Notice of Adoption for NYC Automated Employment Decision Tools Law and Deferred Enforcement Date

April 14, 2023

By: Corinne E. Tierney

New York City’s Local Law 144 has received another update from the City’s Department of Consumer and Worker Protection (DCWP). As a reminder, the new law prohibits an employer or employment agency from using an automated employment decision tool in making an employment decision unless, prior to using the tool, the following requirements are met: (1) the tool has been subject to a bias audit within the last year; and (2) a summary of the results of the most recent bias audit and distribution data for the tool have been made publicly available on the employer or employment agency’s website. On Sept. 23, 2022, the DCWP proposed new rules to clarify the law. Please see our prior blog post for a more thorough summary of the law. On Dec. 23, 2022, the DCWP released a set of revised proposed rules which resulted in another public hearing on Jan. 23, 2023.

On April 6, 2023, following two proposed revisions to the law and two well-attended public hearings, the DCWP has finally filed its notice of adoption for the final set of rules that apply to Local Law 144. The DCWP’s summary of the changes to the final law includes:

• Modifying the definition of “machine learning, statistical modeling, data analytics, or artificial intelligence” to expand its scope;
• Adding a requirement that the bias audit indicate the number of individuals the AEDT assessed that are not included in the calculations because they fall within an unknown category, and requiring that number be included in the summary of results;
• Allowing an independent auditor to exclude a category that comprises less than 2% of the data being used for the bias audit from the calculations of impact ratio;
• Clarifying the examples of a bias audit;
• Clarifying when an employer or employment agency may rely on a bias audit conducted using the historical data of other employers or employment agencies;
• Providing examples of when an employer or employment agency may rely on a bias audit conducted with historical data, test data, or historical data from other employers and employment agencies;
• Clarifying that the number of applicants in a category and scoring rate of a category, if applicable, must be included in the summary of results.

With the DCWP’s summary in mind, we will flesh out some of the key takeaways from the adopted rules below.

Automated Employment Decision Tool. Under the final rule, “Automated employment decision tool” or “AEDT” means “Automated employment decision tool” as defined by § 20-870 of the New York City Administrative Code. 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; (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.

Machine Learning, Statistical Modeling, Data Analytics, or Artificial Intelligence. “Machine learning, statistical modeling, data analytics, or artificial intelligence” means a group of mathematical, computer-based techniques that “generate a prediction, meaning an expected outcome for an observation, such as an assessment of a candidate’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 “for which a computer 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 prediction or classification.”

Bias Audits. Under Local Law 144, an employer or employment agency may not use an AEDT as long as the tool has been subject to a bias audit conducted no more than one year prior to the use of the tool. A “bias audit” is defined as “an impartial evaluation by an independent auditor,” which includes “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” 42 U.S.C. § 2000e-8(c) and 29 C.F.R. § 1602.7. The proposals make it clearer that to satisfy the new law, a bias audit must, at a minimum: (1) “calculate the selection rate for each category”; (2) “calculate the impact ratio for each category”; (3) with respect to the previous two calculations, separately calculate the impact on: (i) sex categories; (ii) race/ethnicity categories; and (iii) intersectional categories of sex, ethnicity and race (e.g., impact ratio for selection of Hispanic or Latino male candidates vs. Not Hispanic or Latino Black or African American female candidates); (4) ensure that all of the calculations are “performed for each group, if an AEDT classifies candidates for employment or employees being considered for promotion into specified groups (e.g., leadership styles)”; and (5) “indicate the number of individuals the AEDT assessed that are not included in the required calculations because they fall within an unknown category.”

Additionally, and notwithstanding the requirements of paragraphs 2 and 3 above (and the similar requirements for a bias audit scoring candidates or employees considered for promotions), “an independent auditor may exclude a category that represents less than 2% of the data being used for the bias audit from the required calculations for impact ratio.” The final rules add that “[w]here such a category is excluded, the summary of rules must 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.”

One of the newer additions to Local Law 144 is the limited ability of an employer or employment agency to use historical data for its bias audit. Under the final rules, multiple employers or employment agencies which use the same AEDT may rely on the same bias audit conducted using historical data of other employers or employment agencies, but only if the employer or employment agency “provided historical data from its own use of the AEDT to the independent auditor conducting the bias audit or if such employer or employment agency has never used the AEDT.”

Independent Bias Auditor. Under the law, an independent bias 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 AEDT.” However, the DCWP has outlined several disqualifying characteristics for such an independent auditor. These disqualifying circumstances include a person or group that (i) “is or was involved in using, developing, or distributing the AEDT; (ii) 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 AEDT or with a vendor that developed or distributes the AEDT; or (iii) 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 AEDT or in a vendor that developed or distributed the AEDT.”

Published Summary. As explained in our last blog post, prior to the use of an AEDT, employers and employment agencies in the city are required make a summary of the bias audit results “publicly available on the careers or jobs section of their website in a clear and conspicuous manner”. The summary must include (1) the date of the most recent bias audit of the AEDT and a summary of its results, which shall include the source and explanation of the data used to conduct the bias audit, the number of individuals the AEDT assessed that fall within an unknown category, and the number of applicants or candidates, the selection or scoring rates, as applicable, and the impact ratios for all categories; and, (2) the distribution date of the AEDT.

This requirement can be met with “an active hyperlink to a website containing the required summary of results and distribution date, provided that such link is clearly identified as a link to results of the bias audit.” Finally, employers and employment agencies must keep the summary of results and distribution date posted for at least six (6) months after last using such AEDT for an employment decision.

Notice Requirements. Local Law 144 requires that employers provide at least 10 business days’ notice to candidates and employees who reside in New York City applying for positions or promotions that an AEDT will be used in connection with a given assessment or decision. This requirement may be satisfied by either (a) providing notice on the employment section of its website in a clear and conspicuous manner; (b) providing notice in a job posting; or (c) providing notice to candidates for employment via U.S. mail or e-mail. For candidates applying for a promotion, this notice requirement can be satisfied by providing “notice in a written policy or procedure that is provided to employees at least 10 business days before use of the AEDT.”

Employers should be aware that this notice must also include instructions “for how to request an alternative selection process or a reasonable accommodation under other laws, if available.” Importantly, the law clarifies that nothing in this subchapter requires an employer or employment agency to provide such an alternative selection process.

Delayed Enforcement Date. Another major update is that the DCWP announced it will defer enforcement of the law to July 5, 2023, almost three (3) months after its last scheduled enforcement date of April 15, 2023. This gives employers and employment agencies who may be subject to this law less than three (3) more months to determine any necessary compliance and potential next steps.

Here at Bond we will continue to monitor the law for additional developments. If you would like any assistance in preparing your organization for compliance with the New York City law on automated employment decision tools, please contact Corinne Tierney, any attorney in our labor and employment practice or the attorney at the firm with whom you are regularly in contact.