Re: Proposed Rules, NYC Department of Consumer and Worker Protection; Automated Employment Decision Tools (Updated); (January 23, 2023)
Dear Commissioner Mayuga:
The U.S. Chamber of Commerce’s Chamber of Technology Engagement Centers (C_TEC) appreciates the opportunity to provide further feedback to the Department of Consumer and Worker Protection (DCWP) on the proposed rules for “Requirement for the use of Automated Employment Decision Tools.” As we stated in our first filing, we believe that 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, and A.I. has become an essential tool for employers to use to avoid their own unconscious bias in the hiring process.
C_TEC has long recognized that “fostering public trust and trustworthiness in A.I. technologies is necessary to advance its responsible development, deployment, and use.” We believe it is essential that DCWP make sure that the rules implementing Int. 1894-2020 in relation to “automated employment decision tools,” are made in a considerate and balanced manner to ensure that the deployment of such tools benefits the employer/employment agency, employee, and/or independent contractor to streamline the process.
We are concerned that the regulations, as currently drafted, would impede the ability of businesses to find and hire qualified candidates in New York City, by reducing the number of candidates that may be considered for an open position. Such a scenario, during our current challenging time of an acute labor shortage, deprives businesses of the tools that would allow for a review of a larger volume of resumes. Our comments seek to highlight many of the areas in which regulations can be better tailored to help the business community as well as candidates for employment.
Definition of Independent Auditor: The current definition of “independent auditor” is overly restrictive, resulting in higher costs and potential obstacles in hiring. While outside assistance should never be prohibited, it should be noted that there is a well-documented risk[1] of engaging third-party auditors. There currently are no universal standards and certifications regarding third-party audits. This means there is no guarantee that auditors can deliver verifiable measurement methods that are valid, reliable, safe, secure, and accountable. For this reason, we would encourage the definition to be changed to how it was initially proposed to mean “a person or group that is not involved in using or developing an AEDT that is responsible for conducting a bias audit of such AEDT.”
Definition of Automated Employment Decision Tool: We ask for the following changes to the definition of “automated employment decision tool.” We would ask the following to be stripped from the current definition “(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.” Furthermore, we would 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."
Bias Audit: The examples provided in subsections (b) and (c) of 5-301 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 (b):
- In the example, strike "provides historical data" and all that follows and replace it with "uses test data to conduct a bias audit as follows:"
We request the following changes to subsection (c):
- In the example, strike the word “planned” from the phrase “planned use of the AEDT.”
- Also, in the example, strike "provides historical data" and replace it with "uses 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 or complete demographic data.
In section 5-303, 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." Further, the current language in the proposed rule is inconsistent as the definition of “impact ratio” includes either selection rate “or” scoring rate (whereas the wording in the publication requirement mistakenly requires publishing the impact ratio “and” the selection rate).
Data Requirements: C_TEC would also like to highlight our concerns with section 5-302 on data requirements. Specifically, we would ask for clarification on how historical data is made available. There are many practical implementation challenges with using historical data. For instance, the data may reside with multiple entities, making it impossible to compile and share. Furthermore, the sharing of such data introduces privacy concerns and could be used by vendor competitors to create their own Automated Employment Decision System. For this reason, we would encourage that for any vendor-initiated audits, the test data should be the default instead of historical data.
Vendor Audits: The proposed rules contain an example in section 5-301(b) 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. It should also make clear that “historical data” may not be available and “test data” would be sufficient.
Lookback Period: While we appreciate that the DCWP provided a temporary delay in the enforcement of the AEDT law until April 15, 2023, in order to provide final rules, the U.S. Chamber strongly encourages the Department to provide a lookback period from April 15, 2023 of at least twelve (12) months from such date to businesses and organizations as they look to implement the final rule.
Conclusion
We appreciate the opportunity to comment on the implementing rules. We believe it is essential that we get these regulations correct so that New York City does not impose overly broad requirements, which in turn could create significant uncertainty regarding the use of automated employment decision tools in hiring.
Any potential limitation of the use of technology for hiring purposes for businesses could lead to unnecessary barriers to finding qualified candidates for a job. This is not an appropriate policy choice, as we are in a historically tight labor market. Accordingly, we believe that businesses should be able to use tools to identify as wide a pool of applicants as possible. The current draft regulations deprive businesses of the ability to do so. This is also harmful to those who are seeking employment as well.
Automated employment decision tools are essential in helping streamline the hiring and promotion process, so we ask that you make the following above-proposed changes to give the business community the necessary certainty they will need. If you have any questions, do not hesitate to contact Michael Richards at mrichards@uschamber.com.
Sincerely,
Tom Quaadman
Executive Vice President
Chamber Technology Engagement Center
U.S. Chamber of Commerce
[1] https://www.gmfus.org/sites/default/files/2022-11/Goodman%20%26%20Trehu%20-%20Algorithmic%20Auditing%20-%20paper.pdf
