Algorithmic Price-Fixing | Rogé Karma is a staff writer at The Atlantic.

The plaintiffs suing RealPage, including the Arizona and Washington, D.C., attorneys general, argue that this has enabled a critical mass of landlords to raise rents in concert, making an existing housing-affordability crisis even worse. 

(In a statement, RealPage has responded that the share of landlords using its services is far lower, about 7 percent nationwide. 

RealPage’s estimate includes all rental properties, whereas the lawsuits focus on multifamily-building units.)

We’re Entering an AI Price-Fixing Dystopia
Algorithmic collusion appears to be spreading to more and more industries. And existing laws may not be equipped to stop it.
By Rogé Karma 

Illustration by Matteo Giuseppe Pani

August 10, 2024, 7:30 AM ET

HOW IT WORKS: "Property owners feed RealPage’s “property management software” their data, including unit prices and vacancy rates, and the algorithm—which also knows what competitors are charging—spits out a rent recommendation. If enough landlords use it, the result could look the same as a traditional price-fixing cartel: lockstep price increases instead of price competition, no secret handshake or clandestine meeting needed.
Without price competition, businesses lose their incentive to innovate and lower costs, and consumers get stuck with high prices and no alternatives. Algorithmic price-fixing appears to be spreading to more and more industries. And existing laws may not be equipped to stop it.. .

Its main competitor, Yardi, is involved in a similar lawsuit.
One of RealPage’s subsidiaries, a service called Rainmaker, faces multiple legal challenges for allegedly facilitating price-fixing in the hotel industry. (Yardi and Rainmaker deny wrongdoing.)

• Similar complaints have been brought against companies in industries as varied as health insurance, tire manufacturing, and meat processing. 
• But winning these cases is proving difficult.

The challenge is this: Under existing antitrust law, showing that companies A and B used algorithm C to raise prices isn’t enough; you need to show that there was some kind of agreement between companies A and B, and you need to allege some specific factual basis that the agreement existed before you can formally request evidence of it. This dynamic can place plaintiffs in a catch-22: Plausibly alleging the existence of a price-fixing agreement is hard to do without access to evidence like private emails, internal documents, or the algorithm itself. But they typically can’t uncover those kinds of materials until they are given the legal power to request evidence in discovery. . .

The basic premise of free-market capitalism is that prices are set through open competition, not by a central planner. That goes for algorithmic central planners too.

ADDITIONAL EXAMPLES CITED: GAS STATIONS AND HOTELS

In the case of RealPage, the plaintiffs were able to make the peg fit. 

But in May, a Nevada judge dismissed a similar case against a group of Las Vegas hotels who used Rainmaker, concluding that there wasn’t enough evidence of a price-fixing agreement, because the hotels involved hadn’t shared confidential information with one another and weren’t required to accept Rainmaker’s recommendations, even if they allegedly did so about 90 percent of the time. 

“The rulings so far have set the bar very high,” Kenneth Racowski, a litigation attorney at Holland & Knight, told me. 

The RealPage case “was able to clear that bar, but it might prove to be the exception.”

And cases like RealPage and Rainmaker may be the easy ones. 

• In a series of papers, Stucke and his fellow antitrust scholar Ariel Ezrachi have outlined ways in which algorithms could fix prices that would be even more difficult to prevent or prosecute—including situations in which an algorithm learns to fix prices without its creators or users intending it to. 
• Something similar could occur even if companies used different third-party algorithms to set prices. 

They point to a recent study of German gas stations, which found that when one major player adopted a pricing algorithm, its margins didn’t budge, but when two major players adopted different pricing algorithms, the margins for both increased by 38%

“In situations like these, the algorithms themselves actually learn to collude with each other,” Stucke told me. 

“That could make it possible to fix prices at a scale that we’ve never seen.”

Rogé Karma is a staff writer at The Atlantic.

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