WHAT THIS BILL REGULATES · 1 REQUIREMENT TYPE
How Is This Bill Enforced
Verbatim statutory text on the left; plain-language analysis and a per-section checklist on the right. Numbered markers cross-link to the matching checklist row.
(1)(a) "Wage-fixing algorithmWage-fixing algorithm"Wage-fixing algorithm" means a mathematical or computational process or methodology implementing a set of rules, including without limitation data collected and used in conjunction with any such processes or methodologies, to be followed in calculations, data processing, data mining, machine learning, pattern recognition, automated decision-making or problem-solving operations, including those that transform inputs into outputs, utilized for the purpose of setting or recommending wages or compensation for an individual or a class or group to whom an individual belongs. "Wage-fixing algorithm" shall not include any such tool whose inputs are limited to job requirements, job performance, qualifications, labor market conditions, or the cost of living in an applicable metropolitan statistical area, micropolitan statistical area, combined statistical area, county or county equivalent. For the purposes of this section, "job performance" shall not include customer reviews.Labor Law § 194-c(1)(a)" means a mathematical or computational process or methodology implementing a set of rules, including without limitation data collected and used in conjunction with any such processes or methodologies, to be followed in calculations, data processing, data mining, machine learning, pattern recognition, automated decision-making or problem-solving operations, including those that transform inputs into outputs, utilized for the purpose of setting or recommending wages or compensation for an individual or a class or group to whom an individual belongs. "Wage-fixing algorithmWage-fixing algorithm"Wage-fixing algorithm" means a mathematical or computational process or methodology implementing a set of rules, including without limitation data collected and used in conjunction with any such processes or methodologies, to be followed in calculations, data processing, data mining, machine learning, pattern recognition, automated decision-making or problem-solving operations, including those that transform inputs into outputs, utilized for the purpose of setting or recommending wages or compensation for an individual or a class or group to whom an individual belongs. "Wage-fixing algorithm" shall not include any such tool whose inputs are limited to job requirements, job performance, qualifications, labor market conditions, or the cost of living in an applicable metropolitan statistical area, micropolitan statistical area, combined statistical area, county or county equivalent. For the purposes of this section, "job performance" shall not include customer reviews.Labor Law § 194-c(1)(a)" shall not include any such tool whose inputs are limited to job requirements, job performance, qualifications, labor market conditions, or the cost of living in an applicable metropolitan statistical area, micropolitan statistical area, combined statistical area, county or county equivalent. For the purposes of this section, "job performance" shall not include customer reviews.
(1)(b) "Personal dataPersonal data"Personal data" means any data that identifies, relates to, describes, is reasonably capable of being associated with, or could be reasonably linked, directly or indirectly, with a particular person or device, including but not limited to: (i) name or alias, signature, social security number, postal address, telephone number, passport number, driver's license or state identification card number, insurance policy number, email address, Internet Protocol address, account name, or other similar identifiers; (ii) bank account number, credit card number, debit card number, credit score or credit history, financial circumstances, or any other financial information, medical information, or health insurance information; (iii) records of personal property, products or services purchased, obtained, or considered, or other purchasing or consuming histories or tendencies; (iv) personal, political, professional, or religious affiliations, memberships, relationships, or activities, or status, activity, or relationships within a social media network, or any other associations with a group, band, class, or tier of individuals to which the individual belongs; (v) internet or other electronic network activity information, including browsing history, search history, and information regarding a person's interaction with an internet website application or advertisement; (vi) characteristics of protected classifications under state or federal law, geolocation identifiers, physical descriptions or characteristics, genetic information, or biometric information; and (vii) inferences drawn from any of the information identified in this paragraph to create a profile about a person, or a class or group to which such person belongs, reflecting such person's preferences, characteristics, psychological trends, predispositions, behavior, attitudes, intelligence, abilities, and aptitudes. "Personal data" shall not include location data that is used by a for-hire vehicle as defined in section 19-502 of the administrative code of the city of New York or as otherwise defined in local law or rule, or a transportation network company vehicle as defined in section sixteen hundred ninety-one of the vehicle and traffic law, solely to calculate the fare based on mileage and trip duration between the passenger's pickup and drop-off locations.Labor Law § 194-c(1)(b)" means any data that identifies, relates to, describes, is reasonably capable of being associated with, or could be reasonably linked, directly or indirectly, with a particular person or device, including but not limited to: (i) name or alias, signature, social security number, postal address, telephone number, passport number, driver's license or state identification card number, insurance policy number, email address, Internet Protocol address, account name, or other similar identifiers; (ii) bank account number, credit card number, debit card number, credit score or credit history, financial circumstances, or any other financial information, medical information, or health insurance information; (iii) records of personal property, products or services purchased, obtained, or considered, or other purchasing or consuming histories or tendencies; (iv) personal, political, professional, or religious affiliations, memberships, relationships, or activities, or status, activity, or relationships within a social media network, or any other associations with a group, band, class, or tier of individuals to which the individual belongs; (v) internet or other electronic network activity information, including browsing history, search history, and information regarding a person's interaction with an internet website application or advertisement; (vi) characteristics of protected classifications under state or federal law, geolocation identifiers, physical descriptions or characteristics, genetic information, or biometric information; and (vii) inferences drawn from any of the information identified in this paragraph to create a profile about a person, or a class or group to which such person belongs, reflecting such person's preferences, characteristics, psychological trends, predispositions, behavior, attitudes, intelligence, abilities, and aptitudes. "Personal dataPersonal data"Personal data" means any data that identifies, relates to, describes, is reasonably capable of being associated with, or could be reasonably linked, directly or indirectly, with a particular person or device, including but not limited to: (i) name or alias, signature, social security number, postal address, telephone number, passport number, driver's license or state identification card number, insurance policy number, email address, Internet Protocol address, account name, or other similar identifiers; (ii) bank account number, credit card number, debit card number, credit score or credit history, financial circumstances, or any other financial information, medical information, or health insurance information; (iii) records of personal property, products or services purchased, obtained, or considered, or other purchasing or consuming histories or tendencies; (iv) personal, political, professional, or religious affiliations, memberships, relationships, or activities, or status, activity, or relationships within a social media network, or any other associations with a group, band, class, or tier of individuals to which the individual belongs; (v) internet or other electronic network activity information, including browsing history, search history, and information regarding a person's interaction with an internet website application or advertisement; (vi) characteristics of protected classifications under state or federal law, geolocation identifiers, physical descriptions or characteristics, genetic information, or biometric information; and (vii) inferences drawn from any of the information identified in this paragraph to create a profile about a person, or a class or group to which such person belongs, reflecting such person's preferences, characteristics, psychological trends, predispositions, behavior, attitudes, intelligence, abilities, and aptitudes. "Personal data" shall not include location data that is used by a for-hire vehicle as defined in section 19-502 of the administrative code of the city of New York or as otherwise defined in local law or rule, or a transportation network company vehicle as defined in section sixteen hundred ninety-one of the vehicle and traffic law, solely to calculate the fare based on mileage and trip duration between the passenger's pickup and drop-off locations.Labor Law § 194-c(1)(b)" shall not include location data that is used by a for-hire vehicle as defined in section 19-502 of the administrative code of the city of New York or as otherwise defined in local law or rule, or a transportation network company vehicle as defined in section sixteen hundred ninety-one of the vehicle and traffic law, solely to calculate the fare based on mileage and trip duration between the passenger's pickup and drop-off locations.
(1)(c) "Behavioral dataBehavioral data"Behavioral data" means an individual's observable or measurable actions, habits, preferences, interests, or vulnerabilities, including without limitation audio, visual, olfactory, thermal, and other sensory data, and inferences drawn from any such information to create a profile about a person, or a class or group to which such person belongs, reflecting such person's preferences, characteristics, psychological trends, predispositions, behavior, attitudes, intelligence, abilities, and aptitudes.Labor Law § 194-c(1)(c)" means an individual's observable or measurable actions, habits, preferences, interests, or vulnerabilities, including without limitation audio, visual, olfactory, thermal, and other sensory data, and inferences drawn from any such information to create a profile about a person, or a class or group to which such person belongs, reflecting such person's preferences, characteristics, psychological trends, predispositions, behavior, attitudes, intelligence, abilities, and aptitudes.
This subdivision establishes the three key defined terms for the bill: wage-fixing algorithm, personal data, and behavioral data. The wage-fixing algorithm definition is deliberately broad, encompassing any computational process — including machine learning, data mining, and automated decision-making — used to set or recommend wages. A significant safe harbor excludes tools whose inputs are limited to traditional compensation benchmarking factors such as job requirements, qualifications, labor market conditions, and cost of living. Notably, customer reviews are excluded from the definition of permissible job performance inputs, which directly affects gig economy and platform-based compensation models.
Personal data is defined expansively to include not only traditional identifiers but also financial data, purchasing histories, internet activity, protected-class characteristics, biometric information, and inferences drawn from any of these. A narrow carve-out preserves location-based fare calculations for for-hire and transportation network company vehicles. Behavioral data separately captures observable actions, habits, vulnerabilities, and sensory data, along with profiling inferences.
(2) 1 No employer shall utilize a wage-fixing algorithmWage-fixing algorithm"Wage-fixing algorithm" means a mathematical or computational process or methodology implementing a set of rules, including without limitation data collected and used in conjunction with any such processes or methodologies, to be followed in calculations, data processing, data mining, machine learning, pattern recognition, automated decision-making or problem-solving operations, including those that transform inputs into outputs, utilized for the purpose of setting or recommending wages or compensation for an individual or a class or group to whom an individual belongs. "Wage-fixing algorithm" shall not include any such tool whose inputs are limited to job requirements, job performance, qualifications, labor market conditions, or the cost of living in an applicable metropolitan statistical area, micropolitan statistical area, combined statistical area, county or county equivalent. For the purposes of this section, "job performance" shall not include customer reviews.Labor Law § 194-c(1)(a), or the output of a wage-fixing algorithmWage-fixing algorithm"Wage-fixing algorithm" means a mathematical or computational process or methodology implementing a set of rules, including without limitation data collected and used in conjunction with any such processes or methodologies, to be followed in calculations, data processing, data mining, machine learning, pattern recognition, automated decision-making or problem-solving operations, including those that transform inputs into outputs, utilized for the purpose of setting or recommending wages or compensation for an individual or a class or group to whom an individual belongs. "Wage-fixing algorithm" shall not include any such tool whose inputs are limited to job requirements, job performance, qualifications, labor market conditions, or the cost of living in an applicable metropolitan statistical area, micropolitan statistical area, combined statistical area, county or county equivalent. For the purposes of this section, "job performance" shall not include customer reviews.Labor Law § 194-c(1)(a), in combination with personal or behavioral dataBehavioral data"Behavioral data" means an individual's observable or measurable actions, habits, preferences, interests, or vulnerabilities, including without limitation audio, visual, olfactory, thermal, and other sensory data, and inferences drawn from any such information to create a profile about a person, or a class or group to which such person belongs, reflecting such person's preferences, characteristics, psychological trends, predispositions, behavior, attitudes, intelligence, abilities, and aptitudes.Labor Law § 194-c(1)(c), whether collected or processed by the employer or a third-party, to set or recommend wages or compensation.
This is the bill's core operative provision. It categorically prohibits employers from using a wage-fixing algorithm, or the output of such an algorithm, in combination with personal or behavioral data to set or recommend wages or compensation. The prohibition covers both direct employer use and employer reliance on third-party-processed data or algorithm outputs. Importantly, the prohibition is not limited to algorithms the employer itself operates — it extends to using the output of a third-party wage-fixing algorithm when combined with personal or behavioral data.
(3) The commissioner may promulgate such rules and regulations as the commissioner deems necessary and proper to effectuate the purposes and provisions of this section.
This subdivision grants the Commissioner of Labor discretionary authority to promulgate rules and regulations to effectuate the bill's purposes and provisions. This is a standard enabling clause that creates no independent compliance obligation on employers but signals that the Commissioner may issue interpretive guidance or detailed compliance rules in the future.
(4)(a) The attorney general may enforce the provisions of this section by civil action in any court of competent jurisdiction. Such action may seek to enjoin violations of this section and recover for each violation, and on behalf of any harmed worker: (i) actual damages or three thousand dollars, whichever is larger; (ii) treble damages, where such violation was willful or egregious; (iii) disgorgement of profits obtained directly or indirectly as a result of any violation of this section; (iv) attorneys' fees and costs; and (v) any other legal or equitable relief the court may deem just and proper.
(4)(b) The commissioner may enforce the provisions of this section in accordance with section two hundred eighteen of this chapter.
(4)(c) An individual or group of individuals who have been harmed by a violation of this section may bring in any court of competent jurisdiction a civil action to enjoin violations of this section and recover for each violation: (i) actual damages or three thousand dollars, whichever is larger; (ii) treble damages, where such violation was willful or egregious; (iii) attorneys' fees and costs; and (iv) any other legal or equitable relief the court may deem just and proper.
(4)(d) 2 An individual alleging a violation of this section shall be protected from retaliation pursuant to section two hundred fifteen of this chapter and any other applicable law.
(4)(e) In an action alleging a violation of this section, the burden shall rest with the employer to demonstrate, by a preponderance of the evidence, that a difference in wages or compensation was due only to lawful factors.
This subdivision establishes a comprehensive enforcement framework with three distinct tracks. The Attorney General may bring civil actions seeking injunctive relief, actual damages or $3,000 per violation (whichever is larger), treble damages for willful or egregious violations, disgorgement of profits, attorney's fees and costs, and any other equitable relief. The Commissioner of Labor may enforce under the existing Labor Law § 218 framework. Individuals or groups of individuals who have been harmed may bring private civil actions with similar remedies, except that disgorgement is available only in AG actions.
The subdivision also incorporates anti-retaliation protections under existing Labor Law § 215 and shifts the burden of proof: in any enforcement action, the employer must demonstrate by a preponderance of the evidence that a wage differential was due only to lawful factors.
This act shall take effect on the thirtieth day after it shall have become a law.
The act takes effect on the thirtieth day after it becomes law. No specific calendar date is established, as the bill has not yet been enacted.