How AI Sets Your Price Tag

The Hidden Cost of Personalized Pricing

In today’s digital age, your personal information is more valuable than ever. From your browsing habits to your shopping cart contents, companies are collecting and analyzing vast amounts of data to determine how much you’re willing to pay for products and services. This practice, often referred to as surveillance pricing, has raised significant concerns among consumers, regulators, and experts alike.

The entities involved in this data collection include retailers, social media platforms, app developers, and big data brokers. These organizations gather information about your preferences, location, and even your financial status to create detailed profiles. Using artificial intelligence, they can then tailor prices based on what they predict you’ll accept.

What Is Surveillance Pricing?

Surveillance pricing is a term used to describe the practice of setting individualized prices based on consumer data. This means that two people could be quoted different prices for the same product or service, depending on what a company believes they are willing or able to pay. While some may refer to it as dynamic or personalized pricing, the Federal Trade Commission (FTC) has labeled it as surveillance pricing, emphasizing the potential risks to consumer privacy and fairness.

The FTC has launched an ongoing investigation into this practice, aiming to understand its impact on consumers and the market. In a preliminary report from January, the agency highlighted several actions it has taken to address the rise of surveillance pricing. For example, the FTC issued a ban on the use and sale of sensitive location data by a data broker, which had been selling information about visits to health clinics and places of worship. Another complaint alleged that a data broker used location data to segment consumers into specific groups, such as "parents of preschoolers" or "Christian church goers."

The Role of AI in Consumer Profiling

Artificial intelligence plays a crucial role in creating these detailed consumer profiles. Companies use AI algorithms to analyze data and determine pricing strategies. This process, known as "bespoke pricing," allows businesses to set prices that maximize profits while minimizing the risk of losing customers.

However, this approach poses a threat to consumer welfare and free market principles. According to George Slover, general counsel and senior counsel for competition policy at the Center for Democracy and Technology, bespoke pricing can lead to higher prices for those who cannot afford them. He warned that unlike uniform pricing, AI-driven pricing systems give companies little incentive to offer discounts to those who can’t afford market prices.

Slover emphasized the importance of the FTC's investigation, stating that it could reveal more about the methodologies behind bespoke pricing and potentially lead to appropriate restrictions under existing law. For now, he suggested that consumers might consider masking their data through virtual private networks, anonymized intermediaries, or even fictional profiles to reduce the amount they have to pay.

The Need for Comprehensive Privacy Protections

The debate over surveillance pricing has sparked discussions about the need for comprehensive privacy protections. Slover pointed out that his organization, the Center for Democracy and Technology, has focused on data privacy since the internet was in its early stages. He stressed the importance of Congress implementing a strong, comprehensive privacy law to protect consumers.

Utah state Rep. Tyler Clancy echoed these concerns, emphasizing the need for guardrails to protect consumer data. He is exploring "consent provisions" to ensure Utahns know if their data is being used in pricing systems. Clancy cited the recent controversy involving Delta Air Lines, where an executive mentioned testing AI technology to set fares based on customer data. Although Delta later clarified that it was not using individualized pricing, the incident highlighted the growing public concern.

Clancy aims to compel transparency in how business entities use personal information in pricing systems for products and services. He believes that "sunshine is the best disinfectant" and hopes that increased transparency will lead to a better and freer market.

The Evolution of Targeted Advertising and Pricing

John Howell, a marketing professor at BYU, noted that targeted advertising came before targeted pricing. He explained that while the concept of individual-level pricing has been around for decades, the focus has shifted to advertising first. However, he warned that the negative consumer reaction to price discrimination is predictable.

Howell highlighted that the Sherman Antitrust Act, passed in 1890, was largely inspired by price discrimination by the railroad industry. He argued that while price discrimination can theoretically benefit more consumers, the current economic system tends to reward big players with increased power, disrupting competition and locking out smaller players.

In conclusion, the issue of surveillance pricing raises important questions about consumer privacy, fairness, and the role of technology in shaping the marketplace. As the FTC continues its investigation and lawmakers explore new regulations, the need for transparency and accountability in data practices becomes increasingly clear.