Stop AI Price Gouging and Wage Fixing Act of 2025
- Sponsor
- Rep. Casar, Greg [D-TX-35]
- Committees
- Education and Workforce Committee (primary)
- Last action
- Jul 23, 2025
Bottom line
The bill aims to prevent algorithmic discrimination in pricing and wages by restricting the use of personal surveillance data in automated decision systems, empowering consumers and workers with new protections and legal recourse.
What it actually does
This bill prohibits the use of automated decision systems, including AI, to set individualized prices for goods and services or to determine individual wages based on 'surveillance data.' It establishes exceptions for cost-based pricing, broadly offered discounts, and loyalty programs, provided specific transparency and data accuracy procedures are followed. The bill grants enforcement powers to the Federal Trade Commission, the Equal Employment Opportunity Commission, State attorneys general, and provides a private right of action for individuals harmed by violations.
Proponents argue
Proponents argue that this bill is essential to combat the growing problem of algorithmic exploitation, where opaque AI systems can leverage personal data to charge consumers higher prices or suppress worker wages. They contend it will promote economic fairness, protect individual privacy, and ensure that technological advancements do not lead to new forms of discrimination or economic inequality. The bill provides necessary transparency and accountability for automated decision-making processes.
Opponents contend
Opponents might argue that the bill's broad prohibitions and strict compliance requirements could stifle innovation in pricing and wage-setting models, potentially leading to less efficient markets or fewer personalized offers that could benefit consumers. They may also contend that the definitions of 'surveillance data' and 'automated decision system' are too broad, creating an undue regulatory burden on businesses and potentially increasing operational costs, which could be passed on to consumers or lead to reduced employment opportunities.
The bill is relatively short and clearly structured, making it accessible for an informed reader to understand its core provisions within a reasonable timeframe.
Section 2(a)
Prohibition on Surveillance-Based Price Setting
This provision generally prohibits businesses from using automated decision systems (like AI) to offer or inform customized prices for goods or services to specific individuals or groups based on 'surveillance data.' It includes exceptions for price differences based on reasonable costs, broadly offered discounts (e.g., for veterans or students), and loyalty programs, provided these exceptions meet strict transparency and data accuracy requirements.
Supporters argue
Supporters argue this provision is crucial for preventing 'price gouging' enabled by AI, where algorithms can identify a consumer's willingness to pay and charge them more, leading to unfair and discriminatory outcomes. It ensures that prices are based on objective factors rather than intrusive personal data.
Critics contend
Critics might argue that this provision could limit businesses' ability to offer dynamic pricing or personalized deals that could benefit some consumers, and that the compliance burden for distinguishing 'surveillance data' from permissible data could be substantial, potentially leading to less competitive pricing.
Tradeoffs
The provision balances the desire for consumer protection against potentially discriminatory algorithmic pricing with concerns about limiting business flexibility and innovation in pricing strategies. It seeks to draw a line between beneficial personalization and exploitative targeting.
Section 2(b), (c), (d)
Enforcement for Price Setting Violations
This section outlines the enforcement mechanisms for violations of the surveillance-based price setting prohibition. The Federal Trade Commission (FTC) is empowered to treat violations as unfair or deceptive acts or practices. State attorneys general can bring civil actions on behalf of their residents, seeking injunctions, compliance, and damages of at least $3,000 per violation. Importantly, individuals injured by a violation also have a private right of action to seek similar relief, and pre-dispute arbitration agreements or joint action waivers are explicitly deemed invalid for these claims.
Section 3(a)
Prohibition on Surveillance-Based Wage Setting
This provision prohibits employers from using automated decision systems that consider personal information or 'surveillance data' to set or inform the compensation (wages, bonuses, scheduling, etc.) of individual workers. An exception is made if the system uses only data regarding the worker's city or state and the cost of living in that area, allowing for geographically adjusted wages but preventing individualized wage suppression based on personal data.
Section 3(c), (d), (e), (f)
Enforcement for Wage Setting Violations
Similar to price setting, this section establishes multiple enforcement avenues for violations of the surveillance-based wage setting prohibition. The Equal Employment Opportunity Commission (EEOC) can bring civil actions on behalf of individuals or groups. The Federal Trade Commission (FTC) also has enforcement authority, treating violations as unfair or deceptive acts. State attorneys general can act on behalf of residents, and individuals harmed by violations have a private right of action, with pre-dispute arbitration and joint action waivers explicitly invalidated for these claims.
Section 4
Preemption of Directly Conflicting State Laws
This section clarifies that the Act does not preempt, displace, or supplant any State law, except to the extent that a State law directly conflicts with a provision of this Act. Crucially, it specifies that a State law does *not* conflict if it provides additional protections for individuals regarding surveillance-based wage setting or the collection of surveillance data, effectively setting a federal floor rather than a ceiling for protections.
Section 5
Preservation of Collective Bargaining Rights
This section explicitly states that nothing in the Act should diminish or interfere with employees' right to collectively bargain over terms and conditions of employment, including protections against surveillance-based wage discrimination. It establishes the Act's provisions as a minimum standard, allowing labor organizations and employers to negotiate stronger or additional protections through collective bargaining agreements. Employers are also required to provide advance notice and a reasonable opportunity for bargaining over any intended use of automated decision systems to set or influence employee compensation.
These clauses explicitly invalidate pre-dispute arbitration agreements and pre-dispute joint action waivers for claims brought under this Act. This means individuals cannot be forced into arbitration or prevented from joining class-action lawsuits if they are harmed by surveillance-based price or wage setting.
Section 2(d)(6) and Section 3(f)(6)
Why it matters:While standard legislative practice to place such clauses within enforcement sections, the invalidation of pre-dispute arbitration is a significant policy choice that often faces strong opposition and is therefore consequential despite its technical phrasing.
Case for: Supporters argue that these waivers often strip consumers and workers of their ability to seek justice, especially for systemic issues, and that their invalidation is crucial for the private right of action to be truly effective against powerful corporations.
Case against: Opponents contend that arbitration is a faster and less costly alternative to litigation, and that invalidating these agreements will lead to an increase in expensive and time-consuming court cases, ultimately harming businesses and potentially consumers through higher costs.
Estimated impact: Significantly shifts the legal landscape for disputes related to algorithmic pricing and wages, potentially enabling more class-action lawsuits and direct court proceedings.
The definition of 'surveillance data' is broad, including 'data obtained through observation, inference, or surveillance of an individual that is related to personal information, genetic information, behavior, or biometrics of the individual or a group... and includes information gathered, purchased, or otherwise acquired.' This broad scope is central to the bill's prohibitions.
Section 2(e)(9) and Section 3(g)(7)
Why it matters:Definitions are standard locations for such details, but the expansive nature of 'surveillance data' is a critical element that determines the practical reach of the bill's prohibitions. Its broadness could be seen as either comprehensive protection or overreach.
Case for: Proponents argue that a broad definition is necessary to prevent companies from finding loopholes to continue using intrusive data for pricing and wage setting, ensuring comprehensive protection against various forms of algorithmic exploitation.
Case against: Critics might argue that such a broad definition could inadvertently capture data that is not truly 'surveillance-based' or is commonly used for legitimate business purposes, leading to unintended consequences and excessive restrictions on data utilization.
Estimated impact: Determines the scope of data that businesses can and cannot use for algorithmic pricing and wage setting, potentially requiring significant changes to data collection and processing practices.
These clauses explicitly extend the Federal Trade Commission's enforcement authority to common carriers subject to the Communications Act of 1934 and to nonprofit organizations, overriding typical jurisdictional limitations of the FTC.
Section 2(b)(3) and Section 3(d)(3)
Why it matters:This is a deliberate expansion of FTC authority into areas it typically does not regulate, ensuring comprehensive coverage of algorithmic pricing and wage setting across various sectors. It addresses potential gaps in consumer and worker protection.
Case for: Proponents argue that common carriers and nonprofits increasingly use algorithmic systems that can engage in surveillance-based pricing or wage setting, and it is crucial for the FTC to have jurisdiction over these entities to prevent loopholes and ensure consistent enforcement.
Case against: Some might argue that extending FTC jurisdiction to common carriers could create regulatory overlap with existing sector-specific regulators (like the FCC) and that applying these rules to nonprofits could place undue burdens on organizations not primarily driven by profit.
Estimated impact: Broadens the scope of federal oversight for algorithmic pricing and wage setting to include sectors typically exempt from FTC jurisdiction, ensuring wider application of the bill's protections.