Prohibit Surveillance Price & Wage Setting
HB1210 prohibits businesses from using “surveillance data” and price-or-wage-setting algorithms to make individualized decisions about what consumers are charged or what workers are paid. The bill defines surveillance data broadly to include information inferred or collected through observation of personal characteristics, online behavior, or biometrics, and it defines a price or wage setting algorithm as a technology or computational process that uses data analytics, AI, or similar tools as a substantial factor in setting prices or wages. It also adds a deceptive trade practice violation for conduct that violates the new part of the consumer protection statute.
The bill creates a general ban on individualized price setting and individualized wage setting, while listing several exceptions. For pricing, it allows differences based on actual cost differences, supply-and-demand fluctuations, publicly disclosed discounts, loyalty or rewards programs, customer-service credits, need-based programs such as hospital discounted care or charity care, recurring subscription pricing, and certain credit-related decisions based on consumer reports or required application data. For wages, it permits individualized wages based only on worker-specific seniority or task-related performance data, and it requires employers using such algorithms to disclose in plain language what data is used and how it affects wages. Businesses using these algorithms must also publish procedures for data accuracy, worker access to information, and correction or challenge of data.
The bill would affect Colorado’s consumer protection and labor-related practices by restricting the use of algorithmic profiling in pricing and compensation decisions. It amends the deceptive trade practices statute in Title 6 and authorizes the Attorney General to adopt rules to implement and enforce the new provisions. The law would apply prospectively to conduct occurring on or after the effective date.
The overall sentiment in the recorded votes suggests the bill was supported but not unanimously. It passed key House and Senate floor votes with clear majorities, but several committee and floor votes were close, indicating meaningful concern even among legislators who ultimately allowed it to advance. The bill’s title and structure suggest a policy goal of limiting hidden or discriminatory algorithmic pricing and pay-setting practices.
The main points of contention appear to be the breadth of the ban and how it would affect legitimate business practices. Supporters likely view the bill as a consumer- and worker-protection measure aimed at preventing AI-driven discrimination, price discrimination, and opaque wage setting. Opponents or skeptics likely focused on whether the definitions are too broad, whether the restrictions could interfere with dynamic pricing, loyalty programs, credit underwriting, or compensation systems, and whether compliance and disclosure requirements would be burdensome for employers and businesses.
HB1210 would add a new part to Colorado’s consumer protection laws prohibiting individualized price and wage setting using surveillance data and price-or-wage-setting algorithms, and it would make violations a deceptive trade practice under section 6-1-105. It would impose disclosure and procedure requirements on businesses and employers that use such algorithms, while carving out specified exceptions for legitimate pricing, credit, insurance, loyalty, and pay-equity-related practices. The Attorney General would gain rulemaking authority to enforce the new framework.
The bill appears to have been generally favorable but somewhat divided. It advanced through both chambers with majority support, including some close votes in committee and on the floor, suggesting broad interest in regulating algorithmic pricing and pay practices but also substantial concern about the scope and practical effects of the proposal. The final concurrence votes indicate the bill ultimately secured enough support to pass despite opposition.
The main contention centers on whether the bill’s prohibition on individualized price and wage setting is too sweeping or too vague, especially given the broad definition of surveillance data and the use of AI or analytics in business decisions. Supporters likely emphasize consumer privacy, fairness, and protection against discriminatory pricing or pay discrimination, while critics likely worry about impacts on dynamic pricing, loyalty and rewards programs, credit decisions, insurance practices, and employer compensation systems. Another likely point of debate is the compliance burden created by required disclosures, data-access procedures, and correction mechanisms for workers and consumers.