decision making” means:
i. to rely solely on a simplified output (score, tag, classification, ranking, etc.), with no other factors considered; or
ii. to use a simplified output as one of a set of criteria where the simplified output is weighted more than any other criterion in the set; or
iii. to use a simplified output to overrule conclusions derived from other factors including human decision-making.

1. When employment hiring decisions are being made with the use of AEDT, the law requires,
   1. AEDT undergo an annual “bias audit” by an “independent auditor” before use; and
   the results of the most recent bias audit and the AEDT’s distribution date are published on the employer’s or employment agency’s website.
2. Testing of the AEDT to assess its disparate impact on persons of any component 1 category required to be reported by employers in their EEO-1 reports. Example: composition of an employer’s workforce by race or ethnicity, sex and job categories.
3. Employers and employment agencies must publish the results of their annual bias on their publicly available website.
4. Candidates and employees residing in New York City must be notified before the AEDT is used.
5. Candidates have the right to request additional information about data handling practices, alternative selection processes, or accommodations.

According to the Local Law 144, “The term “bias audit” means an impartial evaluation by an independent auditor. Such bias audit shall include but not be limited to the testing of an automated employment decision tool to assess the tool’s disparate impact on persons of any component 1 category required to be reported by employers pursuant to subsection (c) of section 2000e-8 of title 42 of the United States code as specified in part 1602.7 of title 29 of the code of federal regulations.”

In summary, this means, it must, at a minimum, measure disparate impact (also called adverse impact) based on the protected categories of sex, race, or ethnic group (Title VII of the Civil Rights Act of 1964).

Bias defined as systematic and repeatable errors in a computer system that create unfair outcomes, applied specifically to protected categories.

Disparate Impact is defined as selection rate for any race, sex, or ethnic group which is less than four-fifths (4/5) (or 80%) of the rate for the group with the highest rate.

There is some strong history behind the law. The law is being hailed as the first federal legislation ever to address bias in employment hiring tools to be enacted in the United States.

On April 6, 2023, the Department of Consumer and Worker Protection announced that it will begin enforcement of the AEDT Law and Final Rule on July 5, 2023.

A brief history: The DCWP held two public hearings since it was first put into action in December 2021. The law was originally is anticipated to go into effect on first on Jan 1, 2023 and then was pushed to April 15, 2023. A notice of adoption of final rule was made on April 6, 2023.

The NYC DCPW can enforce the law and issue fines between $500 and $1,500 per violation, per day. The law also provides a private right of action for employees and candidates. 

Each tool that falls under the law that is not audited is a separate violation. So, a company that uses 3 automated tools, starting on the third day after violation, can potentially incur a penalty of $4,500 per day.

Failure to comply with the law also introduces other violations that should be considered in conjunction with the violation of the local law 144, such as –

• Employers or employment agencies should consider a range of penalties for violation of Title VII which can vary depending on the specific circumstances of the case.
• Additionally, the Equal Employment Opportunity Commission (EEOC) may also impose fines and other penalties for Title VII violations.

The scope of the NYC AEDT Audit Bias Audit and Independent Audit Certification will be executed across three stages – Current State Assessment, Gap Analysis and Reporting over reasonable pre-determined time period. The key objective of this audit is to determine whether your company’s governance, policies, procedures, and controls concerning bias definitions, practices and bias mitigation of AEDT are in accordance with the regulatory obligations. The results of the audit characterized with what is in compliance, which is partially met and where requirements are non-compliant along with evidence-based objective feedback.

Through our long-standing experience in assisting companies over the years with business transformations, risk management and compliance assessment, we collaborate with you to:

• Develop a clear understanding of your current business environment including the scope of work.
• Assess AEDT and data governance practices, including, but not limited to, data policies, data sources, and data quality throughout AEDT’s lifecycle.
• Evaluate the AEDT for potential sources ethical bias based on the regulatory obligations.
• Prepare a final audit report for collective review and finalization.

A job candidate perceives your company’s brand throughout the hiring process. Creating the right candidate experience is integral to your brand message. Regardless of how good your career site is or how enticing your job description may be, if incorrect AI-powered technology is used in the recruiting funnel, can potentially lead to ethical bias, deception, and unfair practices, resulting in a downward spiral for your brand.

There is no arguing that AI augmented hiring process creates superior benefits in funneling hiring performance and saving time, however number of market research have revealed biases at various steps in recruitment process.

When used correctly, AI can neutralize bias and positively impact your D&I initiatives.

Company’s candidate experience metrics are often viewed through candidate-centric lens. Don’t let your algorithms be inscrutable and force job seekers to confront a new kind of interview anxiety. 

Seize this compliance opportunity to set the bar high for ethical, equitable and responsible use of AEDT and its associated data, and a defensible posture for subsequent stream of regulatory obligations.

Let us help you take the right steps to protect your AEDT value.