An Act to create 100.303 of the statutes; Relating to: prohibiting retail dynamic price gouging of consumer goods and providing a penalty.
AB1186 would create a new section of Wisconsin statutes prohibiting “dynamic price gouging” in the retail sale of consumer goods. The bill defines that term to mean the use of a computational system or model, including artificial intelligence or machine learning, that processes consumer data to set a customized price for a specific consumer. It also defines consumer data broadly to include information purchased from data brokers, data gathered through surveillance or automated scraping, data obtained without consent, and information tied to protected characteristics or prohibited bases of discrimination.
Under the bill, a retail seller could not offer or sell a consumer good at a price established in whole or in part through dynamic price gouging. The prohibition applies to consumer goods sold in person or online for personal, family, or household use, and the bill authorizes enforcement by the Department of Agriculture, Trade and Consumer Protection, and, after consultation, the Department of Justice. Enforcement tools include warning notices, civil forfeitures of up to $10,000, and injunctive relief. The act would take effect on the first day of the fourth month after publication.
The bill would add a new consumer-protection restriction to Wisconsin law by creating s. 100.303, regulating how retail prices may be individualized using consumer data and automated systems. It would affect retailers selling packaged consumer goods and would give state agencies explicit authority to investigate and enforce violations through warnings, civil penalties, and court orders. The measure would also indirectly constrain the use of data brokerage, surveillance-based profiling, and algorithmic pricing in retail settings.
The available record suggests the bill was introduced as a consumer-protection measure, with support implied by its multiple authors and cosponsors. However, there are no committee transcripts or recorded votes in the provided materials, and the bill ultimately failed to pass pursuant to Senate Joint Resolution 1. As a result, the public record here does not show detailed debate, but the overall framing indicates concern about algorithmic pricing and consumer fairness.
The main points of contention likely center on whether retailers should be barred from using AI-driven or data-driven pricing tools, and whether the bill’s definition of consumer data is too broad. Potential critics could argue that the measure would limit legitimate pricing innovation, complicate online and in-person retail operations, or create compliance challenges for businesses using analytics. Supporters would likely emphasize privacy, anti-discrimination concerns, and preventing individualized price discrimination based on surveillance, purchased data, or protected characteristics.