As artificial intelligence (AI) and “big data” continue to shape modern commerce, lawmakers across the country are increasingly turning their attention to monitored pricing legislation. This new policy trend seeks to limit or ban the use of algorithms and automated decision-making systems that adjust prices based on consumer data such as browsing history, location, and even mobile phone battery life. Although none of these proposals have yet been enacted, they represent a growing interest in protecting consumers from pricing practices that rely on personal or device-specific data. Below is an overview of how California, Colorado, Georgia, Minnesota, and Pennsylvania have addressed or are addressing the issue of monitored pricing legislation in 2025.
California: Fair Online Pricing Act
California’s SB 259, entitled the “Fair Online Pricing Act,” would prohibit businesses from generating or displaying prices online to consumers based on certain data from the consumer’s device. The bill prohibits the use of “input data” such as battery life, performance characteristics, or device hardware or hardware condition, including the age of the device, the presence or absence of software, and geolocation data, when used to make inferences about a consumer. Limited exceptions are made for the use of location data to determine repair or maintenance costs, calculate trade-in value, or reflect legitimate regional price differentials or real-time demand.
The law defines terms such as “coupon,” “discount,” “hardware condition,” and “online device,” which broadly apply to connected devices such as smartphones and computers. This allows companies to continue offering public discounts that don’t rely on limited data. SB 259 also makes clear that its provisions supplement existing consumer protection laws and exclude cellular broadcasting technologies that do not use personal location data from its scope.
Colorado: Prohibits price and wage discrimination based on surveillance
Colorado’s HB 25-1264 proposed broad restrictions on the use of “surveillance data” to determine individual prices and wages. The bill defined surveillance data as information obtained through observation, inference, or monitoring that relates to an individual’s characteristics, behavior, or biometrics. Companies would have been prohibited from using automated decision-making systems, including artificial intelligence or machine learning, to set different prices or payment rates based on this data.
The measure also included exceptions for legitimate cost-based price differences and discounts offered across the board to certain groups, such as veterans and seniors. Insurance companies and credit decisions under the Fair Credit Reporting Act were also exempted. Colorado’s attorney general and district attorneys could impose fines of up to $10,000 for each violation, while individuals could also seek civil damages. Although comprehensive, the proposal did not advance out of committee, reflecting the early and exploratory stage of Colorado’s monitored pricing legislation effort.
Georgia: Addressing price and wage discrimination with AI
Georgia’s SB164 also sought to prohibit “surveillance-based price discrimination” and “surveillance-based wage discrimination.” The proposal would make it illegal for companies to use automated decision-making systems or AI tools to set personalized prices or wages based on data collected through observations or inferences about consumer behavior, personal characteristics, or biometric identifiers.
The bill created an exception for insurers that rely on legitimate cost fluctuations and risk-related data. Employers using AI to determine wages would have been required to disclose in plain language what data was considered and how it influenced wage decisions. Enforcement authority was given to the Georgia Attorney General, with civil penalties of up to $10,000 per violation and the right of private action against affected individuals. Although SB 164 did not advance in 2025, it was Georgia’s first major attempt to implement a monitored pricing law targeting algorithmic decision-making in trade practices.
Minnesota: Ban on AI-based dynamic pricing
Minnesota’s HF 2452 and SF 3098 bills, introduced in 2025, sought to ban the use of artificial intelligence to dynamically set product prices in real time. If enacted, this legislation would enact Minnesota Statute §325F.997, which would prohibit AI systems from adjusting or controlling prices based on market demand, competitor pricing, inventory levels, or consumer behavior.
By targeting what is often referred to as “dynamic pricing” or “algorithmic pricing,” the bill represented a narrower form of supervised pricing law that focused specifically on AI tools rather than all automated decision-making systems. Under current consumer protection law, enforcement authority was assigned to the Minnesota Attorney General. Neither bill advanced beyond committee review during the 2025 session.
Pennsylvania: Proposed ban on rideshare monitoring fees
In Pennsylvania, Rep. Andre Carroll and Rep. Ben Waxman circulated a co-sponsor memorandum announcing their intention to introduce legislation that would ban “monitored pricing” by rideshare companies. The upcoming proposal, “Ban Rideshare Companies from Monitoring Pricing,” would prohibit rideshare companies from using consumer device data, such as battery life, number of wireless connections, and age of the device, to determine the price of a ride. Unlike surge pricing, which reflects real-time market demand, this proposal focuses on ensuring that pricing decisions are not based on personal or technical information from users’ mobile phones. Although still in its memo stage, the initiative would bring Pennsylvania into the national conversation on monitored pricing laws, emphasizing consumer privacy and fair pricing in the digital economy.
