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Bill

S 8623

Prohibits the use of surveillance pricing

2025 Regular Session Introduced by Samra Brouk and 6 co-sponsors

Prohibits personalized algorithmic pricing using personal data and requires clear disclosures for automated pricing, with strong enforcement and consumer remedies.

SUBSTITUTED BY A9349B
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WeVote Research Nonpartisan
Bill Summary · S 8623

Summary of Bill S.8623 (2025-2026) — New York

Overview

  • Purpose: Prohibit the use of personalized, algorithmic pricing and require disclosure of automated pricing systems in New York.
  • Status: Introduced in Senate and referred to Rules (initial steps completed; related committee actions noted). Co-sponsored by Sen. Rachel May and Sen. Mike Gianaris.
  • Effective date: 180 days after enactment. Immediate authority to implement rules for the act is allowed.

Core Definitions (Section 349-a)

  • Algorithm: A computational automated process using a set of rules.
  • Clear and conspicuous disclosure: Information presented in the same medium as the price, near the price, easily visible and understandable.
  • Consumer: Natural person buying or seeking to purchase for personal use.
  • Personal data: Data that identifies or could be linked to a specific consumer or device (with specified exclusions for certain transportation-related data).
  • Dynamic pricing: Prices that fluctuate based on conditions.
  • Personalized algorithmic pricing: Dynamic pricing that uses personal data.
  • Automated pricing system: System using software and algorithms to adjust prices based on factors other than personal data.
  • Entity: Any business or organization operating in New York.

Provisions and Prohibited Practices (Section 349-a, §2)

  • Prohibition on personalized algorithmic pricing:
    • Entities may not set a price for a specific good/service using personalized algorithmic pricing.
    • If an entity advertises or uses personalized pricing to a New York consumer, the entity must include a clear, conspicuous disclosure stating: "THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA."
    • Prohibits collecting, using, retaining, or disclosing personal data for surveillance pricing.
  • Disclosure for automated pricing systems:
    • Entities using automated pricing systems must clearly disclose the use of such a system and the categories of non-personal inputs that influence pricing.

Exceptions (Section 349-a, §3)

The bill provides several carve-outs, including:
- Insurance-related activities under relevant laws.
- Financial institutions or affiliates under applicable federal law.
- Certain prices under federal/state law and regulatory frameworks.
- Subscription-based pricing where the price is less than the subscription rate.
- Uniform discounts or promotional pricing offered to all consumers.
- Time-limited or inventory-based pricing that does not rely on personal data (e.g., seasonal sales, end-of-season sales, early-bird/flash sales, inventory adjustments).
- Loyalty programs meeting specific criteria:
- Participation voluntary.
- Uniform pricing benefits for all members.
- Benefits not based on personal data outside the program or behavioral profiles.
- Clear disclosure of data practices within the program.
- Government-approved pricing or bona fide discounts benefiting broad groups (e.g., military, seniors, teachers).
- Pricing required or expressly authorized by law.
- Bona fide group discounts.

Enforcement (Section 349-a, §4)

  • Attorney General enforcement:
    • May issue a cease-and-desist letter for alleged violations with a cure timeline.
    • If noncompliance persists, the AG may seek a court injunction.
    • Potential penalties if found in violation:
    • Civil penalties up to $10,000 for the first violation; up to $25,000 for each subsequent violation.
    • Additional penalties equal to profits earned from the violation.
    • Restitution and damages to affected consumers.
    • Other civil penalties or remedies as deemed appropriate by the court.
  • Civil penalties collected under the section support consumer protection and data privacy enforcement.

Private Right of Action (Section 349-a, §5)

  • Individuals harmed by violations may sue in a court of competent jurisdiction.
  • Potential remedies include:
    • Statutory damages: $500 to $5,000 per violation.
    • Actual damages (including overcharges or lost discounts).
    • Injunctive or declaratory relief.
    • Attorneys’ fees and costs.
  • Each instance of personalized algorithmic pricing or undisclosed automated pricing system usage constitutes a separate violation.
  • Waivers of rights under this section are void.

Construction (Section 349-a, §6)

  • The act does not limit other criminal or civil liability under law.

Practical Implications

  • Consumers: Enhanced transparency and protection from pricing practices that leverage personal data or undisclosed automated pricing.
  • Businesses: Firms operating in New York that use or plan to use automated or personalized pricing must implement clear disclosures, review pricing practices, and ensure compliance with exceptions.
  • Regulators: New enforcement toolkit including civil penalties, injunctive relief, and private rights of action to address violations.

Key Takeaways

  • The bill targets personalized pricing tied to personal data and requires explicit disclosures for both personalized and automated pricing systems.
  • It creates a robust enforcement framework with both state (AG) and private remedies.
  • Several broad and narrowly tailored exceptions may apply, notably for loyalty programs, public discounts, and legally mandated pricing.

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

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