Hogan’s Position on NYC Local Law 144



A photo of the New York City skyline glowing pink at dusk or dawn. The photo accompanies a statement about Hogan's position on NYC Local Law 144.

On July 5, 2023, the New York City Department of Consumer and Worker Protection will begin enforcing the updated NYC Local Law 144, which requires employers to obtain a third-party bias audit for “automated employment decision tools.”

NYC Local Law 144 does not apply to Hogan’s tools. This law only applies to automated employment decision tools. The law states:

“The term ‘automated employment decision tool’ means 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 term ‘automated employment decision tool’ does not include a tool that does not automate, support, substantially assist or replace discretionary decision-making processes and that does not materially impact natural persons, including, but not limited to, a junk email filter, firewall, antivirus software, calculator, spreadsheet, database, data set, or other compilation of data.”

Importantly,

“the phrase ‘to substantially assist or replace discretionary decision-making’ means to rely solely on a simplified output (score, tag, classification, ranking, etc.), with no other factors considered, or 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, or to use a simplified output to overrule or modify conclusions derived from other factors including human decision-making.”

In other words, NYC Local Law 144 only applies to decision tools that serve as the primary factor upon which decisions are based. Hogan does not recommend using its tools to serve as the only criteria or to override other important criteria in personnel decision-making processes. Rather, Hogan’s tools should be used as one consideration among many. For example, no matter how impressive a candidate’s personality profile, many jobs also require a certain level of job knowledge, which is difficult to determine with personality scores alone.

Furthermore,

“’Machine learning, statistical modeling, data analytics, or artificial intelligence’ means a group of mathematical, computer-based techniques:

i. 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

ii. 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.”

Here, both bullets must be met for purposes of meeting this definition. Although Hogan’s tools can be used to generate predictions (i), humans at Hogan, not computers, identify the inputs and importance of such inputs (ii). Therefore, Hogan’s tools do not meet the second bullet.

In sum, Hogan’s tools are not “automated employment decision tools” under NYC Local Law 144 because they are not used to “substantially assist or replace discretionary decision-making” and they do not use “machine learning, statistical modeling, data analytics, or artificial intelligence” as defined by the law.