Overview

This chapter compares New York’s Algorithmic Pricing Disclosure Act with the FTC’s proposed enforcement policy on personalized pricing. New York’s quoted rule requires a clear and conspicuous statement when specified conditions connect an algorithm, personal data, and a displayed price or offer to a New York consumer; the Act took effect November 10, 2025, according to the Attorney General’s alert. The FTC proposal, dated August 19, 2026, says the Commission cannot ban personalized pricing in all circumstances but may address deceptive or unfair practices and expects disclosure of the personalization, its basis, and data types where common pricing is reasonably expected. Neither approach makes disclosure permission or proves fairness.

Learning outcomes

New York’s quoted rule focuses on a clear, conspicuous disclosure when an algorithm uses personal data to set a displayed price or offer for a New York consumer.
The FTC’s August 19, 2026 proposal addresses deception and unfairness, not a blanket ban, and is not a binding rule.
A useful notice must reach consumers before choice and explain the relevant basis; disclosure alone does not prove fairness, accuracy, or legality.

Keywords

Personalized pricingDisclosureAlgorithmic pricingNew YorkFTCUnfairness

Why Disclosure Is the Middle Path

The policy problem created by personalized pricing is not just that prices may differ; it is that consumers may not know why they differ or what they can do about it. This chapter compares New York’s disclosure rule with the Federal Trade Commission’s proposed enforcement approach. The comparison shows what each framework makes visible, why neither is a universal ban, and why a disclosure can improve consumer choice without proving that the underlying price is fair or lawful.

What New York makes visible

New York’s Algorithmic Pricing Disclosure Act, as quoted in the New York Attorney General’s January 2026 letter, focuses on a particular connection between data and a displayed price. The letter says the Act defines “personalized algorithmic pricing” as dynamic pricing set by an algorithm that uses personal data. It defines dynamic pricing as pricing that fluctuates depending on conditions, and personal data as information that identifies or could reasonably be linked, directly or indirectly, to a specific consumer or device.

Those definitions do not make every changing price a personalized price. A price can fluctuate because supply and demand change, because a local market condition changes, or because a promotion is available to a defined group. The quoted New York rule becomes relevant when an entity sets the price of a specific good or service using personalized algorithmic pricing and directly or indirectly advertises, promotes, labels, publishes, or displays that price or offer to a consumer in New York using personal data specific to that consumer.

When the quoted conditions are met, the entity must include a clear and conspicuous disclosure stating: “THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA.” The requirement is deliberately direct. It does not ask the consumer to infer personalization from an unusual price, compare several accounts, or decode a general privacy policy. It names the fact that matters at the point where the price is being shown.

The New York Attorney General’s consumer alert says the Act took effect on November 10, 2025 and that businesses that do not comply can face a $1,000 penalty per violation. The January letter describes a different part of the enforcement picture, saying an entity that continues violating the Act after receiving a cease-and-desist letter may be subject to injunctive and monetary relief. These official summaries support the existence of a disclosure obligation and describe potential consequences, but they are not the full statutory text. They should not be used to infer unquoted exemptions or a complete remedies analysis.

The law’s practical significance is easiest to see in the Attorney General’s concern about Instacart. The letter said the platform provided a disclosure on a page reached by clicking fine-print text such as “View pricing policy,” “Higher than in-store prices,” or “Pricing & fees.” The notice referred to randomized tests, the use of personal information to calculate fees, and personalized incentives.

Published by DeepMox

FAQ

What does New York’s algorithmic pricing disclosure rule require?

When its quoted conditions are met, New York requires an entity to give a clear and conspicuous statement that an algorithm used the consumer’s personal data to set the displayed price or offer.

How does the FTC proposal differ from New York’s disclosure rule?

New York’s quoted approach uses a fixed warning about algorithmic use of personal data, while the FTC’s proposed approach asks for the personalization’s basis and data types and evaluates deception or unfairness; the proposal is not binding.

When can a pricing disclosure fail to inform consumers?

A disclosure can fail when it is hidden, separated from the price, displayed too late, or too vague to show whether the item price, discount, or fee was individualized.

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Personalized Pricing: New York Rule, FTC Proposal

Why Disclosure Is the Middle Path

What New York makes visible

FAQ