Seattle’s ‘Surveillance Pricing’ Ban Is a Solution Searching for a Problem

Seattle recently passed the Fair Pricing and Transparency Ordinance, which prevents large online and brick‑and‑mortar grocery retailers from using consumers’ “behavior, location, demographic characteristics, biometric data, or other personal information” to offer consumers distinct prices. The city’s announcement touts protections against price manipulation based on social media activity and chatbot conversations.

The ordinance includes carveouts for certain discounts but still prohibits discounts tailored to an individual shopper. Seattle’s ban follows similar proposals in Maryland, Connecticut, and New Jersey.

Supporters of the law stress affordability, fairness, and privacy, framing it as a check on big grocery chains profiting from customers’ data. In the announcement, City Councilmember Alexis Mercedes Rinck stated, “Groceries are getting more expensive for everyday Seattleites, while the buying, selling, and leveraging our private information to manipulate prices is making big national grocery corporations millions in profits….This is an important step we can take to prevent AI-assisted price gouging and ensure fair discounts for everyone.”

The hard evidence of retailers using surveillance pricing hardly lives up to these claims. The ordinance cites investigations by Consumer Reports that found Instacart shoppers paid different prices for the same items, but it found no evidence that personal data played a role. Instacart said the price differences came from random tests, which it stopped last December. The ordinance also cites an investigation into Kroger that found it targets discounts based on customers’ demographic characteristics, and inferred income, education, and loyalty levels but again cites no evidence that it raised prices based on that information. Neither case involved the use of social media history or chatbot conversations.

Unequal prices don’t mean consumers are being ripped off. As Josh Withrow, a tech and innovation policy fellow at the R Street Institute, told Reason, “Rewards programs that give certain people discounts that other people don’t would benefit some customers more than others, but I don’t see how that’s harming anybody.” He added, “As long as they’re not actively gouging customers…that’s not a harm. That’s just personalized benefits.”

In a proposed policy statement outlining how it would police personalized pricing, the Federal Trade Commission acknowledged that “the extent to which businesses currently use personalized pricing is not well understood, and the effects of personalized pricing on consumers are unclear.” There’s no guarantee that banning algorithmic pricing would reduce prices—and as others have pointed out, banning the practice risks banning beneficial discounts and loyalty programs with it. 

Councilmember Maritza Rivera (D–Seattle), one of the two votes against the ordinance, called it “an overly broad ordinance that has the potential to backfire.” She stated, “I would have liked to have seen legislation that banned algorithmic pricing while ensuring loyalty programs wouldn’t be impacted. It’s now very possible those programs will go away, and groceries could become even more expensive.”

Withrow has similar concerns; he told Reason that rules like Seattle’s create “a permission-based system where the only personalized pricing programs that are legal are the ones that have been specifically carved out….It basically kills innovation on the potentially beneficial ways that companies can use data-driven pricing to better get goods to customers.”

Rinck frames the ordinance as a way to stop “AI-assisted price gouging.” But Withrow argues markets already punish that behavior: “A company that uses personalized pricing to consistently charge certain customers more would soon find itself with competitors who advertise doing the opposite—smart consumers will shop elsewhere.”

The term surveillance pricing gives an already common practice a sinister connotation. Personal pricing has been occurring long before AI or computers existed. Algorithms and larger data sets simply help companies gain better insights and meet customers at their willingness to pay more efficiently.

Seattle’s ordinance may be well-intentioned, but it targets a largely theoretical problem and puts real discounts at risk. As Withrow tells Reason, “any regulation should target actual demonstrated harms, not hypothetical use cases that, as far as I can tell, don’t exist.”