Last fall, Massachusetts Senators Ed Markey and Elizabeth Warren, along with Representatives Jim McGovern and Ayanna Pressley, sent a letter to Stop & Shop suggesting the grocery chain’s use of a price algorithm tool is driving up food prices, especially in low-income areas. This critique warrants closer examination.
Price algorithms themselves have not independently driven up food prices; instead, they help grocery stores — which often operate on profit margins of just 1% to 3% — better understand current market conditions. These algorithms analyze data on supply chain fluctuations, consumer demand, and other factors to determine appropriate pricing in real time. They do not artificially inflate prices but rather adjust them in response to shifts in the market.
What we can fact-check is the cause of food price inflation: grocery prices did surge recently. In 2022 alone, grocery prices increased by 10%, the fastest rate since 1979. But USDA reports that this spike was driven by a variety of different issues such as COVID-19 impacts (labor shortages, transportation issues), a bird flu outbreak (which hit egg/poultry supply), and the war in Ukraine (often called “Europe’s breadbasket,” impacting grain and fertilizer supply). While general inflation may have had a hand in increasing food prices, the U.S. Government Accountability Office reports that “other factors — like global disruptions to the food supply chain — may have had a greater impact.”
Meanwhile, consumer sentiment toward Stop & Shop remains positive. According to data from the online service Stats Panda, Stop & Shop ranks as the most popular grocery store in four out of the six New England states, including Massachusetts. In a competitive grocery market, algorithm-driven price hikes by one franchise risk driving consumers elsewhere — whether to nearby competitors or the rapidly expanding online grocery sector. If Stop & Shop’s AI algorithm is engaging in price gouging while competitors are not, why has it not lost its customer base?
The recent scrutiny of Stop & Shop’s pricing algorithm highlights a broader trend. AI is a relatively new and evolving technology, and its economic impact is actively being evaluated across different nooks and crannies of various industries. However, attributing increases in housing and food prices to AI overlooks the numerous other factors that influence costs.
A related example involves the AI pricing software RealPage, which property owners use to help them determine their prices. The Justice Department has filed a lawsuit alleging that RealPage’s YieldStar and AIRM enabled landlords to coordinate pricing, thereby contributing to higher rents, and in January, Massachusetts Attorney General Andrea Campbell joined this lawsuit.
However, just like with grocery inflation, attributing price increases to an AI tool requires more evidence as their are multiple factors contributing to the housing crisis.
Multiple factors contribute to Massachusetts’ expensive housing, including strict zoning laws and complex regulations that raise construction costs, as well as broader inflationary trends. These longstanding issues have resulted in a persistent housing shortage. Similar constraints exist in other American cities, where regulations and limited development opportunities continue to drive up costs.
Ultimately, pricing and AI tools are informational aids that businesses can choose to implement or disregard. While the attention on AI, a relatively new technology, is understandable, policymakers and stakeholders may benefit from addressing underlying economic forces — such as labor market dynamics, global geopolitical issues, regulations, and supply chain disruptions — when seeking to manage rising prices in Massachusetts and beyond.
Certainly, AI is not without risks, and it will require thoughtful oversight as it continues to evolve. Nonetheless, AI-driven pricing mechanisms have demonstrated benefits across industries, such as ride-sharing, where dynamic pricing has been shown to enhance consumer welfare, healthcare, where AI improves pricing efficiency and access , and air travel, where algorithmic pricing optimizes market efficiency and more.
Given the numerous confounding factors driving rising food and housing costs, attributing these increases to AI algorithms without rigorous studies that control for other variables is premature. A more nuanced, evidence-based approach is necessary before AI is classified as a driver of rising costs. In fact, premature policy interventions could lead to unintended consequences, potentially reducing public welfare by limiting some of the aforementioned benefits of AI.
Dokyun Lee is Kelli Questrom Associate Professor of IS & Computing and Data Sciences at Boston University