Maryland Doesn't Need to Stop Dynamic Pricing

Developments in artificial intelligence continue to raise alarm among the public and lawmakers. Among the many concerns cited about artificial intelligence and automation is dynamic pricing. To this end, Maryland Governor Wes Moore signed legislation last week banning grocery stores and third-party delivery services from using individual shopper data to increase prices "dynamically."

Under dynamic pricing, sellers may use data about shopping behavior to automate and continuously adjust their prices. Under individualized dynamic pricing – sometimes called surveillance pricing in pejorative terms – businesses set different prices for different consumers by charging more to shoppers who appear willing to pay a premium or offering lower prices to customers who might not otherwise buy. Other types of dynamic pricing may include shifting prices at different times of day based on changes in demand or competitive conditions.

The underlying logic of dynamic pricing is straightforward: businesses have always tried to match price to demand, and data-driven tools make doing so easier.

Maryland’s bill drew public support, reflecting broader concern with companies exploring individualized pricing, especially on food and housing as basic needs. Critics frame these practices as predatory: corporations using shadowy algorithms to target and extract as much money as possible from individual shoppers.

However, the alarm reflects a misconception regarding what data collection and algorithmic pricing can actually accomplish. Even the most sophisticated artificial intelligence uses incomplete information and thus imperfect predictions – the same reason why centrally planned economies with government-dictated prices are so inefficient. Consumer preferences change with income, season, family circumstances, competing options, and other infinite variables that are impossible to capture in a dataset. The premise that an algorithm can reliably identify each shopper's maximum willingness to pay overstates the role that data and algorithms play in society.

Dynamic pricing is also already a routine feature of commerce. Airlines adjust fares continuously based on demand, booking patterns, and seat availability. That's why the person sitting next to you on a plane likely paid a different price than you paid for her ticket. Bars and restaurants offer happy hour pricing. Retailers run flash sales, time-limited promotions, and personalized discounts. Even Maryland’s own law acknowledges this reality with its numerous exemptions and clarifications for longstanding practices – promotional pricing, loyalty program discounts, and other temporary price reductions.

Moreover, the alarm over dynamic prices overlooks the consumer benefits. A grocer or other business that makes more sales has more room to keep overall prices low, and dynamic individualized prices can be what closes a sale that otherwise would not have happened. This means that people can buy things that otherwise wouldn’t have fit in their budgets.

Maryland’s law purports to address a public concern by conflating a common business practice with a supposedly harmful predatory practice and without acknowledging the consumer benefits. Maryland should indeed tackle deceptive trade practices in grocery stores and elsewhere, but states should not ban technology before actual harms to consumers materialize. Regulating against possible harms has its consequences – shoppers forgo benefits that they never even see.