NYC Local Law 144

Local Law 144 of 2021 is New York City's law on automated employment decision tools (AEDTs). It sits in the New York City Administrative Code at §§ 20-870 through 20-874 (Title 20, Chapter 5, Subchapter 25) and is implemented by the Department of Consumer and Worker Protection (DCWP) through its rules at 6 RCNY §§ 5-300 through 5-304. In the city, an employer or employment agency may not use an AEDT to screen a candidate for employment or an employee for promotion unless the tool has been the subject of a bias audit by an independent auditor no more than one year before the use, the audit date, a summary of the results, and the tool's distribution date are publicly posted before the use (and kept posted for six months after the last use), and candidates and employees who reside in the city receive notice at least 10 business days before the tool is used to assess them; the tool's data type, source, and retention policy must also be posted on the employment section of the website, with a 30-day written-request route and explained withholding where disclosure is prohibited (6 RCNY § 5-304(d)). The law took effect on January 1, 2023 and DCWP has enforced it since July 5, 2023.

Modulos models the law as a single application-level template, MFF-27, with the Regulation label. There is no organization-level twin: every duty in the law attaches to the use of one specific tool, which is the Modulos project model. This page orients you on what the law requires, who it reaches, how the template is structured, and where to go next.

Quick decision — is this framework for you?

• You screen candidates for a job located at least part time in a New York City office (or fully remote but associated with one), or through an employment agency located in the city, or employees for promotion in the city, with a tool that scores, ranks, classifies, or recommends → this framework applies if the tool also meets the AEDT definition: a qualifying computational technique whose simplified output is relied on solely, weighted more than any other criterion, or used to overrule conclusions from other factors. Start with Scope and applicability to confirm every element and record the determination.
• You are a vendor that sells such a tool → the law places the duties on the employer or employment agency that uses the tool, not on you. You can still run MFF-27 for a tool for which you arrange an audit by an independent auditor on behalf of deployers (pooled audits are permitted under conditions), but the control questions address the deployer. See The bias audit and its data.
• The AI-application project for the tool already carries the EU AI Act, NIST AI RMF, or IEEE 7003 → add MFF-27 to the same project: the fairness, data-bias, and workplace-transparency controls are shared, so each stays one control instance there, and Evidence attached to its components supports the same claims for both frameworks. Depending on the template, 4 of the 5 reused controls are shared with the EU AI Act, 2 with NIST AI RMF, 3 with IEEE 7003; the 4 Local Law 144-specific controls are new. See Operationalizing Local Law 144 in Modulos.
• You want a compact, per-tool template → MFF-27 is six requirements, and each of the audit, publication, notice, and data-disclosure duties maps to one control. Other federal, state, and local employment laws are analyzed separately.

TL;DR

• The law: N.Y.C. Admin. Code §§ 20-870–874, enacted as Local Law 144 of 2021 (passed by the Council on November 10, 2021 and returned unsigned by the Mayor on December 13, 2021), effective January 1, 2023, enforced by DCWP since July 5, 2023. Implementing rules: 6 RCNY §§ 5-300–5-304.
• Three conditions on use (§ 20-871): an annual bias audit by an independent auditor with selection-rate and impact-ratio calculations for selection or classification functions and median-score, scoring-rate, and impact-ratio calculations for scoring functions (both sets where the tool does both) across sex, race/ethnicity, and intersectional categories; public posting before use of the date of the most recent bias audit, the required summary, and the tool's distribution date, kept up for at least six months after the last use; and 10-business-day notice to candidates and employees who reside in the city. Under 6 RCNY § 5-304(d), the tool's data type, source, and retention policy are also posted with written-request instructions, requests are answered within 30 days, and disclosure the law prohibits is withheld with an explanation.
• What it does not require: remediation of adverse results. The law sets no impact-ratio threshold; discrimination itself is governed by federal, state, and city human-rights law.
• Penalties (§ 20-872): not more than $500 for a first violation and for each additional violation occurring on the same day as the first, and $500 to $1,500 for each subsequent violation; each day on which an AEDT is used in violation of § 20-871(a), and each failure under § 20-871(b)(1), (2), or (3), is a separate violation.
• Modulos: one app-only template, MFF-27 (templates 1.0.29), 6 requirements (MRF-476–MRF-481), 9 distinct controls (4 new, 5 reused). No scoping questionnaire and no framework-specific tag family.

Primary sources

Local Law 144 of 2021 (Int 1894-2020), N.Y.C. Administrative Code §§ 20-870–874: New York City Council legislative record. DCWP final rules, 6 RCNY §§ 5-300–5-304: Notice of Adoption (PDF). DCWP, Automated Employment Decision Tools: Frequently Asked Questions (June 29, 2023) and DCWP AEDT page. Always verify claims against the current published text.

Key facts

Legislator

New York City Council (Local Law 144 of 2021)

Instrument

N.Y.C. Admin. Code §§ 20-870–874 and DCWP rules 6 RCNY §§ 5-300–5-304 (Regulation label in Modulos)

In effect

January 1, 2023; enforced since July 5, 2023

Enforced by

NYC Department of Consumer and Worker Protection (DCWP)

Covers

Employers and employment agencies using an AEDT to screen candidates for employment or employees for promotion in New York City

Modulos template

MFF-27 (application, one project per AEDT): 6 requirements, 9 controls

What the law requires

The statute is short and the rules do the detailed work. The table groups the provisions the way the Modulos template does.

Provision	What it holds
§ 20-870; 6 RCNY § 5-300 — Definitions	What an automated employment decision tool is (the computational-process definition and its exclusions), what an employment decision is (screening for hire or promotion within the city), and the rules' definitions of simplified output, "substantially assist or replace", candidate for employment, bias audit, independent auditor, selection rate, scoring rate, impact ratio, category, historical data, test data, and distribution date.
§ 20-871(a)(1); 6 RCNY §§ 5-301, 5-302 — The bias audit	Use is unlawful unless the tool has been the subject of a bias audit no more than one year before the use. The rules set the calculations (selection rates and impact ratios for selection or classification functions; the full-sample median, scoring rates, and impact ratios for scoring functions; both sets where the tool does both; separately for sex, race/ethnicity, and intersectional categories), the unknown-category count, the 2 percent exclusion rule, and the data requirements (historical data by default, pooling conditions, test-data fallback).
§ 20-871(a)(2); 6 RCNY § 5-303 — Publication	Before use, the employment section of the website must carry the date of the most recent bias audit, a summary of its results, and the tool's distribution date, and keep them posted for at least six months after the tool was last used for an employment decision.
§ 20-871(b)(1)–(2); 6 RCNY § 5-304(a)–(c) — Notice	Candidates and employees who reside in the city are told, at least 10 business days before use, that an AEDT will be used and which job qualifications and characteristics it assesses, with instructions for requesting an alternative selection process or accommodation, through a channel the rules permit for their group.
§ 20-871(b)(3); 6 RCNY § 5-304(d) — Data transparency	The type of data collected for the tool, its source, and the data retention policy are posted on the employment section of the website, with request instructions and a 30-day response to written requests; disclosure that would violate law or interfere with a law enforcement investigation is withheld with an explanation.
§ 20-872; 6 RCNY § 6-81 — Penalties	Civil penalties per violation, with each day of non-compliant use and each missed notice counting separately.
§ 20-874 — Construction	The subchapter does not limit any candidate's or employee's right to bring a civil action, or the authority of the New York City Commission on Human Rights to enforce Title 8.

Who is covered

The duties fall on the employer or employment agency that uses the tool to make an employment decision. Under § 20-870 an employment decision is "to screen candidates for employment or employees for promotion within the city." Three points from the DCWP FAQ shape the perimeter:

• "Used in the city" (FAQ I.4): the law applies when the job location is an office in New York City at least part time; or the job is fully remote but the location associated with it is an office in the city; or the employment agency using the AEDT is located in the city (or, if it is not, one of the first two holds).
• Screening, not sourcing (FAQ I.5–I.6): using a tool to scan a resume bank, conduct outreach, or invite applications is out of scope; screening people who applied for a specific position, at any point of the hiring or promotion process, is in scope.
• Deployer, not vendor (FAQ V.1–V.2): the vendor that developed the tool is not responsible under the law, even if it commissions the bias audit. The deployer remains responsible for ensuring a compliant audit exists before use.

The notice duties attach to candidates and employees who reside in New York City (§ 20-871(b)); residence of the individual, not the location of the role, drives them.

→ Full treatment, including the three-prong "substantially assist or replace" test and the penalty mechanics: Scope and applicability.

How Modulos models it

Modulos ships Local Law 144 as one application-level template. It carries the Regulation label and the nyc-ll144.svg icon.

Template	Project type	Holds	Requirements
MFF-27 — NYC Local Law 144	AI application	The applicability determination, the annual independent bias audit and its data rules, the publication of results, the pre-use notice, and the data transparency disclosures for one automated employment decision tool	6 (MRF-476–MRF-481)

One MFF-27 project assesses one AEDT. An employer using three screening tools for city roles runs three projects, each with its own control instances and Evidence library; where a tool's project already carries another framework, the shared controls (fairness metrics, bias assessment, data bias assessment) serve both frameworks in that project. There is no scoping questionnaire and no framework-specific tag family: MRF-476 records the in-or-out decision inside the project.

The six requirements group into three coverage areas, each with its own topic page.

1. Scope and applicability

Whether the tool is an AEDT used in the city: the computational-process definition, the simplified-output test, the three prongs of "substantially assist or replace", the two-limb technique test, the "used in the city" test, and the candidate definition (MRF-476), plus who is responsible and what a violation costs.

→ Deep dive: Scope and applicability.

2. The bias audit and its data

The annual audit by an independent auditor with selection-rate and impact-ratio calculations for selection or classification functions and median-score, scoring-rate, and impact-ratio calculations for scoring functions (both sets where the tool does both), the EEO-1 categories including intersectional ones, the unknown-category count, and the 2 percent exclusion (MRF-477); and the data the audit may rest on: historical data by default, pooled data under conditions, test data as a fallback, no imputed demographics (MRF-478).

→ Deep dive: The bias audit and its data.

3. Publication and notices

The public posting of the audit date, the required summary, and the distribution date before use, with the six-month retention (MRF-479), the 10-business-day notice to candidates and employees with its channels per audience (MRF-480), and the data-transparency disclosures with the 30-day request route (MRF-481).

→ Deep dive: Publication and notices.

What the law does not require

Two boundaries matter for how you use the framework, and both come from DCWP's own FAQ.

• No remediation duty. Local Law 144 requires the audit and the transparency; it prescribes no action based on the audit's results (FAQ II.2). Federal, state, and New York City anti-discrimination laws apply independently, and DCWP refers discrimination claims to the New York City Commission on Human Rights (FAQ VII.2). DCWP's Statement of Basis and Purpose says the required calculations are consistent with the EEOC Uniform Guidelines (29 C.F.R. § 1607.4); the four-fifths (80 percent) benchmark of that guideline is a federal selection-rate reference point. It is not a threshold set by Local Law 144, it says nothing about the scoring-rate calculation, and the framework never treats it as one. In Modulos, adverse ratios route into the fairness and bias controls (MCF-42, MCF-43) that the deployer operates for its own reasons and under other frameworks.
• No alternative selection process. The notice must include instructions for requesting an alternative selection process or a reasonable accommodation under other laws, but 6 RCNY § 5-304(a) states: "Nothing in this subchapter requires an employer or employment agency to provide an alternative selection process." Reasonable-accommodation duties under other laws apply independently.

Enforcement and penalties

DCWP enforces the law. Under § 20-872 a first violation, and each additional violation occurring on the same day as the first, carries a civil penalty of not more than $500; each subsequent violation carries $500 to $1,500. Each day on which a tool is used in violation of § 20-871(a) is a separate violation, and each failure to provide a notice required by § 20-871(b) is a separate violation. The DCWP penalty schedule (6 RCNY § 6-81) lists $375 for a first violation ($500 on default), $1,350 for a second ($1,500 on default), and $1,500 for a third or later violation; for schedule purposes a second or later violation is a violation of the same provision by the same respondent, established by plea, decision, or settlement, within two years of the prior one, and each provision charged in a notice of violation is a separate violation. § 20-874 is a construction clause: the subchapter does not limit any candidate's or employee's right to bring a civil action, or the authority of the New York City Commission on Human Rights under Title 8; it does not itself state that Local Law 144 creates a private cause of action.

On December 2, 2025 the New York State Comptroller published an audit of DCWP's enforcement of the law. It found that 75 percent of test calls to 311 on AEDT issues were misrouted and never reached DCWP, and that among 32 companies DCWP had reviewed and found one issue with, the Comptroller's auditors identified at least 17 potential violations. DCWP concurred with the findings and committed to fixing the 311 routing, cross-training staff, adopting written enforcement policies, requiring tool demonstrations during investigations, and moving to proactive rather than complaint-driven enforcement. The framework's content is anchored to the law, the rules, and the FAQ; the enforcement posture is context for planning, not a source of requirements.

How Modulos operationalizes Local Law 144

Each MFF-27 requirement is evidenced through its linked controls; the Requirement Owner reviews the completed controls and marks the Requirement as Fulfilled. The requirements and the four new controls carry the Local Law 144-specific tests, calculations, conditions, and clocks (the three-prong test, the calculation set, the pooling conditions, the notice channels); the five reused controls carry no Local Law 144-specific wording.

• 4 new controls carry the tool-specific duties: MCF-684 (independent AEDT bias audit, covering both the calculations and the data rules), MCF-685 (public disclosure of bias audit results), MCF-686 (pre-use notice to candidates and employees), and MCF-687 (AEDT data transparency disclosures).
• 5 reused controls carry the practice the deployer needs around them: MCF-16 (risk tiering, recording the AEDT determination), MCF-32 (data bias assessment), MCF-42 (model fairness metrics), MCF-43 (model bias assessment), and MCF-167 (transparent deployment at workplace). All five are shared with other templates: MCF-32, MCF-42, MCF-43, and MCF-167 with the EU AI Act, MCF-32 and MCF-167 with NIST AI RMF, and MCF-32, MCF-42, and MCF-43 with IEEE 7003, MAS FEAT, and UAE Consumer AI. In a project that carries one of those templates alongside MFF-27, the shared control is one instance, and Evidence attached to its components supports the same claims for every mapped Requirement in that project; separate per-tool projects keep separate control instances and Evidence libraries.

Framework mapping

Four layers, one reusable column.

Frameworks

EU AI ActRegulatory

ISO 42001Standard

Requirements

Art. 9.1Risk management

Art. 10.2Data governance

6.1.1Risk assessment

Components

Risk identification

Impact analysis

Evidence

Risk registerDocument

Test resultsArtifact

Controls

The reusable column

One control satisfies many requirements across many frameworks, and groups the components and evidence beneath them.

Risk assessment process

Data validation checks

Reusable

Edge from any layer card crosses into the Controls column — the same control may serve a regulatory article, a standards clause, a downstream component, and the evidence that closes it.

→ Full rollout: Operationalizing Local Law 144 in Modulos: project structure, the requirement mapping table, the four new controls, the reuse table, the rollout sequence, and the evidence model.

Where to go next

Scope and applicability

The AEDT definition, the three-prong test, the used-in-the-city test, responsibility, and penalties — MRF-476

The bias audit and its data

Independent auditor, selection and scoring rates, impact ratios, categories, the 2 percent rule, and the data requirements — MRF-477, MRF-478

Publication and notices

Posting the audit date, summary, and distribution date, the 10-business-day notice, and the data-transparency disclosures — MRF-479–481

Operationalizing in Modulos

The MFF-27 rollout: mapping table, the four new controls, reuse, sequence, and evidence

Frequently asked questions about NYC Local Law 144

What is NYC Local Law 144?

Local Law 144 of 2021 is New York City's law on automated employment decision tools (AEDTs), codified at N.Y.C. Administrative Code §§ 20-870 through 20-874 and implemented by the Department of Consumer and Worker Protection (DCWP) rules at 6 RCNY §§ 5-300 through 5-304. It makes it unlawful for an employer or employment agency to use an AEDT to screen a candidate for employment or an employee for promotion in the city unless the tool has been the subject of a bias audit by an independent auditor no more than one year before the use; the date of the most recent audit, the required summary of its results, and the tool's distribution date are publicly posted before the use and kept posted for at least six months after the latest use; and candidates and employees who reside in the city receive notice at least 10 business days before the tool is used to assess them. Separately, 6 RCNY § 5-304(d) requires the tool's data type, data source, and data retention policy to be posted clearly and conspicuously on the employment section of the website with instructions for a written request, written requests to be answered within 30 days, and information whose disclosure would violate law or interfere with a law enforcement investigation to be withheld with an explanation to the requester. The law took effect on January 1, 2023 and has been enforced by DCWP since July 5, 2023.

Who is covered by Local Law 144?

Employers and employment agencies that use an automated employment decision tool to screen candidates for employment or employees for promotion in New York City. Under the DCWP FAQ, the law applies when the job location is an office in the city at least part time, when the job is fully remote but the location associated with it is an office in the city, or when the employment agency using the tool is located in the city. The employer or employment agency that uses the tool is responsible for compliance; the vendor that developed the tool is not, even if the vendor arranges the bias audit. Notice duties attach to candidates and employees who reside in New York City. Scope and applicability walks through each test.

What is an automated employment decision tool under Local Law 144?

Under § 20-870, an automated employment decision tool is 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 DCWP rules narrow "substantially assist or replace" to three situations: relying solely on the simplified output, weighting it more than any other criterion in a set, or using it to overrule conclusions derived from other factors including human decision-making. The statute lists junk email filters, firewalls, antivirus software, calculators, spreadsheets, databases, data sets, and other data compilations as examples of excluded tools, but only where the tool does not automate, support, substantially assist, or replace discretionary decision-making and does not materially impact natural persons; the exclusion turns on function and impact, not on the label. Under 6 RCNY section 5-300, an output that only translates or transcribes existing text is not a simplified output.

What must a Local Law 144 bias audit contain?

A bias audit is an impartial evaluation by an independent auditor. Where the tool selects or classifies people, the audit must calculate the selection rate and the impact ratio for each category; where it scores people, it must calculate the median score for the full sample, the scoring rate for each category, and the impact ratio for each category. The calculations run separately for sex categories, race/ethnicity categories, and intersectional categories, using the EEO-1 Component 1 categories, and per classification group where the tool classifies people into groups. The audit must state the number of individuals assessed that fall within an unknown category. The auditor may exclude a category representing less than 2 percent of the data from the impact-ratio calculations only, with a justification and with the excluded category's count and rate still reported. The audit must use historical data of the tool; pooled data from other employers and test data are allowed only under the conditions of 6 RCNY § 5-302, and imputed or inferred demographic data may not be used. The bias audit and its data has the definitions and the worked logic.

Does Local Law 144 require an employer to fix a biased tool?

No. Local Law 144 requires the bias audit, the publication of its results, and the notices; it prescribes no action based on the audit's results and sets no impact-ratio threshold. The DCWP FAQ states that federal, state, and New York City anti-discrimination laws apply independently (FAQ II.2) and that DCWP refers discrimination claims to the New York City Commission on Human Rights (FAQ VII.2). DCWP's Statement of Basis and Purpose says the required calculations are consistent with the EEOC Uniform Guidelines on Employee Selection Procedures (29 C.F.R. § 1607.4); the four-fifths (80 percent) benchmark of that guideline is a federal selection-rate reference point, not a threshold set by Local Law 144 and not a rule for the scoring-rate calculation.

What are the penalties for violating Local Law 144?

Under § 20-872, a first violation, and each additional violation occurring on the same day as the first, carries a civil penalty of not more than $500, and each subsequent violation carries between $500 and $1,500. Each day on which an automated employment decision tool is used in violation of § 20-871(a) is a separate violation, and each failure to provide a notice required by § 20-871(b) is a separate violation. The DCWP penalty schedule at 6 RCNY § 6-81 lists $375 for a first violation ($500 on default), $1,350 for a second ($1,500 on default), and $1,500 for a third or later violation; for schedule purposes a second or later violation is a violation of the same provision by the same respondent, established by plea, decision, or settlement, within two years of the prior one, and each provision charged in a notice of violation is a separate violation. § 20-874 is a construction clause: the subchapter does not limit any candidate's or employee's right to bring a civil action, or the authority of the New York City Commission on Human Rights under Title 8; it does not itself state that Local Law 144 creates a private cause of action.

How does Modulos model Local Law 144?

As one application-level template, MFF-27 NYC Local Law 144, carrying the Regulation label (templates 1.0.29). There is no organization-level twin, because every duty in the law attaches to the use of one specific tool; the recommended structure is one MFF-27 project per automated employment decision tool. The template holds 6 requirements, MRF-476 through MRF-481: AEDT applicability determination, the annual independent bias audit, the bias audit data requirements, the publication of bias audit results, the candidate and employee notice, and the data transparency disclosures. They map to 9 distinct controls: 4 new controls (MCF-684 independent AEDT bias audit, MCF-685 public disclosure of bias audit results, MCF-686 pre-use notice to candidates and employees, MCF-687 AEDT data transparency disclosures) and 5 reused controls shared with other templates (MCF-16, MCF-32, MCF-42, MCF-43, MCF-167): the EU AI Act shares 4 of them, NIST AI RMF 2, and IEEE 7003 3.

See it in Modulos

Modulos runs NYC Local Law 144 as a per-tool program in MFF-27: the applicability decision, the annual independent bias audit, the public posting, the notices, and the data disclosures, evidenced in one project per tool.

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Source attribution

This page summarizes Local Law 144 of 2021 (N.Y.C. Administrative Code §§ 20-870–874), the DCWP rules at 6 RCNY §§ 5-300–5-304 (Notice of Adoption, April 6, 2023), the DCWP penalty schedule at 6 RCNY § 6-81, and DCWP's Automated Employment Decision Tools: Frequently Asked Questions (June 29, 2023). The enforcement context cites the New York State Comptroller's audit report Enforcement of Local Law 144 (Automated Employment Decision Tools) of December 2, 2025. US federal, state, and municipal edicts are public domain; quoted passages are verbatim from the certified law text and the adopted rules. Requirement and control codes (MFF-27, MRF-, MCF-) are Modulos template identifiers, not references used by the law.

Disclaimer

This page is for general informational purposes and does not constitute legal advice. Local Law 144 operates alongside federal, New York State, and New York City anti-discrimination law, which it does not displace. Always verify against the current published text of the law and the DCWP rules and consult qualified advisers.