At The Money: Is Technology Price Gouging Consumers?

Summary of At The Money: Is Technology Price Gouging Consumers?

by Bloomberg

25m•October 14, 2026
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Overview of At The Money: Is Technology Price Gouging Consumers?

In this Bloomberg At The Money segment, Barry Ritholtz speaks with Lindsay Owens, CEO of the Groundwork Collaborative and author of Gouged: The End of a Fair Price and What That Means for Your Wallet, about how modern pricing technology is changing what consumers pay. The discussion argues that while price gouging is not new, AI, algorithms, data collection, and dynamic pricing tools have made it faster, harder to detect, and more pervasive across industries like housing, grocery delivery, travel, and retail.

Key Themes and Takeaways

Technology has transformed pricing into a highly engineered system

  • Pricing is no longer as simple as “cost plus margin.”
  • Companies now use:
    • AI and pricing software
    • revenue management systems
    • electronic shelf labels
    • consumer data and surveillance tools
  • These systems can adjust prices in real time and target individual shoppers rather than setting one fair price for everyone.

Consolidation makes price gouging easier

  • Owens argues that decades of reduced antitrust enforcement and industry consolidation have weakened competition.
  • In less competitive markets, companies have more power to raise prices without losing customers.
  • Technology then amplifies that power by making price discrimination and coordination easier.

Surveillance pricing is the new frontier

  • The episode highlights how companies can use location data, purchase history, device data, and other signals to infer a consumer’s willingness to pay.
  • This can mean different people pay different prices for the same item at the same time.
  • Owens frames this as a system designed to extract as much consumer surplus as possible.

Notable Examples Discussed

RealPage and rental pricing

  • RealPage’s YieldStar software is presented as a major example of algorithmic price coordination in housing.
  • The tool allowed landlords to share sensitive information and receive rent recommendations that many followed.
  • Owens says this turned a traditionally competitive market into something closer to coordinated pricing.
  • She notes estimates that the software may have added around $120 per month to rents in some markets.

Instacart’s dynamic pricing experiment

  • Groundwork Collaborative, Consumer Reports, and More Perfect Union ran an investigation using hundreds of volunteer shoppers.
  • They found that nearly 75% of items were priced differently for different shoppers, with differences reaching as high as 23%.
  • The backlash led Instacart to stop the experiment and promise that shoppers in the same place at the same time would receive the same prices.

Walmart’s patent and predictive pricing

  • Owens points to a Walmart patent involving scan-and-go technology and electronic shelf labels.
  • In the patent example, buying tuna could trigger a higher price for mayonnaise.
  • Walmart disputed the framing, but Owens emphasizes that the patent itself describes the capability.

Travel, food, and other everyday examples

  • She cites examples like:
    • Expedia charging more to users from higher-income areas
    • Delta experimenting with AI-assisted fare pricing
    • fast-food and retail systems potentially using vehicle, location, and shopping data to infer willingness to pay

Where the Technology Could Help

Potential public-good use cases

Owens does not say the technology is inherently evil, but she argues it is mostly being used against consumers. One example of a positive use:

  • Electronic shelf labels can help stores quickly discount near-expired food
  • That could reduce food waste and help lower-income shoppers access cheaper food

Consumer Impact and Concerns

The main harm is opacity

  • The old promise of e-commerce was more transparency and comparison shopping.
  • Owens argues the reality has been the opposite:
    • less transparency
    • more manipulation
    • more personalized pricing
    • less ability to compare prices fairly

“Corporate Robin Hood” doesn’t really hold up

  • Owens rejects the claim that charging rich shoppers more helps subsidize lower prices for everyone else.
  • Her view is that the real goal is to charge each consumer as much as possible based on their willingness to pay.

Willingness to pay is not the same as income

  • A person may pay more because they are desperate, not because they are wealthy.
  • Examples include urgent travel, sick children, or other time-sensitive needs.
  • That makes personalized pricing especially exploitative.

Closing Perspective

The segment ends by warning that the next wave of AI shopping assistants and “agentic commerce” may deepen the same problems if they gain access to even more consumer data. The central message is that modern technology is not just helping companies operate more efficiently; it is also enabling them to squeeze consumers harder, often in ways that are invisible and difficult to challenge.

Bottom Line

The episode argues that today’s high prices are not only a result of inflation, tariffs, or interest rates. Technology, data collection, and weak competition are increasingly allowing retailers and platforms to charge people different prices and push them toward the maximum they are willing to pay.