iIn 2021, New York City enacted a measure that banned the use of Automated Employment Decision-Making Tools (“AEDT”) to (1) screen job candidates for employment, or (2) evaluate current employees for promotion, unless the tool has been subject to a “bias audit, conducted not more than one year prior to the use of the tool.” The law also required certain notifications regarding the use of AEDTs to be made to job seekers. The measure, known as Local Law 144 of 2021, was set to take effect on January 1, 2023.
In September 2022, the NYC Department of Consumer and Worker Protection (DCWP) issued guidance about the new ordinance and announced it was hosting an initial public hearing. Following the hearing, DWCP announced the law would not be enforced until April 1, 2023, due to the large number of public comments it received in response to prior hearings.
At the end of December 2022, DCWP released revised proposed rules to implement the ordinance and scheduled a further public hearing for January 23, 2023. These proposed rules modify the initial proposed rules. The comment period for the proposed regulations will remain open until January 16, 2023.
Here are some of the important highlights of the recently released rules:
Modification of the Definition of Automated Employment Decision Tools (AEDT)
Under the ordinance, an AEDT is defined 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 employment decisions that impact natural persons.
The latest proposed rules seek to clarify this definition by stating that 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.
Clarification Regarding Bias Audits
The proposed rules also aim to clarify the meaning and scope of bias audits and independent auditors.
Bias Audits – The proposed rules indicate that historical data may be used to conduct a bias audit. Notably, if there is insufficient historical data to conduct a statistically sound bias audit, test data may be used. But if test data is utilized, the required bias audit summary must explain the reason(s) historical data was not used and describe how the test data used was generated and obtained. And if multiple employers are using the same AEDT, they may rely upon the same bias audit so long as they provide historical data, if available, for the independent auditor to consider in such bias audit. Employers must ensure that they are relying on bias audits that are no greater than one year old.
Independent Auditors – The proposed rules further seek to end any uncertainty as to what constitutes an “independent auditor.” Under the new definition, an “independent auditor” may not be employed or have a financial interest in an employer or employment agency that seeks to use or continue to use an AEDT or in a vendor that developed or distributed the AEDT.
Understandably, these changes only represent a fraction of the proposed rules that will be discussed at the upcoming hearing.
