The Federal Trade Commission (FTC) is currently conducting an investigation into the pricing practices of companies that utilize artificial intelligence (AI) to personalize prices for consumers. This practice, known as “surveillance pricing,” involves the use of consumer data to tailor prices to individual customers. The FTC has sent information-seeking orders to eight companies that have publicly acknowledged using AI and machine learning for data-driven targeting.
The Rise of Surveillance Pricing
The concept of surveillance pricing has emerged as a result of advancements in technology that allow companies to gather and analyze vast amounts of consumer data. This data includes information such as age, location, credit score, and browsing history, which can be used to determine a customer’s willingness to pay for a product or service. By leveraging AI algorithms, companies can adjust prices in real-time based on individual characteristics and behaviors.
One of the companies under scrutiny by the FTC is Revionics, which specializes in AI-powered price optimization solutions. While Revionics denies engaging in consumer surveillance, the FTC is investigating the company’s practices along with other major players such as Mastercard, JPMorgan Chase, Bloomreach, Accenture, McKinsey & Company, TASK Software, and PROS. These companies have been asked to provide reports outlining their surveillance pricing practices to the FTC.
The Ethical Implications of Surveillance Pricing
The use of surveillance pricing raises ethical concerns about consumer privacy and fairness. Professor Jean-Pierre Dubé of the University of Chicago Booth School of Business points out that companies may have access to information about consumers that was not knowingly shared or authorized. This lack of transparency in data collection and pricing strategies can lead to personalized pricing along dimensions that may not be acceptable to consumers.
Furthermore, the expansion of surveillance pricing beyond online shopping to brick-and-mortar stores raises questions about the extent of consumer monitoring in physical retail environments. Retailers like Walmart are implementing digital price tags that can be updated in real-time based on factors like expiration dates and customer demand. Similarly, e-commerce platforms like Instacart are introducing AI-powered “smart carts” that display personalized ads and coupons to shoppers.
The Evolution of Personalized Pricing
Surveillance pricing is a modern iteration of personalized pricing, which has been a common practice in various markets throughout history. The idea of adjusting prices based on a customer’s willingness to pay dates back to ancient times when vendors in bazaars would offer different prices to customers based on their perceived wealth or status. In contemporary markets, personalized pricing can be beneficial in maximizing profits and expanding access to goods and services for consumers with varying budgets.
However, the use of AI algorithms in surveillance pricing introduces a new level of complexity and opacity to pricing strategies. By analyzing a combination of demographic information, browsing history, purchasing patterns, and other data points, companies can determine a customer’s willingness to pay more accurately than ever before. This level of precision raises concerns about discrimination, pricing fairness, and consumer consent.
The Role of Transparency and Regulation
While some experts caution against using negative terms like “surveillance pricing” to describe personalized pricing practices, there is a consensus that transparency and consumer awareness are essential in this evolving landscape. Haggai Porat, a teaching fellow at Harvard Law School, emphasizes the importance of informing consumers about how their data is used in pricing decisions so that they can make informed choices about engaging with sellers. Transparency can help build trust between companies and consumers while ensuring that pricing practices are fair and ethical.
As the FTC continues its investigation into surveillance pricing, the regulatory landscape around AI-driven pricing strategies may evolve. Companies will need to navigate the delicate balance between leveraging data for personalized pricing and respecting consumer privacy and autonomy. Ultimately, the goal is to create a marketplace where pricing is transparent, fair, and beneficial to both consumers and businesses.