Local Law 144 and Local Law 35
The one-paragraph answer
NYC AI laws apply to any employer using automated tools to make hiring decisions about NYC positions, and to city agencies using AI in official functions. Local Law 144 (2023) requires annual independent bias audits, public posting of results, and candidate notification for AI hiring tools. Local Law 35 (part of a broader disclosure framework) governs how NYC agencies must publish information about their AI use. Together they make NYC the most active US municipal AI regulator.
New York City has the country's largest labor market. Every national employer hires in NYC. When Local Law 144 took effect in 2023, it caught most employers off guard: any use of an "automated employment decision tool" for an NYC position triggered bias-audit and disclosure obligations. Not just AI hiring products from vendors. Any automated system that scores candidates. The vendor-audit market was not ready. Many employers were not either. The pain is that NYC AI laws are actively enforced, and the compliance overhead is real.
If you use an automated employment decision tool (AEDT) for an NYC position, you must (1) commission an independent bias audit annually, (2) publish a summary of the results on your website, (3) provide notice to candidates that AEDT will be used, and (4) allow candidates to request information about the process. Enforced by the NYC Department of Consumer and Worker Protection.
Governs how NYC agencies must disclose their use of automated decision systems. Affects vendors selling AI to NYC agencies, who must support their customers' disclosure obligations.
Click into each law below for detailed compliance guidance.
NYC is the template for municipal AI regulation. San Francisco, Boston, and other cities are watching. Employers doing business in NYC (which is most national employers) face active enforcement. Vendors selling AI to NYC agencies face disclosure obligations flowing through customer contracts. The NYC AI laws are not aspirational: they are producing real bias audits, real settlements, and real changes to hiring practices right now.
The academic literature on NYC AI laws is ahead of most corporate practice, and it is unusually blunt. Two findings are worth putting in front of any executive who thinks this is a compliance formality.
“Among these employers, 18 posted audit reports and 13 posted transparency notices.”
That is the gap between having AI and governing it. The second finding is the one that tends to change the room.
“bias audits produced in accordance with Local Law 144 are incomplete evaluations of algorithmic bias”
Neither of these is a fringe position. Both come from peer-reviewed work, and both describe the condition most organisations are actually in when the question about NYC AI laws arrives from the board, the buyer, or the regulator.
This is the sequence that works, and it is not the sequence most organisations choose. They start with the framework and work backwards toward reality. Start with reality.
Done in this order, NYC AI laws becomes tractable. Done out of order, it becomes a document nobody uses and a control nobody exercises.
Yes, if you use an AEDT to evaluate candidates for NYC positions.
The regulation defines AEDT narrowly: it must substantially assist or replace discretionary decision-making. But "substantially" is contested, and the safer posture is broad compliance rather than narrow interpretation.
The Bias Audit Working Reference from Volume III of The Operating Discipline for AI Library™ is designed to support Local Law 144 compliance. The HR addendum covers the notification and disclosure obligations.
The detail pages below each take one component of NYC AI laws and answer the same four questions: what it actually is, what it requires of you, why it matters commercially and legally, and what a defensible position looks like. Read the one that maps to your exposure first. The others become relevant as your AI footprint widens.
Executives ask, reasonably, where to start. The sequence that works is the same one every time, and it is not the sequence most organisations choose. Start with an inventory: you cannot govern AI you cannot list, and almost every organisation we assess is using more AI than its leadership believes. Then rank by consequence, not by volume, because the tool that makes one high-stakes decision a week carries more exposure than the one that drafts a thousand emails.
Only then assign an owner. Not a committee, an owner, named, with the authority to stop a deployment. Governance without a person who can say no is documentation, not control. With those three steps done, the specific requirements of NYC AI laws become tractable, because you now know what you have, what matters, and who answers for it.
The organisations that struggle are the ones that begin with the framework and work backwards toward reality. The frameworks are the map. The inventory is the territory. Start with the territory.
The authoritative texts and agency pages behind this summary. We keep this page current, but where a compliance decision turns on exact wording, read the source. Anything concerning NYC AI laws that carries legal consequence should be confirmed against the enrolled text or the issuing body, not against a secondary summary, including this one.
The AI Business Enablement Audit™ measures your organization against every framework in this library, including New York City AI Laws, and delivers a defensible governance dossier. Start or finish your audit below.
Start or finish your AI Audit →