If you lease your private home, there’s a great probability your landlord makes use of RealPage to set your month-to-month fee. The corporate describes itself as merely serving to landlords set probably the most worthwhile value. However a collection of lawsuits says it’s one thing else: an AI-enabled price-fixing conspiracy.
The traditional picture of price-fixing entails the executives of rival firms gathering behind closed doorways and secretly agreeing to cost the identical inflated value for no matter they’re promoting. Any such collusion is without doubt one of the gravest sins you possibly can commit towards a free-market economic system; the late Justice Antonin Scalia as soon as referred to 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 effective.
However, because the RealPage instance suggests, expertise might supply a workaround. As a substitute of getting collectively along with your rivals and agreeing to not compete on value, you possibly can all independently depend on a 3rd social gathering to set your costs for you. Property house owners feed RealPage’s “property administration software program” their information, together with unit costs and emptiness charges, and the algorithm—which additionally is aware of what opponents are charging—spits out a lease suggestion. If sufficient landlords use it, the outcome might look the identical as a conventional price-fixing cartel: lockstep value will increase as a substitute of value competitors, no secret handshake or clandestine assembly wanted.
With out value competitors, companies lose their incentive to innovate and decrease prices, and customers get caught with excessive costs and no options. Algorithmic price-fixing seems to be spreading to increasingly more industries. And present legal guidelines might not be outfitted 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 value technique data from all of the individuals in a market after which inform everyone how they need to value?” 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 various lawsuits towards RealPage differ of their particulars, however all make the identical central argument: RealPage is Bob. In accordance with one estimate, in additional than 40 housing markets throughout the US, 30 to 60 % of multifamily-building items are priced utilizing RealPage. The plaintiffs suing RealPage, together with the Arizona and Washington, D.C., attorneys common, 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 an announcement, RealPage has responded that the share of landlords utilizing its providers is way decrease, about 7 % nationwide. RealPage’s estimate consists of all rental properties, whereas the lawsuits deal with multifamily-building items.)
In accordance with the lawsuits, RealPage’s shoppers act extra like collaborators than opponents. Landlords hand over extremely confidential data to RealPage, and plenty of of them recruit their rivals to make use of the service. “These sorts of behaviors increase a giant purple flag,” Maurice Stucke, a legislation professor on the College of Tennessee and a former antitrust lawyer on the Division of Justice, informed me. When firms are working in a extremely aggressive market, he stated, they usually go to nice lengths to guard any delicate data that might give their rivals an edge.
The lawsuits additionally argue that RealPage pressures landlords to adjust to its pricing solutions—one thing that will 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 considered one of RealPage’s fundamental software program instruments, acknowledged that one of many best threats to a landlord’s income is when close by properties set costs too low. “You probably have idiots undervaluing, it prices the entire system,” he stated. RealPage thus makes it onerous for purchasers to override its suggestions, in accordance with the lawsuits, allegedly even requiring a written justification and specific approval from RealPage employees. Former workers have stated that failure to adjust to the corporate’s suggestions might lead to shoppers being kicked off the service. “This, to me, is the most important giveaway,” Lee Hepner, an antitrust lawyer on the American Financial Liberties Challenge, an anti-monopoly group, informed me. “Enforced compliance is the hallmark characteristic of any cartel.”
The corporate disputes this description, claiming that it merely presents “bespoke pricing suggestions” and lacks “any energy” to set costs. “RealPage prospects make their very own pricing selections, and acceptance charges of RealPage’s pricing suggestions have been drastically exaggerated,” the corporate says.
In December, a Tennessee choose rejected RealPage’s movement to have a class-action lawsuit towards it dismissed, permitting the case to go ahead. It could be a mistake, nonetheless, to conclude from that instance that the authorized system has the algorithmic price-fixing drawback underneath management. RealPage might nonetheless prevail at trial, and in any case, it isn’t alone. Its fundamental competitor, Yardi, is concerned in an analogous lawsuit. One in every of RealPage’s subsidiaries, a service referred to as Rainmaker, faces a number of authorized challenges for allegedly facilitating price-fixing within the lodge business. (Yardi and Rainmaker deny wrongdoing.) Comparable complaints have been introduced towards firms in industries as various as medical health insurance, tire manufacturing, and meat processing. However successful these circumstances is proving troublesome.
The problem is that this: Below present antitrust legislation, displaying that firms A and B used algorithm C to boost costs isn’t sufficient; you have to present that there was some type of settlement between firms A and B, and you have to allege some particular factual foundation that the settlement existed earlier than you possibly can formally request proof of it. This dynamic can place plaintiffs in a catch-22: Plausibly alleging the existence of a price-fixing settlement is tough to do with out entry to proof like non-public emails, inner paperwork, or the algorithm itself. However they usually can’t uncover these sorts of supplies till they’re given the authorized energy to request proof in discovery. “It’s like making an attempt to suit a sq. peg in a spherical gap,” Richard Powers, a former deputy assistant lawyer common within the DOJ antitrust division, informed me. “It makes the job actually onerous.”
Within the case of RealPage, the plaintiffs had been in a position to make the peg match. However in Could, a Nevada choose dismissed an analogous case towards a gaggle of Las Vegas inns who used Rainmaker, concluding that there wasn’t sufficient proof of a price-fixing settlement, as a result of the inns concerned hadn’t shared confidential data 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 up to now have set the bar very excessive,” Kenneth Racowski, a litigation lawyer at Holland & Knight, informed me. The RealPage case “was in a position to clear that bar, but it surely may show to be the exception.”
And circumstances like RealPage and Rainmaker often is the simple ones. In a collection of papers, Stucke and his fellow antitrust scholar Ariel Ezrachi have outlined methods during which algorithms might repair costs that will be much more troublesome to stop or prosecute—together with conditions during which an algorithm learns to repair costs withouts its creators or customers intending it to. One thing comparable might happen even when firms used completely different third-party algorithms to set costs. They level to a current examine of German gasoline 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 informed me. “That might make it doable to repair costs at a scale that we’ve by no means seen.”
Not one of the conditions Stucke and Ezrachi describe contain an specific settlement, making them virtually inconceivable to prosecute underneath present antitrust legal guidelines. Worth-fixing, in different phrases, has entered the algorithmic age, however the legal guidelines designed to stop it haven’t stored up. Powers stated he believes present antitrust legal guidelines cowl algorithmic collusion—however he fearful that he may be fallacious. “That is the factor that stored me up at night time,” he stated about his tenure on the Division of Justice. “The fear that every one 100-plus years of case legislation on price-fixing might be circumvented by expertise.”
Earlier this yr, a handful of Senate Democrats led by Amy Klobuchar launched a invoice that will replace present legal guidelines to robotically presume a price-fixing settlement at any time when “opponents share competitively delicate data by means of a pricing algorithm to boost costs.” That invoice, like a lot congressional laws, is unlikely to change 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 private competitor information to set, suggest or advise on rents and occupancy ranges.”
Whether or not different jurisdictions comply with go well with stays to be seen. Within the meantime, increasingly more firms 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 outcome might be a type 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 might imply completely larger prices for customers—like an inflation nightmare that by no means ends. Extra profound, it will undermine the incentives that preserve economies rising and residing requirements rising. The essential premise of free-market capitalism is that costs are set by means of open competitors, not by a central planner. That goes for algorithmic central planners too.
