AI Price Discrimination and the End of the “Uniform Price”

How often have you gone to a store and discovered a “deal” on a product?  This is known as consumer surplus, or the positive difference between what one is willing and able to pay and the market price.  Under normal circumstances, in a market economy, some consumers are getting a deal because their individual demand is greater than the market price at which everyone can purchase the product.  Whenever there is consumer surplus, the seller is missing out on hypothetical profit: consumers would pay more, but don’t have to.

Price Discrimination Explained

In a market economy, everyone pays the same price for a good or service.  This price is based on supply and demand, and the market price, also known as equilibrium price, is the price at which quantity demanded equals quantity supplied.  In other words, this is the market-clearing price where everything produced is sold and a shortage or surplus does not occur.  If a seller attempts to raise the price to make more revenue, he or she will cause a surplus because some of the product will not sell quickly enough - some consumers will no longer buy.

To continue to sell a maximum number of units, the seller could try to charge each customer the maximum that he or she is [likely] willing to pay.  This is known as price discrimination.  While charging different customers different prices sounds unfair, the concept has been practiced for ages.  What is typically considered discriminatory is first degree price discrimination, where every individual receives a different price.

Third-Degree Price Discrimination

This type of price discrimination occurs when different groups in society are charged different prices to encourage their loyalty to a business or product.  Common examples include senior discounts, student discounts, and veteran or first responder discounts.  Although the seller makes less per-unit revenue from individuals in these groups, it may generate greater long-term revenue by creating a more loyal customer base.  The decrease in per-unit revenue to individuals in these groups may also be rationalized as an investment in marketing by creating positive word-of-mouth.  Sellers that offer discounts to popular groups, such as veterans and first responders, may attract more customers altogether.

For this price discrimination to be successful, the good or service usually has to be one that cannot be resold for a higher price.  Thus, deals for seniors, students, veterans, and first responders often tend to be services (haircuts, oil changes, tickets for events that are not pre-sold) or immediate-consumption goods (food, beverages, utilities).  These cannot be stored and sold to members of other groups for a higher price to make a profit.

Second-Degree Price Discrimination

Customers who purchase in different volumes are subject to this type of price discrimination, which typically offers lower prices to customers who buy in bulk.  Big-box retailers like Sam’s Club and Costco sell these deals to members, who pay an annual fee to access goods that are sold in large units and offer lower per-unit prices.  Customers who frequently make purchases online may earn deals and coupons based on their high volume of consumption.  The sellers’ rationale is simple: they are willing to make less profit per-unit from these high volume customers because they enjoy a very high likelihood of selling more units.

With second-degree price discrimination, customers self-identify as high volume buyers and often have to pay a fee to do so.  This creates a degree of protection against low volume buyers who might take advantage of the buy-in-bulk deals.  Unfortunately for the seller, both third-degree and second-degree price discrimination leave a lot of potential profit on the table.  The seller knows relatively little about the individual buyer’s income, personal tastes and preferences, or mood at the time of purchase.

First-degree Price Discrimination

The ability to charge each individual customer a different price is first-degree price discrimination, and is rare in reality.  An auction, where potential customers bid on a good or service against rivals, is an example.  Of course, it would be very inefficient for sellers to auction most items, and the auction would have to be a minimum bid auction to guarantee a break-even price.  At an auction, buyers self-identify their individual demand through their increasing bids.  How can firms determine this individual demand through traditional selling?

To charge some individuals higher or lower prices than the average, the firm would have to be able to quickly estimate individual demand based on measurable variables.  Some variables are easier for the firm to access than others, such as a customer’s purchase history and demographic information.  Others, such as income and personal tastes and preferences, are harder to learn.  However, what if tools existed that allowed firms to analyze a customer’s likely individual demand within seconds?

AI and Perfect Price Discrimination

AI software may allow firms, in the near future, to deeply analyze prospective customers within seconds while they browse the firm’s website or store.  A customer who creates a profile may have his or her social media history analyzed to determine tastes and preferences, educational background, emotional state, and likely level of income.  In a store, a security camera feed might allow AI to analyze a customer’s physical appearance, clothing choices, and gait to determine identity, probable health, and possible emotional state.  All of this data would be quickly compiled into an individual price for that customer, charging high prices to those who seem more willing and able to make the purchase.

Criticisms of AI Analysis of Customers

Of course, critics abound of the possibility of using AI to scrutinize customers.  There are many privacy concerns of AI software being able to get around typical privacy settings on social media sites, as well as analyze photographs.  Most in-person customers likely do not want security camera footage used by AI to identify them and begin searching through their Internet data.  Aside from privacy concerns, there are also ethical concerns about first-degree price discrimination being used to charge individuals higher prices.  On a macro scale, this could significantly erode consumers’ incentive to work harder and innovate in order to earn greater income.  Why work hard to make more money if AI will simply charge you more for everything?  This would create, in addition to a potential mass unemployment crisis, a mass productivity collapse as workers choose to earn less money in order to pay less for products.