The bill prohibits using automated decision systems to set individualized prices or wages when those decisions rely, in whole or in part, on surveillance data about a person or group. It defines ‘‘surveillance data’’ broadly (including observed, inferred, purchased, biometric, and genetic-linked information), creates narrow exceptions (cost-based price differences, broadly defined public discounts, and opt-in loyalty programs that meet transparency and uniformity requirements), and requires businesses to publish accuracy, notice, and challenge procedures 180 days before deploying such systems.
Enforcement is split: the Federal Trade Commission enforces the pricing prohibition as an unfair or deceptive practice; the Equal Employment Opportunity Commission and the FTC share roles for wage-setting. States can sue as parens patriae and private plaintiffs have a damages remedy (greater of actual damages or $3,000 per violation, with discretionary trebling for willfulness), and pre-dispute arbitration/joint-action waivers are expressly unenforceable for claims under the Act.
The statute preserves state laws that provide stronger protections and protects collective bargaining rights.
At a Glance
What It Does
The bill bars firms from using automated decision systems to offer customized prices or worker compensation when the system relies on surveillance-derived personal data, while permitting price differences tied strictly to legitimate cost differences or clearly disclosed, uniformly applied discounts. It requires public publication of data-accuracy checks, consumer/worker challenge processes, and explanations of which data inform pricing or wages at least 180 days before use.
Who It Affects
Online marketplaces, retailers and platforms that run real-time personalized pricing, employers and staffing platforms using algorithmic wage or scheduling tools, AI vendors and data brokers that supply surveillance-derived features, and consumer-facing loyalty programs that use behavioral data to determine offers.
Why It Matters
This creates a statutory prohibition targeting algorithmic personalization practices that regulators and advocates have warned can produce discriminatory, exploitative, or anticompetitive outcomes. It adds robust public and private enforcement tools and a low statutory damages floor that could drive compliance costs, contractual changes, and litigation risk for companies that monetize detailed consumer and worker data.
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What This Bill Actually Does
The Act takes two parallel tracks: one aimed at prices and one at wages. For prices, it makes it unlawful to use an automated decision system to offer a customized price to a specific person or narrowly defined group when that price depends on surveillance data.
The bill spells out three narrow safe harbors: price differences driven only by verifiable cost differences; broadly available, publicly disclosed discounts for categories like teachers or veterans; and opt-in loyalty or rewards programs—so long as eligibility is disclosed, the offer is administered uniformly, and any surveillance data used is limited to offer administration and not re-used for profiling or additional personalization.
For wages, the statute bars automated systems that consider personal or surveillance-derived information to set or inform pay, but it permits systems that rely solely on the worker’s city or State and the local cost-of-living as the only automated inputs. Both titles force covered entities to publish, at least 180 days before deployment, procedures that document how they ensure data accuracy, how affected people can correct or challenge data, and what specific data the system considers and how it influences prices or wages.Enforcement is multi-layered.
The FTC is charged with enforcing the pricing prohibition as an unfair or deceptive practice and is given the full panoply of FTC powers; the EEOC can bring wage-setting cases on behalf of workers. State attorneys general can file parens patriae suits and seek statutory remedies.
Importantly, individuals can sue for each violation and recover either actual damages or a $3,000 statutory recovery (with the court able to treble awards for willful violations). The Act also nullifies pre-dispute arbitration and class-waiver clauses for claims under the Act, preserves stronger state protections, and explicitly protects collective bargaining rights while requiring employers to bargain over planned uses of automated systems where a collective bargaining agreement exists.
The Five Things You Need to Know
Covered entities must publish conspicuous, accessible procedures at least 180 days before using an automated decision system to set prices or wages; those procedures must include data-accuracy checks and a consumer/worker correction process.
The Act defines surveillance data to include observed, inferred, purchased, biometric, and genetic-linked information and treats use of such data in individualized price or wage offers as prohibited.
Private plaintiffs and state attorneys general can recover the greater of actual damages or $3,000 per violation, with courts authorized to triple awards for willful violations and to award costs and attorney’s fees.
Pre-dispute arbitration agreements and pre-dispute joint-action waivers are unenforceable for claims under the Act, preserving access to judicial relief and class or collective actions.
For wages, the only automatic-data exception permitted is when the automated system uses solely the worker’s city or State and local cost-of-living data to inform compensation.
Section-by-Section Breakdown
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Ban on surveillance-based price setting with narrow exceptions
This provision prohibits using automated decision systems to set individualized prices based on surveillance data. It creates three narrow exceptions: (1) prices that differ only because of reasonable cost differences to serve different consumers; (2) broadly available discounts for defined groups that are publicly disclosed; and (3) opt-in loyalty or rewards programs—subject to disclosure, uniform application, and a restriction that surveillance data may be used only to administer the reward and not for additional profiling or targeted pricing. Practically, companies that have relied on micro-targeted price personalization must either redesign pricing logic to fit an exception or stop using surveillance-derived inputs.
Transparency and remedial procedures before deployment
The bill requires covered actors to publish, 180 days before using the covered practices, procedures detailing how they verify data accuracy, how consumers can challenge or correct data, and what data the automated decision system considers and how it affects prices. This creates a pre-deployment statutory compliance checkpoint and a public record third parties and regulators can use to audit claims of compliance.
Enforcement architecture for pricing: FTC, states, and private suits
The FTC enforces the pricing ban as an unfair or deceptive practice and can use its full enforcement toolbox; the statute also empowers state attorneys general to sue on behalf of residents and gives individuals a private right to sue with statutory damages. The law explicitly treats violations as FTC Act violations, expands FTC reach to common carriers and nonprofits for this statute’s purposes, and strips out arbitration and class-waiver defenses for covered claims.
Prohibition and limited exception for surveillance-based wage setting
Section 3 bars using automated systems that consider personal or surveillance data to set or inform worker compensation, but permits systems that use only the worker’s city or State and cost-of-living metrics. It mirrors the pricing title’s transparency requirements and creates parallel enforcement: EEOC may litigate on behalf of affected workers while the FTC retains an enforcement role; states and private plaintiffs can also pursue remedies.
Limited preemption and state-floor rule
The Act does not preempt state laws except where there is a direct conflict; importantly, state laws that provide greater protections with respect to surveillance-based wage setting or surveillance-data collection remain valid. That makes this a federal minimum standard and invites a patchwork where some states tighten protections further.
Collective bargaining preserved and supplemented
The bill expressly preserves and prioritizes collective bargaining rights: it is a floor, not a ceiling, for labor protections; employers must provide notice and a reasonable opportunity to bargain before using automated systems to influence pay when a collective bargaining agreement covers the workforce; and stronger bargained protections remain enforceable beyond the Act’s baseline.
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Explore Economy in Codify Search →Who Benefits and Who Bears the Cost
Every bill creates winners and losers. Here's who stands to gain and who bears the cost.
Who Benefits
- Consumers subject to individualized pricing—They gain a statutory prohibition on prices set using surveillance-derived personal data and a private damages remedy, lowering the risk of stealth, targeted price gouging.
- Low‑wage and algorithmically managed workers—The wage ban (except for city/State + cost-of-living inputs) reduces the chance that opaque surveillance features will depress pay or automate discriminatory compensation decisions.
- Labor unions and bargaining units—The Act protects collective bargaining leverage and requires notice and an opportunity to bargain over algorithmic pay uses, enlarging labor’s role in shaping pay technology.
- Privacy and civil-rights advocates—They obtain a broad statutory definition of surveillance data and public procedural disclosures that make algorithmic practices more transparent and legally contestable.
Who Bears the Cost
- Online platforms, travel/ride/hospitality marketplaces, and retailers using dynamic pricing—They must remove or re-design personalization that relies on surveillance inputs or reclassify offers to fit narrow safe harbors, entailing engineering, compliance, and revenue impacts.
- Employers and gig-platforms that use algorithmic scheduling, performance scoring, or pay optimization—They may need to refactor pay systems, limit data inputs, or face litigation and administrative enforcement.
- Data brokers and AI vendors that supply surveillance-derived features—Their products become higher‑risk or constrained, which could reduce demand or force product redesigns to exclude sensitive signals.
- Regulators and courts—FTC, EEOC, and state AG offices will face new investigatory and litigation burdens; agencies may need funding and technical capacity to oversee algorithmic systems effectively.
Key Issues
The Core Tension
The central dilemma is protecting people from opaque, surveillance-driven price and wage decisions that can be discriminatory or exploitative, while avoiding a blunt prohibition that also halts legitimate, efficient forms of personalization and cost-based differentiation. The bill favors strong consumer and worker protections at the cost of greater compliance, operational friction, and litigation exposure for firms—and it leaves regulators to define critical line-drawing through enforcement and rulemaking.
The statute’s broad definitions—especially of ‘‘surveillance data’’ and ‘‘personal information’’—are both its strength and its liability. They give regulators and plaintiffs wide latitude to challenge uses of inferred or purchased features, but they also create uncertainty for firms about which signals are permissible.
For example, common non-identifying behavioral signals (time of day, device type, local demand indicators) could be swept up if treated as ‘‘related to’’ personal information without clarifying guidance.
The 180‑day advance publication requirement creates a hard operational lead time that conflicts with modern continuous-deployment models; companies that deploy incremental model updates will need change-control processes tied to statutory notices. The Act also establishes multiple enforcement pathways (FTC, EEOC, state AGs, private plaintiffs), raising the risk of inconsistent standards, forum shopping, and duplicative proceedings.
Finally, the $3,000 statutory floor per violation and the opt-out of pre-dispute arbitration and class-waivers substantially increase aggregate litigation risk—plaintiffs’ bar and state enforcers may pursue high-volume claims that impose settlement pressure even where defenses exist.
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