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Bill

A 11599

Prohibits anticompetitive and deceptive algorithmic pricing practices

2025 Regular Session

New York’s fair cart act prohibits deceptive personalized pricing and requires clear disclosure when prices are tailored by data, while preserving legitimate dynamic pricing.

REFERRED TO CONSUMER AFFAIRS AND PROTECTION
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Bill Summary · A 11599

Summary of Bill A11599 (New York, 2025-2026)

Purpose and intent

  • Enacts the "fair cart act" to establish safeguards against deceptive and anticompetitive algorithmic pricing practices while preserving lawful pricing tools and innovation.
  • Acknowledges potential benefits of AI, dynamic pricing, and electronic shelf labeling, but aims to prevent undisclosed or unfair price discrimination based on personal data or inferred characteristics.
  • Seeks to balance consumer protection with allowed pricing mechanisms that lower prices or improve efficiency.

Key provisions and changes

Section 350-o – Definitions

  • Establishes terms used in the act, including:
    • Algorithmic pricing system: any automated or data-driven system that sets or influences prices.
    • Baseline public price: standard price for a substantially similar good/service absent individualized adjustments.
    • Covered entity: any retailer, online marketplace, grocery/food delivery, ride-hailing, ticket seller, lodging, e-commerce platform, or similar provider operating in NY.
    • Deceptive algorithmic price inflation: using personal data, geolocation, profiling, or inferred economic status to raise a price above baseline without clear disclosure.
    • Dynamic pricing: price changes based on supply/demand, inventory, costs, etc.
    • Personal data, personalized discount, price transparency, and other related terms.

Section 350-p – Prohibited practices

  • Prohibits covered entities from:
    • Deceptively increasing prices above baseline based on personal data or inferred characteristics without clear disclosure.
    • Engaging in unfair or deceptive individualized price inflation that harms consumers.
    • Misrepresenting the basis for price determination, adjustments, or display.
    • Falsely representing a personalized price as universally available when different prices are offered to similarly situated consumers.
  • Note: Dynamic pricing remains allowed if not deceptive or unfair under the act.

Section 350-q – Permitted pricing practices and safe harbors

  • Enumerates pricing practices not restricted by the act, including:
    • Loyalty programs, coupons, rebates, promotional/priced discounts, introductory/retention/subscription discounts, geographic promotions, and store-specific sales.
    • Personalized offers or discounts that lower price.
    • Electronic shelf labeling, dynamic pricing based on legitimate business factors.
    • Seller/vendor-funded discounts; app- or platform-based pricing; anniversary/birthday promotions; registry-linked savings.
    • Algorithmic systems for inventory management, waste reduction, or efficiency.
    • Pricing systems using purchase history or behavioral data solely to provide discounts or consumer benefits.
  • Prohibits disclosure of proprietary algorithms or confidential business information as a condition of compliance.

Section 350-r – Consumer pricing transparency

  • Requires clear and conspicuous disclosures when:
    • Prices are materially personalized.
    • Personal data materially influences price determination.
    • Individualized profiling materially affects final price.
  • Disclosures must be reasonably designed to inform consumers before purchase.
  • Mandates providing clear pricing information, including all mandatory fees, prior to transaction completion.

Section 350-s – Compliance guidance and enforcement

  • The Division of Consumer Protection and the Attorney General have enforcement authority.
  • Before civil action, the enforcing agency must provide written notice and allow 30 days to cure (where appropriate).
  • Civil penalties: up to $10,000 per violation for knowing violations.
  • Penalty factors include intent, corrective efforts, consumer harm, and good faith reliance on guidance.
  • Agencies may issue guidance, opinions, and best practices.

Section 350-t – Educational outreach

  • The Division must develop consumer education materials about rights related to algorithmic pricing and pricing transparency.
  • May convene stakeholders (industry, consumer groups, tech experts, academia) to develop voluntary best practices for fairness, innovation, and transparency.

Effective date

  • The act takes effect 180 days after becoming law.

Who/what is affected

  • Covered entities operating in New York that use algorithmic pricing systems for goods or services, including retailers, online marketplaces, grocery/food/transport platforms, ticketing, lodging, and related platforms.
  • Consumers in New York who purchase goods/services from these entities will be impacted by enhanced transparency requirements and protections against deceptive pricing practices.

Procedural/timeline notes

  • Referred to the Committee on Consumer Affairs and Protection as of June 5, 2026.
  • Full text indicates a standard enforceable framework with a cure period and civil penalties, plus a future guidance and education program.

If you’d like, I can tailor this summary for a stakeholder audience (e.g., businesses vs. consumer advocates) or compare it to current NY law on pricing/transparency.

Compiled from official sources — confirm details with the bill’s official record.

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