Key takeaways
- The New York Legislature has passed the One Fair Price Act, which would prohibit businesses from using algorithms and consumers' personal data to offer different prices to different customers for the same goods or services, a practice the act terms "surveillance pricing." The bill awaits delivery to Governor Kathy Hochul.
- The act would replace the disclosure regime created by New York’s Algorithmic Pricing Disclosure Act with an outright prohibition, extending liability to service providers and to data practices that facilitate surveillance pricing.
- Loyalty programs, class-based discounts for groups such as veterans and seniors, and other “bona fide” discounts would remain permitted, subject to new uniformity and disclosure conditions.
- The New York Attorney General would enforce the act, with civil penalties of up to $5,000 for a first violation and $20,000 for each subsequent violation, but the act would not create a private right of action.
The New York Legislature recently passed the One Fair Price Act. The bill would amend last year’s Algorithmic Pricing Disclosure Act to prohibit surveillance pricing rather than merely require its disclosure. If signed by Governor Hochul, the act would take effect 180 days after becoming law.
We covered the Algorithmic Pricing Disclosure Act in a prior Legal Development. That law requires a prescribed disclosure when a price shown to a New York consumer is set by an algorithm using the consumer’s personal data. The One Fair Price Act, championed by Attorney General Letitia James, would move New York from transparency to prohibition.
Overview of the One Fair Price Act
The act would define “surveillance pricing” as “pricing set completely or in part by an algorithm that uses personal data to offer different prices to different customers for the same goods or services,” excluding bona fide custom discounts. “Personal data” would continue to mean any data that identifies or could reasonably be linked, directly or indirectly, with a specific consumer or device, with a reworked carve-out for location data this is “affirmatively and knowingly provided or shared by a consumer and used: (i) for the purpose of calculating trip duration and mileage costs associated with location-based service, such as transportation, delivery, and courier logistics; or (ii) to assess local supply and demand conditions.”
These prohibitions would reach any “entity” domiciled or doing business in New York and, notably, any “service provider” acting on its behalf. Specifically, the act includes the following prohibitions and restrictions:
- Ban on surveillance pricing: No entity or service provider could use surveillance pricing, directly or indirectly, to set or adjust the “reference price” or “consumer price” of a good or service offered to a consumer.
- Ban on advertising surveillance pricing: No entity or service provider could advertise, promote, label, or publish a statement, display, image, offer, or announcement using surveillance pricing to a consumer.
- Restrictions on data practices: No entity or service provider could “collect, use, sell, retain, share for valuable consideration, or disclose personal data for the purpose of facilitating surveillance pricing to a consumer.”
- Uniformity requirement for custom discounts: Bona fide custom discounts could be offered only uniformly, to any consumer who meets the disclosed eligibility conditions or criteria.
The definition of “consumer” would expand to cover purchases “in New York state or from an entity domiciled in New York state.” The New York Attorney General might take the position that this language reaches transactions with New York-domiciled businesses wherever the consumer is located.
Preserved discounts and pricing strategies
The act would not ban discounting. It would preserve “bona fide discounts,” which are defined as genuine reductions from a “reference price” that are generally available without the use of personal data. Examples of bona fide discounts include posted promotional periods, end-of-season and flash sales, inventory-based pricing, price matching, rebates, and bulk or subscription discounts.
The act would also permit “bona fide custom discounts,” which may use limited categories of personal data under specified conditions. These include:
- Loyalty and rewards programs: Discounts offered to all members of a loyalty or rewards program a consumer affirmatively and knowingly joins. Such programs may include tiered discounts based on prior purchase history, provided the tiers are clearly and conspicuously disclosed.
- Class-based discounts: Discounts based on a consumer’s voluntary self-identification with a broadly defined class (such as military veterans, seniors, teachers, or employees) or on a birthday or membership anniversary.
- Purchase-history discounts: Discounts based solely on a consumer’s prior purchase history with the specific entity, provided that history is not paired or combined with other personal data and its use is clearly and conspicuously disclosed.
- Online marketplace discounts: Separate conditions would govern operators of “online marketplaces,” including a pathway for one-time new-customer discounts offered on behalf of third-party sellers.
The act also would not prohibit dynamic pricing. “Dynamic pricing” refers to pricing that fluctuates automatically based on one or more algorithms, and algorithmic pricing that responds to nonpersonal conditions such as supply, inventory levels, or time of day would remain permitted. The prohibition on surveillance pricing would apply only where an algorithm uses personal data to offer different prices to different customers for the same goods or services.
By contrast, the act would eliminate the existing exception for personalized subscription retention offers under New York’s prior Algorithmic Pricing Disclosure Act. This would mean that a retention offer personalized using a subscriber’s personal data could constitute prohibited surveillance pricing unless it qualifies as a bona fide discount or bona fide custom discount.
Exceptions and limitations
The act also includes several exceptions. Entities subject to the New York Insurance Law and regulations promulgated thereunder would remain excluded, but the current law’s categorical exemptions for certain financial institutions would narrow to an exception for using personal data to price or extend credit based on an evaluation of creditworthiness, including determinations based on consumer report data under the federal Fair Credit Reporting Act. Pricing required or expressly authorized by federal or state law would be excluded, and a service provider would not be liable for a covered entity’s prohibited conduct unless the service provider shows “reckless disregard” of that conduct.
Enforcement
The New York Attorney General would have authority to enforce the act and could seek an injunction on five days’ notice. The Attorney General could seek restitution and damages to aggrieved parties and civil penalties of up to $5,000 for a first violation and $20,000 for each subsequent violation. This is a substantial increase from the $1,000-per-violation cap under current law. Recovered penalties would accrue to the state and be used exclusively by the Attorney General for consumer protection enforcement.
Under current law, the Attorney General must issue a cease-and-desist letter and allow an opportunity to cure before bringing an action; the act would eliminate that requirement. And although an earlier version of the bill included a private right of action with statutory damages, the version that passed does not create one. The act would leave intact the current law’s provision that the section does not “limit any other criminal or civil liability,” which continues to leave open the possibility of causes of action under other consumer protection laws. The act would also authorize the Attorney General to adopt implementing regulations.
Looking ahead
The bill has yet to be delivered to Governor Hochul, and amendments negotiated as a condition of signature remain possible. In the meantime, businesses that price goods or services for New York consumers, along with vendors that provide pricing technology to them, should begin reviewing their pricing practices. That review should cover whether pricing models use personal data in ways that could fall within the act’s definition of surveillance pricing; the data flows that feed pricing algorithms; and whether loyalty, membership, and discount programs satisfy the act’s uniformity and disclosure conditions.
