If you hire your property, there’s an excellent likelihood your landlord makes use of RealPage to set your month-to-month fee. The corporate describes itself as merely serving to landlords set essentially the most worthwhile worth. However a sequence of lawsuits says it’s one thing else: an AI-enabled price-fixing conspiracy.
The traditional picture of price-fixing includes the executives of rival corporations gathering behind closed doorways and secretly agreeing to cost the identical inflated worth for no matter they’re promoting. This kind of collusion is likely one of the gravest sins you may commit in opposition to a free-market economic system; the late Justice Antonin Scalia as soon as known as price-fixing the “supreme evil” of antitrust legislation. Agreeing to repair costs is punishable with as much as 10 years in jail and a $100 million fantastic.
However, because the RealPage instance suggests, know-how could supply a workaround. As a substitute of getting collectively along with your rivals and agreeing to not compete on worth, you may all independently depend on a 3rd get together to set your costs for you. Property house owners feed RealPage’s “property administration software program” their knowledge, together with unit costs and emptiness charges, and the algorithm—which additionally is aware of what opponents are charging—spits out a hire suggestion. If sufficient landlords use it, the end result might look the identical as a conventional price-fixing cartel: lockstep worth will increase as an alternative of worth competitors, no secret handshake or clandestine assembly wanted.
With out worth competitors, companies lose their incentive to innovate and decrease prices, and shoppers get caught with excessive costs and no options. Algorithmic price-fixing seems to be spreading to an increasing number of industries. And present legal guidelines might not be geared up to cease it.
In 2017, then–Federal Commerce Fee Chair Maureen Ohlhausen gave a speech to antitrust legal professionals warning in regards to the rise of algorithmic collusion. “Is it okay for a man named Bob to gather confidential worth technique info from all of the members in a market after which inform all people how they need to worth?” she requested. “If it isn’t okay for a man named Bob to do it, then it in all probability isn’t okay for an algorithm to do it both.”
The numerous lawsuits in opposition to RealPage differ of their particulars, however all make the identical central argument: RealPage is Bob. In response to one estimate, in additional than 40 housing markets throughout america, 30 to 60 % of multifamily-building models are priced utilizing RealPage. The plaintiffs suing RealPage, together with the Arizona and Washington, D.C., attorneys normal, argue that this has enabled a essential mass of landlords to boost rents in live performance, making an present housing-affordability disaster even worse. (In a assertion, RealPage has responded that the share of landlords utilizing its providers is much decrease, about 7 % nationwide. RealPage’s estimate contains all rental properties, whereas the lawsuits give attention to multifamily-building models.)
In response to the lawsuits, RealPage’s shoppers act extra like collaborators than opponents. Landlords hand over extremely confidential info to RealPage, and lots of of them recruit their rivals to make use of the service. “These sorts of behaviors increase a giant crimson flag,” Maurice Stucke, a legislation professor on the College of Tennessee and a former antitrust legal professional on the Division of Justice, advised me. When corporations are working in a extremely aggressive market, he stated, they sometimes go to nice lengths to guard any delicate info that might give their rivals an edge.
The lawsuits additionally argue that RealPage pressures landlords to adjust to its pricing options—one thing that may make no sense if the corporate had been merely being paid to supply individualized recommendation. In an interview with ProPublica, Jeffrey Roper, who helped develop certainly one of RealPage’s primary software program instruments, acknowledged that one of many biggest threats to a landlord’s income is when close by properties set costs too low. “When you’ve got idiots undervaluing, it prices the entire system,” he stated. RealPage thus makes it arduous for purchasers to override its suggestions, in keeping with the lawsuits, allegedly even requiring a written justification and express approval from RealPage workers. Former staff have stated that failure to adjust to the corporate’s suggestions might end in shoppers being kicked off the service. “This, to me, is the largest giveaway,” Lee Hepner, an antitrust lawyer on the American Financial Liberties Venture, an anti-monopoly group, advised me. “Enforced compliance is the hallmark function of any cartel.”
The corporate disputes this description, claiming that it merely presents “bespoke pricing suggestions” and lacks “any energy” to set costs. “RealPage clients make their very own pricing choices, and acceptance charges of RealPage’s pricing suggestions have been enormously exaggerated,” the corporate says.
In December, a Tennessee choose rejected RealPage’s movement to have a class-action lawsuit in opposition to it dismissed, permitting the case to go ahead. It might be a mistake, nonetheless, to conclude from that instance that the authorized system has the algorithmic price-fixing drawback below management. RealPage might nonetheless prevail at trial, and in any case, it isn’t alone. Its primary competitor, Yardi, is concerned in an identical lawsuit. One among RealPage’s subsidiaries, a service known as Rainmaker, faces a number of authorized challenges for allegedly facilitating price-fixing within the lodge business. (Yardi and Rainmaker deny wrongdoing.) Related complaints have been introduced in opposition to corporations in industries as different as medical health insurance, tire manufacturing, and meat processing. However successful these instances is proving tough.
The problem is that this: Beneath present antitrust legislation, displaying that corporations A and B used algorithm C to boost costs isn’t sufficient; it’s good to present that there was some form of settlement between corporations A and B, and it’s good to allege some particular factual foundation that the settlement existed earlier than you may formally request proof of it. This dynamic can place plaintiffs in a catch-22: Plausibly alleging the existence of a price-fixing settlement is difficult to do with out entry to proof like personal emails, inner paperwork, or the algorithm itself. However they sometimes can’t uncover these sorts of supplies till they’re given the authorized energy to request proof in discovery. “It’s like attempting to suit a sq. peg in a spherical gap,” Richard Powers, a former deputy assistant legal professional normal within the DOJ antitrust division, advised me. “It makes the job actually arduous.”
Within the case of RealPage, the plaintiffs had been capable of make the peg match. However in Might, a Nevada choose dismissed an identical case in opposition to a gaggle of Las Vegas accommodations who used Rainmaker, concluding that there wasn’t sufficient proof of a price-fixing settlement, as a result of the accommodations concerned hadn’t shared confidential info with each other and weren’t required to just accept Rainmaker’s suggestions, even when they allegedly did so about 90 % of the time. “The rulings to this point have set the bar very excessive,” Kenneth Racowski, a litigation legal professional at Holland & Knight, advised me. The RealPage case “was capable of clear that bar, however it may show to be the exception.”
And instances like RealPage and Rainmaker could be the straightforward ones. In a sequence of papers, Stucke and his fellow antitrust scholar Ariel Ezrachi have outlined methods during which algorithms might repair costs that may be much more tough to forestall or prosecute—together with conditions during which an algorithm learns to repair costs withouts its creators or customers intending it to. One thing related might happen even when corporations used completely different third-party algorithms to set costs. They level to a current examine of German fuel stations, which discovered that when one main participant adopted a pricing algorithm, its margins didn’t budge, however when two main gamers adopted completely different pricing algorithms, the margins for each elevated by 38 %. “In conditions like these, the algorithms themselves truly study to collude with one another,” Stucke advised me. “That would make it attainable to repair costs at a scale that we’ve by no means seen.”
Not one of the conditions Stucke and Ezrachi describe contain an express settlement, making them virtually not possible to prosecute below present antitrust legal guidelines. Value-fixing, in different phrases, has entered the algorithmic age, however the legal guidelines designed to forestall it haven’t saved up. Powers stated he believes present antitrust legal guidelines cowl algorithmic collusion—however he apprehensive that he is likely to be incorrect. “That is the factor that saved me up at night time,” he stated about his tenure on the Division of Justice. “The fear that each one 100-plus years of case legislation on price-fixing may very well be circumvented by know-how.”
Earlier this yr, a handful of Senate Democrats led by Amy Klobuchar launched a invoice that may replace present legal guidelines to robotically presume a price-fixing settlement every time “opponents share competitively delicate info by a pricing algorithm to boost costs.” That invoice, like a lot congressional laws, is unlikely to develop into legislation anytime quickly. Native governments might need to take the lead. Final week, San Francisco handed a first-of-its-kind ordinance banning “each the sale and use of software program which mixes personal competitor knowledge to set, suggest or advise on rents and occupancy ranges.”
Whether or not different jurisdictions comply with swimsuit stays to be seen. Within the meantime, an increasing number of corporations are determining methods to make use of algorithms to set costs. If these actually do allow de facto price-fixing, and handle to flee authorized scrutiny, the end result may very well be a form of pricing dystopia during which competitors to create higher merchandise and decrease costs would get replaced by coordination to maintain costs excessive and income flowing. That may imply completely greater prices for shoppers—like an inflation nightmare that by no means ends. Extra profound, it will undermine the incentives that hold economies rising and residing requirements rising. The fundamental premise of free-market capitalism is that costs are set by open competitors, not by a central planner. That goes for algorithmic central planners too.
