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NRF files lawsuit to stop New York’s algorithmic pricing disclosure law

The Act mandates that retailers place a notice next to any price determined using customer information, stating: “This price was set by an algorithm using your personal data.”

Photo by Wesley Tingey / Unsplash

WASHINGTON — The National Retail Federation (NRF) has filed a federal lawsuit aiming to halt enforcement of a controversial New York state law that would require retailers to disclose when prices are set using algorithms and customer data.

Set to take effect July 8, the New York Algorithmic Pricing Disclosure Act mandates that retailers place a notice next to any price determined using customer information, stating: “This price was set by an algorithm using your personal data.” The law was passed in May as part of the state’s annual budget legislation and signed by Governor Kathy Hochul with little public debate.

In a lawsuit filed today in U.S. District Court in Manhattan, the NRF argued that the measure is both unconstitutional and harmful to consumers, claiming it would stigmatize technology that enables discounts, personalization, and increased value. The lawsuit seeks both preliminary and permanent injunctions against the enforcement of the law.

“This law interferes with retailers’ ability to provide their customers with the highest value and best shopping experience they can,” NRF Chief Administrative Officer and General Counsel Stephanie Martz said. “Algorithms are created by humans, not computers, and they are an extension of what retailers have done for decades, if not centuries, to use what they know about their customers to serve them better. It’s just done at the scale of the modern economy. Stigmatizing tools that drive prices down turns offering deals into a liability, and consumers will end up paying more.”

According to the NRF, algorithmic pricing relies on information such as purchase history, location, or online behavior—not sensitive personal data—to tailor promotions or discounts. The group said requiring retailers to issue what it called a “misleading and ominous” disclosure amounts to compelled speech and violates the First and 14th Amendments.

“This act compels NRF’s members to impugn their pro-consumer practices against their will,” NRF said in a lawsuit filed today in U.S. District Court in Manhattan. The suit argues that the law, which is “replete with arbitrary exemptions,” violates both the First and 14th Amendments and asked for both preliminary and permanent injunctions blocking its enforcement.

The complaint also highlights what NRF described as “arbitrary exemptions” in the law and argues that it lacks evidence to support the claim that algorithmic pricing harms consumers. “Although the state is free to express its opinion that algorithmic pricing is dangerous, it cannot force businesses that disagree to do so,” the lawsuit stated.

“Retailers use algorithmic pricing to help customers save money” by using their purchase history, items in their online shopping cart, zip code and other information customers voluntarily share rather than any personal sensitive data, the complaint said. “Despite this, the State of New York will soon require many retailers to affix a misleading and ominous warning to any price set by an algorithm using any information that could be linked to a customer. … Although the state is free to express its opinion that algorithmic pricing is dangerous, it cannot force businesses that disagree to do so.”

The lawsuit said the law “is unsupported by any facts” that algorithmic pricing is inherently harmful and based instead on “speculative fear.” Any discrimination or price gouging that might inadvertently occur is already prohibited by other state laws, the suit said.

“Algorithmic pricing mechanisms lower overall consumers prices in the aggregate,” the suit said. “Studies have consistently shown that algorithmic pricing incorporating data on market conditions plays a powerful role in driving prices down because algorithms allow companies to be more responsive to supply and demand and so better optimize pricing to reflect market conditions.”

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