States are racing to rein in the growing use of artificial intelligence and computer algorithms to set prices, with New York leading the charge. On Dec. 15, a major amendment to New York’s antitrust law took effect, banning the use of certain algorithmic rent-setting tools for residential units under Section 340-b of the state’s General Business Law.
This follows New York’s November implementation of a first-in-the-nation disclosure law, Section 349-a of the General Business Law, that requires merchants to tell consumers when individualized prices are set using algorithms trained on personal data. State lawmakers are also considering S.B. 7033, which would outlaw algorithmic price discrimination based on protected characteristics like race and age.
These measures arrive amid a torrent of litigation challenging the use of algorithmic pricing software in contexts ranging from apartment rents to healthcare reimbursements, and as more companies adopt pricing systems that tailor offers to individual consumers.[1]
By pushing these laws, New York and other states seek to fill perceived gaps in the Sherman Antitrust Act and Robinson-Patman Act, the primary federal antitrust statutes prohibiting price-fixing and price discrimination.
Industry pushback has been swift: Multiple lawsuits are challenging the New York laws on constitutional and other grounds. The outcomes could determine not only the future of these statutes but the viability of similar regulations nationwide.
For businesses, this means both immediate new compliance burdens and continued uncertainty over how and whether these rules will ultimately be enforced.
The Algorithmic Rent-Setting Ban: Section 340-b
Section 340-b, enacted in October and effective Dec. 15, is the first state law barring the use of algorithms to set rents.[2]
The statute deems it an unlawful agreement in violation of New York’s Donnelly Act “for a residential rental property owner or manager to knowingly or with reckless disregard set or adjust rental prices, lease renewal terms, occupancy levels, or other lease terms and conditions” based on recommendations from algorithmic pricing software that performs a “coordinating function.”[3]
Notably, the law represents a potential expansion of liability beyond the federal Sherman Act, which requires proof of a horizontal agreement between competitors or potential competitors for a per se violation of the law. In contrast, the New York law deems the unilateral use of algorithmic pricing software to set or adjust rents and lease terms to constitute an unlawful agreement, even without a meeting of the minds between the landlords, provided the software performs a coordinating function.[4]
Further, the statute bars setting or adjusting rates using an algorithm, meaning a landlord could potentially violate the statute even if it does not reflexively adopt the recommended rent.[5] For example, landlords might arguably violate the statute by using algorithmic output as a default benchmark then adjusting the benchmark up or down to determine the actual rent.
This possibility represents a departure from some prior federal algorithmic pricing decisions, which dismissed complaints in part because the alleged conduct demonstrated that the defendants sometimes deviated from the algorithm-recommended price.[6]
Section 340-b is limited to algorithmic pricing software that performs a coordinating function. But the term “coordinating function” is defined broadly to include collecting past and present data on price and other factors from two or more competing property owners or managers, processing that data, and recommending rental prices or lease terms.[7]
The definition does not distinguish between algorithms that use confidential information or publicly available information. This too represents a meaningful departure from federal cases, which have generally treated algorithmic pricing based on public information as less problematic.[8]
Additionally, the statute does not require landlords to know they are using an offending pricing software. Instead, it is enough that they act with “reckless disregard.”[9] It is thus prudent for landlords to understand the mechanics of their software, as a lack of knowledge will not be a viable defense.
Landlords should also consider that software may fall within the covered definition even if coordinating rent prices is not its primary function. For example, one of the law’s sponsors indicated that the law could possibly apply to situations where “mom-and-pop style landlords” use ChatGPT or other AI tools to analyze data available on the internet to help them set rents.[10] While it is unclear whether courts would enforce the law in such a circumstance, landlords of any size should be aware of the potential risk.
In addition to prohibiting the use of certain software, the law makes it illegal for any person or entity to facilitate an agreement to not compete between residential rental properties, “including by operating or licensing” algorithmic pricing software that performs a coordinating function.[11] This provision plainly targets companies that make pricing software, but it may sweep in other actors who could be deemed to have facilitated an agreement.
It is unclear whether the statute requires proof of a predicate agreement to not compete for facilitator liability to attach, or if merely operating or licensing the offending software is enough. Given that the statute treats the use of such software to set rents as an unlawful agreement, a cautious approach is to assume that operating or licensing software used in that manner is sufficient to trigger the statute.
As to the new law’s geographic and temporal scope, Section 340-b adds a new provision to New York’s existing antitrust statute, the Donnelly Act. By its terms, the Donnelly Act applies to restraints on “business, trade or commerce or in the furnishing of any service in this state,” meaning there must be a nexus between the alleged conspiracy and injury to competition in New York.[12] The new law further specifies that the property owners and managers subject to the ban are individuals and entities that own or manage residential rental units in New York state.[13]
Although the law does not indicate whether it applies retroactively or prospectively, New York courts generally hold that “amendments are presumed to have prospective application unless the Legislature’s preference for retroactivity is explicitly stated or clearly indicated” or the amendment is remedial in nature.[14]
Violations of the new law may result in civil penalties of up to $1 million, as well as potential criminal prosecution.[15] The Donnelly Act authorizes suits by the government and provides a private right of action, meaning this new section could create a basis for private plaintiffs to sue.[16] Parties suing under Section 340-b may be entitled to treble damages and attorney fees.
A Developing Challenge to Section 340-b
RealPage Inc., a company that provides pricing software to rental properties and recently entered a consent decree resolving a federal antitrust investigation, sued New York’s attorney general on Nov. 26 to block enforcement of Section 340-b.[17]
In its complaint, RealPage argues the statute violates the First Amendment by restricting lawful advice and analysis, imposing severe penalties, and discriminating based on viewpoint. The company seeks declaratory and injunctive relief, claiming the law is overbroad, unsupported by evidence and a threat to routine data-driven tools.
While RealPage’s preliminary injunction motion is still pending, the action’s outcome will have a large impact on the viability of Section 340-b and potentially other algorithmic rent-setting bans elsewhere.
Regulating Personalized Algorithmic Pricing: Section 349-a and S.B. 7033
In addition to legislative efforts aimed at restricting the use of algorithmic tools in rent-setting, New York has enacted and is considering further measures to regulate algorithms that leverage consumers’ personal data for individualized pricing. These legislative developments stem from heightened scrutiny of personalized pricing practices that have emerged in response to the proliferation of data-driven systems, particularly in industries like e-commerce, where algorithms dynamically adjust prices in real time based on consumer profiles and behavioral data.
Notably, New York’s Algorithmic Pricing Disclosure Act, codified at Section 349-a of the General Business Law, went into effect in November. The statute requires merchants to disclose when a published price has been set by an algorithm using a consumer’s personal data.[18]
The law recently survived a challenge brought by the National Retail Federation alleging that the disclosure requirement violates the First Amendment’s prohibition on compelled speech, though that ruling is under appeal.[19]
A second bill, New York S.B. 7033, the Preventing Algorithmic Pricing Discrimination Act, is currently under committee review. If enacted, this bill would prohibit the use of protected class data to set prices for goods or services that differ from those offered to other consumers. Protected class data encompasses information identifying legally protected characteristics, such as ethnicity, nationality, age, disability, sex or sexual orientation.
Unlike the Robinson-Patman Act, S.B. 7033 would regulate price discrimination in direct-to-consumer transactions and apply to both goods and services, thereby expanding protections to areas previously outside the reach of federal law.
Takeaways for Businesses
New York Property Owners and Managers
Property owners and managers within the state should:
- 重新评估使用算法定价软件或系统来设定租金、入住率及其他租赁条款的做法；
- 理解软件的运作机制。识别其数据来源、处理方法及输出结果，以确定该软件是否在第340-b条下履行协调职能；
- 对租赁和管理团队进行培训，明确第三方定价工具的允许用途与禁止用途。
向纽约房产所有者提供算法软件的公司
向房产出租方提供算法软件的供应商应：
- 审核产品以确认其无法合理地被归类为履行第340-b条规定的协调职能；
- 审查审计结果并确认合规性，尤其在边界案例中；
- 详细记录调查结果，包括数据来源、模型版本及合规审计结果，以防范潜在的协调人责任；
- 实施合规功能，以阻止或标记可能涉及第340-b条的客户使用行为，并提供清晰的指导和培训材料，帮助客户避免无意中违反规定。
纽约州采用算法定价策略的企业
本州采用算法定价的公司应：
- 审查定价算法以确定其是否符合第349-a条的规定；
- 当公布的价格是由使用个人数据的算法设定时，应向消费者明确说明；
- 关注纽约州参议院第7033号法案的进展，该法案可能禁止基于受保护群体数据的算法价格歧视。
纽约州外企业
州外公司应：
- 追踪相关司法管辖区内涉及算法定价的立法进展和执法行动，因为其他州（如加利福尼亚州）已颁布或正在考虑类似法规。
富乐律师事务所律师理查德·李与萨凡纳·米拉克尔，以及法学院毕业生汉娜·阿尔伯里共同撰写了本文。本文最初发表于 Law360 ，经授权转载。
[1] 参见例如：RealPage公司租赁软件反垄断诉讼案 (No. II)案， 709 F. Supp. 3d 478 (M.D. Tenn. 2023)；参见MultiPlan健康保险供应商诉讼案，7 89 F. Supp. 3d 614 (N.D. Ill. 2025)。
[2] 多个城市和地区已颁布算法定价禁令，包括：旧金山、伯克利、圣莫尼卡和圣地亚哥（加利福尼亚州）；泽西市和霍博肯（新泽西州）；西雅图和金县（华盛顿州）；费城；明尼阿波利斯；以及普罗维登斯。
[3] 《纽约州一般商业法》第340-b(3)条。
[4] 同上。
[5] 同上。
[6] 参见例如：Gibson v. MGM Resorts Int’l案，案号 2:23-CV-00140-MMD-DJA，2023 WL 7025996，第*3页（内华达州地方法院，2023年10月24日）（认定未指控酒店经营者必须采用建议价格构成"诉状的致命缺陷"）。[email protected] 2023年10月24日) (认定未主张酒店经营者必须采用建议价格构成"诉状中的致命缺陷")。
[7] 《纽约州一般商业法》§ 340-b(1)(c)。
[8] 参见，例如，Dai v. SAS Inst. Inc.案， 案号24-CV-02537-JSW，2025 WL 2078835，第*5页（加州北区法院2025年7月18日）（因"事实不足以使法院合理推断存在机密信息交换"而驳回）； Gibson v. Cendyn Grp. LLC案，148 F.4th 1069, 1083, n.8 (9th Cir. 2025)（原告未指控软件供应商"向各被许可方共享竞争酒店的机密信息"，故维持驳回判决）。
[9] 《纽约州一般商业法》第340-b(3)条。
[10] 2025年6月10日会议：关于AO1417号法案的听证会，纽约州议会记录161-63页（2025年）。
[11] 《纽约州一般商业法》第340-b(2)条。
[12] 参见同上 § 340(1)；《环球再保险公司美国分支机构诉Equitas有限公司案》， 969 N.E.2d 187, 196 (纽约州 2012)。
[13] 《纽约州一般商业法》§ 340-b(1)(d)。
[14]格利森案（迈克尔·维有限公司）， 749 N.E.2d 724, 726 (N.Y. 2001)。
[15] 《纽约州一般商业法》第341条、第342-a条。
[16] 同上，第340(5)条。
[17] 诉状第1页，RealPage公司诉詹姆斯案，案号25-cv-9847（纽约南区联邦地区法院2025年）。
[18] 参见《纽约州一般商业法》§ 349-a(2)。
[19] 参见全国零售联合会诉詹姆斯案， 案号25-CV-5500 (JSR)，2025 WL 2848212 (纽约南区联邦地区法院2025年10月8日)。
