Letter to the NYC DCWP on Automated Employment Decision Tools

Re: Comment on Proposed Rules

Dear Commissioner Mayuga:

The use of A.I. in the hiring and promoting process has been essential in helping streamline the review, outreach, vetting, and onboarding process of potential employees. The recent data from the Labor Statistics for the New York City Region indicates that “The city’s seasonally adjusted unemployment rate was 6.6 percent in August 2022, up 0.6 percent from July.” This increase in the unemployment rate is due to a “rise in the number of people entering the labor force.” In a time when the region is seeing growth in the labor market, and people are looking to enter the workforce, we feel it is essential that the City make sure that the rules implementing Int. 1894-2020 in relation to “automated employment decision tools,” are made in a thoughtful and balanced manner, which will allow for the deployment of such tools to benefit the employer, employee, and/or independent contractor to help streamline the process.

The U.S. Chamber of Commerce has long recognized that “fostering public trust and trustworthiness in A.I. technologies is necessary to advance its responsible development, deployment, and use.” For this reason, we at the Chamber appreciate the opportunity to provide the following comment on the New York City Automated Employment Decision Tools Regulation, which we believe will help provide more certainty to the framework.

Definition of Automated Employment Decision Tool. We urge you to revise the definition of “automated employment decision tool” and, more specifically, the definition of the phrase “to substantially assist or replace discretionary decision making.” First, we would ask that you strike the last phrase “or to use a simplified output to overrule or modify conclusions derived from other factors including human decision making. ” In its place, we ask that you add the following sentence: “Automated employment decision tool,’ or ‘AEDT,’ does not include the automated searching of resumes to identify candidate qualifications, including relevant skills or experience.

Furthermore, most employers do not use AEDT as the sole factor for determination of whom to employ but use it in a more holistic approach as one of many factors in evaluating a candidate. Although an employer may deploy an algorithm on every potential candidate, that does not mean that the output is always used by the employer. While an AEDT may review and/or score each candidate, an employer may still empower the hiring manager with the discretion to determine whom to interview and the amount of reliance and weight they put on the tool’s output. With hiring managers potentially weighing their expertise and analysis more than the AEDT output, we ask for clarification on category (2) (“to use a simplified output as one of a set of criteria where the output is weighted more than any other criterion in the set”).

Finally, if you choose not to delete category (3) (“to use a simplified output to overrule or modify conclusions derived from other factors including human decision making”), we ask that “or modify” be struck or clarification be provided on what it means to “modify” a conclusion.

Bias Audit: The examples provided in subsections (a) and (b) are both prescriptive in who bears responsibility for the bias audit (i.e., the employer/deployer or the vendor/developer) without accounting for the range of possible scenarios. For this reason, we prefer that the examples be made clear that they aren’t necessarily exhaustive of all scenarios and remove the specificity of responsibility in each of the two examples, allowing for flexibility to account for the range of scenarios.

We request the following changes to subsection (a):

  • Revise the initial phrase to read: “Where an AEDT is used to screen a candidate or employee for an employment decision, a bias audit required by § 20-871 of the Code must, at a minimum”
  • In the example, strike “historical data” and replace it with “test data.”

We request the following changes to subsection (b):

  • In the example, strike the word “planned” from the phrase “planned use of the AEDT.”
  • Also, in the example, strike “historical data” and replace it with “test data.”

Finally, both examples suggest that the bias audit should compare selection rates of not just gender and race/ethnicity – the usual categories required to be compared under the Uniform Guidelines of Employee Selection Procedures – but also on the intersectional categories of gender and race/ethnicity (e.g., Hispanic Males, Non-Hispanic Female Whites, etc.). Data on these intersectional categories, however, typically is not collected by employers or vendors, as applicants and employees are given the opportunity to separately self-identify their gender and their race/ethnicity. Furthermore, many employers and vendors do not collect any gender or race/ethnicity data on their applicants; please clarify how such employers and vendors should conduct a bias audit in the circumstance in which they do not have any demographic data.

Published Results: We ask for the addition of the following italicized phrase in section (a) “Prior to the use of an AEDT to screen a candidate or employee for an employment decision , employers and employment agencies in the city must make the following publicly available on the careers or jobs section of their website in a clear and conspicuous manner:”

We also suggest striking the phrase in subsection (a)(1) “the selection rates and impact ratios for all categories,” and replacing it with “a statement on adverse impact.”

Definition of Screen in relation to Employment Decisions: The law states that “employment decision” means “to screen candidates for employment or employees for promotion within the city.” The proposed rule defines “screen” as “to make a determination about whether someone should be selected or advanced in the hiring or promotion process.” We ask for clarity on how the use of some A.I. tools would fit within this definition.

Vendor Audits: The proposed rules contain an example in §5-301(a) that strongly implies that employers can rely upon bias audits commissioned by vendors using historic applicant data collected by the vendor and not the employer’s own data. We ask that the rule explicitly state that this is permissible and satisfies the “bias audit” requirement.

Frequency of Audits: The law states that an AEDT cannot be used unless a bias audit was “conducted no more than one year prior to the use of such tool.” It is not clear whether that language requires yearly bias audits of the tool or if conducting one audit on a tool is sufficient unless or until the tool is replaced or materially modified. The Statement of Basis and Purpose of the Proposed Rule states that a bias audit is required “within one year of use of the tool” which implies that the audit may take place within the 12 months which follow implementation of the tool. We understand this is not the intent, so this should be clarified.

Grace Period: While we understand the legislation requires the rules and regulations to go into effect by January 2023, the U.S. Chamber strongly encourages the Department to provide a grace period of at least twelve (12) months to businesses and organizations as they prepare to implement the final rule.

Conclusion: We appreciate the opportunity to comment on the implementing rules. It is essential that these regulations are implemented by New York City in a manner that does not impose overly broad requirements, which in turn could create significant uncertainty regarding the use of automated tools in hiring. Potential limitations of the use of technology for hiring purposes for businesses could lead to unnecessary barriers to finding qualified candidates for a job; this is particularly challenging during periods when we see both labor shortages and increases in the labor market, as businesses are put in a position where they receive more resumes/applications than they have the capability to review, which inhibits their ability to identify potential candidates. The use of automated employment decision tools is essential in helping streamline the hiring and promotion process. Thank you for considering the above proposed changes to give the business community the necessary certainty they will need. If you have questions, do not hesitate to contact Michael Richards at mrichards@uschamber.com.


Tom Quaadman
Executive Vice President
Chamber Technology Engagement Center
U.S. Chamber of Commerce