Before the 1870s, retail goods rarely carried fixed prices. Instead, haggling was the norm. Customers and store clerks engaged in a song and dance, testing the other’s economic limits. Then, on the eve of the Philadelphia World’s Fair, businessman John Wanamaker transformed an abandoned railroad station into the Grand Depot, one of the first department stores in the United States. At the grand opening, each item in the sprawling store was affixed with a conspicuous label declaring a non-negotiable price. When millions came to the city for the fair, many had their first encounter with fixed price tags. The elimination of haggling saved both customers and clerks time, making the market significantly more efficient. Fair visitors brought the idea of the price tag home with them. Soon, businesses around the world adopted fixed prices and price transparency.
One hundred and fifty years later, the datafication of the economy is causing the retail experience to regress to a form of variable pricing far more coercive than the haggling of the past. With online shopping, social media, and data collection, modern corporations have access to more information than ever before. Retailers can view your purchase history, location, personal demographics, and much more. This has enabled businesses across a variety of sectors to engage in surveillance pricing—the practice of extracting and exploiting personal information in order to charge customers different prices for the same product or service. Today, variable pricing is back, but this time the seller knows everything about you.
The viability of surveillance pricing—its profitability, ubiquity, and exploitative nature—hinges on the presence of market failures. Severe information asymmetries are perhaps the most insidious. While corporations have access to data brokers, online behavioral advertising, and algorithms that can adjust prices in real time, consumers are more disempowered than ever.
A Tradition of Consumer Exploitation
Surveillance pricing is not new. American capitalism has a long tradition of consumer exploitation, including targeted advertising, behavioral advertising, price discrimination, and algorithmic pricing. All of these tactics make it easier for corporations to extract more consumer surplus; that is, to close the gap between what consumers are willing to pay and what they actually pay.
Since the 2010s, companies have been experimenting with more precise and invasive pricing schemes. In 2011, Ticketmaster rolled out “dynamic pricing,” which adjusted ticket prices based on demand and caused prices to reach levels that captured virtually all consumer surplus. Later that year, Uber implemented its notorious “surge pricing,” which applied multipliers to the price of a ride during weekends, special events, and inclement weather. In 2012, Orbitz infamously displayed more expensive hotel offers to Mac users on the assumption that they were less price-sensitive. A 2015 ProPublica investigation revealed that Princeton Review charged higher prices to customers from ZIP codes with more Asian people. Staples and Target have both experimented with GPS-based pricing, charging higher prices to customers close to them and far from competitors. In 2025, a group of nonprofits revealed that some grocery prices on Instacart differed by as much as 23 percent from one customer to another.
These pricing strategies share a common characteristic: using information asymmetries to take advantage of consumers when they are most constrained and captive. Crucially, the objective of surveillance pricing is not personalization, but maximum extraction.
Beyond Laws Mandating Disclosure
While an outright ban on surveillance pricing offers a direct solution, such an approach still leaves underlying systemic problems unaddressed. The extractive aspects of a failing oligopolistic market—data brokers, online behavioral advertising, information asymmetry, and consumer isolation—remain even if corporations can no longer openly engage in surveillance pricing. Conversely, mere disclosure—which typically only requires companies to inform consumers that prices may be set based on personal data—is far too narrow to meaningfully protect consumers from price gouging. Disclosure regimes outsource accountability by placing the onus on consumers to determine how their data may affect the price they are shown instead of changing corporations’ practices. Laws mandating disclosure may leave consumers more informed, but they fail to lower prices and prevent companies from amassing personal data.
In May 2025, New York became the first state to pass a law specifically targeting surveillance pricing. The Algorithmic Pricing Disclosure Act requires companies that set prices using an algorithm based on consumers’ personal data to display a disclosure stating, “THIS PRICE WAS SET BY AN ALGORITHM USING YOUR PERSONAL DATA.” The Act defines personal data as “any data that identifies or could reasonably be linked, directly or indirectly, with a specific consumer or device.” Several other states have pending bills that would either ban surveillance pricing outright or require similar disclosures.
Although New York’s Algorithmic Pricing Disclosure Act represents a step in the right direction, it ultimately falls into the transparency trap. That is, transparency alone will not curb the harms of surveillance pricing. The New York law merely mandates that businesses acknowledge their use of surveillance pricing. The consumer is left informed but unprotected. Without options to safeguard their data, the value of the disclosure is questionable at best. Furthermore, individuals often lack the necessary expertise or resources to make sense of disclosed information, resulting in information overload or fatigue (when was the last time you read a cookie consent prompt?). The disclosure approach is untenable as digital products and services become increasingly essential for navigating daily life.
Addressing surveillance pricing requires more than mere transparency; it necessitates meaningful accountability. To that end, recent federal bills offer a more impactful solution by including a missing ingredient: enforcement. The Stop AI Price Gouging and Wage Fixing Act of 2025, introduced by House Representatives Greg Casar (D-TX) and Rashida Tlaib (D-MI), would eliminate surveillance pricing and wage setting. With respect to surveillance pricing, the proposed bill defines “surveillance data” as not only data obtained by the business implementing surveillance pricing but information gathered or purchased from other sources. Crucially, state attorneys general and private citizens could bring civil actions for alleged violations. Additionally, the Act empowers the FTC to impose fines and consumer redress on offenders. In December 2025, Senator Ruben Gallego (D-AZ) introduced the “One Fair Price Act of 2025,” which includes similar definitions and enforcement mechanisms. Unfortunately, the likelihood of either bill passing is low.
While federal legislation faces significant hurdles in a divided Congress, there is an appetite for regulating surveillance pricing. The outlook is more positive in state legislatures, where lawmakers are more sensitive to constituents’ concerns about the rising costs of groceries and housing.
The Problem of First Amendment Expansion
Despite my gripes with the New York law’s distinct lack of bite, business interests were quick to call the law too broad and confusing for consumers. Critics allege that the language imposed by the Act could be interpreted as a warning about pricing errors or overcharging instead of a neutral transparency statement. In July 2025, the National Retail Federation, the world’s largest retail trade association, challenged the New York disclosure law on First Amendment grounds, arguing that the Act “compels NRF members to publish misleading government opinions.” The Southern District of New York dismissed NRF’s lawsuit in October 2025, reasoning that “the statement requirement by the Act . . . is plainly factual,” and “the required disclosure accurately describes plaintiff’s members’ practices.” The case is pending appeal before the Second Circuit, but the law went into effect in November 2025.
While New York’s law survived the challenge at the district court level, the lawsuit highlights a significant risk to legislative efforts to limit companies’ ability to collect information on consumers: the First Amendment.
The Supreme Court in Sorrell v. IMS Health (2011) struck down Vermont’s Prescription Confidentiality Law, which prohibited the sale of doctors’ prescribing history to drug marketers. According to the Vermont legislature, the law was designed to prohibit pharmacies from selling or using “prescriber-identifiable” data to drug companies. By banning the sale of prescription records, the law aimed to protect physician privacy, curb targeted pharmaceutical marketing, and ultimately, reduce reliance on expensive brand-name drugs.
The Court, however, held that restricting corporate flows of information—here, physicians’ prescribing records—violated the First Amendment. Specifically, the Court found that the Vermont law imposed speaker- and content-based restrictions by targeting specific speakers (pharmaceutical sales representatives and data miners) and specific content (drug marketing). In fact, the Court held that the law amounted to both content and viewpoint discrimination because it permitted the same information to be used freely for other purposes, such as research and education, but restricted its use for marketing purposes. In a 6-3 decision, the Court in Sorrell concluded that data mining for marketing purposes is speech fully protected by the First Amendment.
The Sorrell case reflects a dire interpretive misstep in First Amendment jurisprudence: conflating privacy regulation with speech regulation. The Court found that the creation and dissemination of information are themselves speech protected by the First Amendment. However, if “data” is given the same constitutional treatment as “speech,” this expansionist interpretation would swallow up virtually every regulation affecting data flows: product labels, securities disclosures, job safety and labor law disclosures, and so on. Not all regulations of information flows fall within the realm of the First Amendment.
NRF’s lawsuit seeking to enjoin the New York Algorithmic Pricing Disclosure Act also invoked Sorrell, arguing that “the Act is subject to heightened review because it singles out a class of speakers for differential treatment based on the subject matter of their speech.” Thankfully, the district court distinguished the New York law as requiring commercial disclosure whereas the Vermont law restricted commercial speech.
Despite this limited victory, courts have increasingly adopted an expansionist conception of the First Amendment post Sorrell, rendering the constitutionality of data privacy statutes and even disclosure statutes unclear. Sorrell is an obstacle to an outright ban on surveillance pricing and limits states’ ability to regulate data brokers. However, Sorrell also offers valuable lessons for states interested in regulating surveillance pricing and enacting privacy protections more broadly. Since Sorrell, courts have applied a more forgiving standard to disclosures. In fact, when the Southern District of New York dismissed the NRF’s lawsuit, it held that disclosure mandates promote the free flow of information. To avoid Vermont’s pitfall of targeting a specific category of speakers and content, legislation should be drafted carefully to only regulate economic activity or conduct.
Surveillance pricing is the next data privacy battleground. The practice further incentivizes aggressive data collection, with the end goal of extracting as much consumer surplus as possible. Although disclosure legislation is a step in the right direction, it cannot be the final step. State and federal legislation must address the upstream drivers of harmful data practices—the buying and selling of personal data, consumer segmentation and discrimination, and commercial surveillance—while avoiding the First Amendment landmines left by Sorrell.
If every habit, activity, or decision can be accounted for by data brokers, advertisers, and retailers, what does that say about our agency and free will? If surveillance pricing becomes the new status quo, we can ponder that question while being ripped off.
