What is 'supervised pricing,' where large corporations exploit consumers to the absolute limit by taking advantage of the information gap? What are the problems with it?
While it's generally believed that product prices are determined by the balance of supply and demand, in today's world where various user data can be collected, 'surveillance pricing,' where companies use information asymmetry to set prices, is on the rise.
Surveillance Pricing: Exploiting Information Asymmetries - LPE Project
https://lpeproject.org/blog/surveillance-pricing-exploiting-information-asymmetries/
Before the 1870s, fixed prices were rare for retail goods in America. Typically, customers and shop assistants would negotiate prices, finding a compromise to determine the final transaction price. However, the Grand Depot department store, which opened in conjunction with the Philadelphia World's Fair , eliminated bargaining and introduced fixed prices, leading to the widespread adoption of the fixed-price concept.
However, Lin points out that 150 years later, there is a movement to return from fixed pricing to variable pricing, also known as 'supervised pricing.' Modern large corporations can collect all kinds of data, such as users' purchase history, location information, and other personal information. By using this, they can offer different prices for the same product or service depending on the user's situation and demand.
Lynn points out that supervised pricing is part of the American tradition of 'consumer exploitation.' Consumer exploitation refers to the practice of minimizing the gap between 'how much consumers are willing to pay' and 'how much they actually pay,' thereby extracting as much of consumers' surplus funds as possible.
Companies have been experimenting with various pricing schemes since the 2010s. In 2011, ticket vendor Ticketmaster introduced 'dynamic pricing,' which changes ticket prices according to demand. In the same year, ride-hailing service Uber introduced 'surge pricing,' which increases fares on weekends and during events. Hotel booking service Orbitz offered higher rates to Mac users, and educational service Princeton Review charged higher rates in areas with a large Asian population.
Lin states, 'These pricing strategies have a common characteristic: they exploit the information gap and take advantage of consumers when they are most constrained and unable to act. The important point is that the purpose of supervised pricing is not personalization, but maximum exploitation.' In other words, supervised pricing is not a service to increase user satisfaction, but rather exploitation aimed at maximizing corporate profits.
Some politicians have already recognized the problem of monitored pricing, and in May 2025, New York State passed the
While acknowledging that the Algorithmic Pricing Disclosure Act is a first step in the right direction, Lin points out that simply maintaining transparency in pricing is not enough to curb the harmful effects of supervised pricing. Although consumers may understand that the prices they see are determined by algorithms, companies can still continue to use supervised pricing. Therefore, Lin argues that more than transparency is needed to address supervised pricing.
The ' Stop AI Price Gouging and Wage Fixing Act,' introduced in 2025 by Representatives Gregorio Cazar (Democrat) and Rashida Tlaib (Democrat), explicitly prohibits companies from using AI-controlled pricing and allows state attorneys general and ordinary citizens to file civil lawsuits against companies. Furthermore, Senator Ruben Gallego (Democrat) has also introduced the ' One Fair Price Act,' which contains similar provisions.
While these bills are unfortunately unlikely to pass due to the divided state of Congress, Lynn points out that calls for the abolition of supervised pricing are growing. She also notes that state legislatures have many members who are more attuned to residents' concerns, such as rising housing and food costs, making it easier for bills to pass that would curb supervised pricing.
Companies are resisting the suppression of monitored pricing, and
In Sorrell v. IMS Health, the Supreme Court ruled that Vermont law imposes restrictions based on speakers and content by targeting 'certain speakers (pharmaceutical sales representatives and data providers)' and 'certain content (pharmaceutical marketing).' The Vermont law, which allows the use of similar data for research and educational purposes but does not permit its use for marketing purposes, is considered to be restricting freedom of speech.
Regarding this ruling, Lynn points out that the court is confusing 'privacy protection' with 'restriction of expression.' If the creation and distribution of data such as a doctor's prescription history were to constitute speech protected by the First Amendment, then it would encompass regulations on all kinds of data, including 'food ingredient labeling,' 'disclosure of securities reports,' and 'disclosure related to workplace safety and labor laws.' Of course, this is impossible, but companies opposing monitored pricing are citing the Sorrell v. IMS Health case and broadly interpreting the First Amendment.
The First Amendment was also cited as the reason in a lawsuit filed by the National Retail Federation (NRF) against New York State's Algorithmic Pricing Disclosure Act. Fortunately, the U.S. District Court for the Southern District of New York dismissed the NRF's case, ruling that New York State's law merely mandates commercial disclosure and differs from Vermont's law, which attempted to restrict commercial speech. Lynn argues that this case should serve as a lesson, and that legislation aimed at curbing supervised pricing should be carefully drafted to regulate only economic activity and behavior, rather than targeting specific speakers or content.
Lynn stated, 'Surveillance pricing is the next point of contention regarding data privacy. This practice further encourages aggressive data collection with the ultimate goal of exploiting as much consumer surplus as possible. While legal regulations on information disclosure are a first step in the right direction, they are not enough. State and federal regulations must address the root causes of harmful data practices such as the buying and selling of personal data, consumer segmentation and discrimination, and commercial surveillance, while also avoiding the First Amendment landmines left by Sorrell.'
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