This bill, titled the “Fair Cart Act,” would add a new article to the General Business Law regulating algorithmic pricing systems used by retailers, online marketplaces, delivery platforms, transportation network companies, lodging and hospitality providers, ticket sellers, and other consumer-facing businesses in New York. The bill is aimed at preventing deceptive or unfair price increases that rely on personal data, inferred economic status, geolocation, behavioral profiling, or similar individualized characteristics, especially when those increases are not clearly disclosed to consumers.
The bill defines key terms such as algorithmic pricing system, baseline public price, deceptive algorithmic price inflation, dynamic pricing, personal data, personalized discount, and price transparency. It prohibits covered entities from using automated pricing tools to secretly raise prices above a baseline public price, misrepresent how prices are determined, or falsely present individualized prices as universally available. At the same time, it expressly preserves lawful dynamic pricing and a wide range of discounting practices, including loyalty programs, coupons, rebates, promotional pricing, geographic promotions, subscription discounts, and electronic shelf labeling systems.
The bill would require clear and conspicuous disclosure when prices are materially personalized or influenced by personal data or consumer profiling, and it would require accurate disclosure of mandatory fees before purchase. Enforcement authority would be given to the Division of Consumer Protection and the Attorney General, with a 30-day cure period before civil enforcement in appropriate cases. Knowing violations could result in civil penalties of up to $10,000 per violation, and the Division would also be authorized to issue guidance and consumer education materials.
The bill’s impact on state law would be to create a new consumer-protection framework specifically targeting algorithmic and AI-driven pricing practices in the marketplace. It would affect a broad range of businesses that use automated pricing or personalized offers, while also protecting common retail pricing tools and business efficiencies. The measure would likely require covered entities to review pricing systems, disclosure practices, and compliance procedures to ensure they do not engage in undisclosed individualized price inflation.
The general sentiment reflected in the bill text is cautious but supportive of innovation: it recognizes the benefits of AI, dynamic pricing, and digital commerce, while emphasizing consumer trust, transparency, and fairness. Because there are no committee transcripts or recorded votes provided, there is no direct evidence of opposition or support from lawmakers in the available record. The main point of contention inherent in the bill is the balance between consumer protection and business flexibility—specifically, whether algorithmic pricing should be tightly regulated when it personalizes prices, versus preserved as a legitimate tool for discounts, inventory management, and market-based pricing.
The bill would amend the General Business Law by creating Article 22-C, establishing new rules for algorithmic pricing transparency and prohibiting deceptive individualized price inflation. It would impose disclosure obligations on covered entities, authorize enforcement by the Division of Consumer Protection and the Attorney General, and create civil penalties for knowing violations, while expressly preserving lawful dynamic pricing and discount programs.
The bill’s stated approach is generally pro-consumer but not anti-technology: it seeks to curb undisclosed or unfair price discrimination while preserving beneficial uses of AI, dynamic pricing, and personalized discounts. No committee debate or vote record is available, so the broader legislative sentiment cannot be measured directly from the provided materials.
The central policy tension is between transparency and innovation. Supporters of the bill would likely favor protections against hidden price increases based on personal data, geolocation, or profiling, while businesses and technology providers may be concerned about compliance burdens, ambiguity around what counts as “materially personalized” pricing, and the risk of exposing proprietary algorithms. The bill attempts to address those concerns by carving out safe harbors for loyalty programs, promotions, dynamic pricing, and trade secrets.