automated employment decision tool
In plain wordsSoftware that scores, ranks or screens job candidates or employees. New York City requires employers using such tools to have them checked for bias every year and to tell applicants.
In New York City law, software that applies AI, machine learningmachine learning, n.: A way of building software that learns from examples instead of following rules written by a programmer. Shown thousands of labeled photos, for instance, a program can learn to recognize cats., statistical modeling or data analytics to reduce information about a job candidate or employee to a simple score, classification or recommendation, and that substantially assists or replaces human discretion in hiring or promotion. Under Local Law 144 of 2021, enforced from July 5, 2023, an employer or employment agency may use such a tool only if it has undergone an independent bias audit within the past year, a summary of results (selection rates and impact ratios by sex and race or ethnicity) is published, and candidates are notified at least ten business days before use; penalties run from $500 to $1,500 per violation. Researchers and a December 2025 state audit found low compliance and weak enforcement, partly because employers decide for themselves whether a tool 'substantially' assists decisions. Comparable duties appear in Illinois employment law and the Colorado AI ActColorado AI Act, prop. n.: A Colorado law, first passed in 2024, governing AI used to make important decisions about people, such as hiring, lending and housing. In 2026 it was rewritten as a narrower law that starts in 2027..
Before rolling out the résumé screener, the employer commissioned the annual bias audit the city requires for an automated employment decision tool.
Origin
Defined in New York City's Local Law 144, enacted in late 2021; after delays in writing implementing rules, the Department of Consumer and Worker Protection began enforcement on July 5, 2023, making it the first US law to require bias audits of AI hiring tools.
Usage note
The impact ratio compares each group's selection rate with that of the most-selected group, echoing the four-fifths rule of thumb used in US employment-discrimination analysis.
Related
- AI auditAI audit, n.: An independent check of an AI system, or of the company using it, against agreed standards — for example, testing whether a hiring tool treats women and men fairly.
- algorithmic biasalgorithmic bias, n.: Unfairness in software that judges or serves people: it consistently produces worse results for some groups, such as women, older people or ethnic minorities, often because it learned from skewed or incomplete records.
- disparate impactdisparate impact, n.: When a rule or system that treats everyone alike on paper still lands much harder on one group, such as women or older workers; the law can forbid this even if no one intended it.
- automated decision-makingautomated decision-making, n.: When a computer system, rather than a person, makes or effectively makes a decision about someone — such as approving credit, screening job applicants or flagging possible welfare fraud.
- algorithmic impact assessmentalgorithmic impact assessment, n.: A structured review, done before and during the use of an automated system, of whom it could affect and how — such as unfair treatment or privacy harms — and what will be done about it.
- Colorado AI ActColorado AI Act, prop. n.: A Colorado law, first passed in 2024, governing AI used to make important decisions about people, such as hiring, lending and housing. In 2026 it was rewritten as a narrower law that starts in 2027.
Defined in law or standards
New York City Administrative Code § 20-870 et seq. (Local Law 144 of 2021)
Mentioned in
AI auditAI audit, n.: An independent check of an AI system, or of the company using it, against agreed standards — for example, testing whether a hiring tool treats women and men fairly., algorithmic accountabilityalgorithmic accountability, n.: The idea that the people and organizations behind automated decision systems must be able to explain and justify those systems' effects, answer for the harm they cause, and fix it., automated decision-makingautomated decision-making, n.: When a computer system, rather than a person, makes or effectively makes a decision about someone — such as approving credit, screening job applicants or flagging possible welfare fraud.