Amid concerns about the use of artificial intelligence and algorithms in high-stakes decision-making, such as for making employment-related decisions, the New York City council passed a landmark piece of legislation that mandates bias audits of automated employment decision tools (AEDTs) being used to evaluate candidates for employment or employees for promotion within New York City.

Under Local Law 144, employers and employment agencies are required to commission independent, impartial bias audits of their tools, where, under the latest version of the Department of Consumer and Worker Protection’s (DCWP) proposed rules, bias should be determined using impact ratios based on outcomes for different subgroups. In this blog post, we outline the metrics required to conduct the bias audit, how small sample sizes can pose issues, and how they can be dealt with when carrying out audits.