Distribution, Competition, and Antitrust / IP Law

Can Software Conspire?

English: The famous red eye of HAL 9000

The famous red eye of HAL 9000 (Photo credit: Wikipedia)

Philip K. Dick’s post-apocalyptic novel “Do Androids Dream of Electric Sheep” (the basis for the movie Blade Runner) asked whether robots can think and feel.  One of the hot topics du jour in antitrust is whether (software) robots can conspire and collude for purposes of the Sherman Act.  We’re in the very early days, so we must caveat every statement and preliminary conclusion, but just as robots can’t dream, there are reasons to believe that, at least in the short- to intermediate-term, they also cannot collude to violate the antitrust laws. (A couple years ago I did a related post on this issue: Can Computers Conspire to Fix Prices?.)

First, there is no empirical evidence that software has been able to (or could) learn to conspire.  Despite some recent hype about computer collusion, one recalls the adage that “artificial intelligence is always 10 years away.”  One of the few (if only) studies in this area – of the ability of computer algorithms to cooperate in the famous “Prisoner’s Dilemma” game – yielded mixed results.  It appears that the chance of creating algorithms that just happen to be good at colluding may be small.[1]

Let’s assume, however, that computer software develops faster than we otherwise would predict.  What are the risks that companies’ computers are going to be charged with price-fixing, or that companies will be held responsible for their doing so?

To answer this question, we should step back and methodically consider the various types of activities at issue here – because sometimes the discussions do not unpack the various distinct scenarios.  First, reference is often made to the 2015 DOJ case against Daniel William Aston and his company Trod Ltd. for allegedly fixing the prices of posters sold online via Amazon Marketplace.[2]  According to the DOJ, the conspirators agreed to adopt specific pricing algorithms for the sale of posters with the goal of offering online shoppers the same price for the same product and coordinating changes to their respective prices.  Importantly, although the alleged conspirators used algorithms, the alleged conspiracy involved an old-fashioned and very human meeting of the minds, and so the case doesn’t break new ground, any more than the first prosecutions of price-fixing conspiracies conducted over the telephone or via email did.

The second scenario involves employing algorithms as a business practice that can tend to facilitate collusion.  The concern here comes in one of two flavors.  First is the concern that simply having more data (about customers as well as competitors’ behavior) available for real-time analysis may facilitate collusion.  But this seems to be a question of degree, rather than kind, because firms already look at the same types of (and sometimes voluminous) data in making decisions about their pricing (input costs, buyer behavior, publicly-available information on competitors, etc.).   Second is the concern that competitors may use the exact same algorithms, which will result in parallel pricing, or make parallel pricing more likely, even if the algorithms do not communicate with each other.  That’s a possibility, although it is not clear that major competitors will buy the same off-the-shelf algorithms.  If they did, perhaps that could be a “plus factor” to be considered in combination with parallel pricing and the like to evaluate whether there is circumstantial evidence of an agreement.  However, using the same algorithm may be a relatively weak plus factor – after all, options traders have for decades used the same Black-Scholes formula to calculate options prices without any antitrust challenge.

The third scenario is the (for now) hypothetical one: two or more firms employ pricing algorithms that, without full human control, somehow communicate and ultimately conspire with each other.  This scenario also has two variants – a difficult case and an easy (or at least easier) case.  In the easier case – which may be the more likely one – although humans do not affirmatively program the algorithms to conspire, they can observe the results.  After all, it seems likely that for the foreseeable future humans will remain in the buying and selling loop even if computers set the prices.  And so, for example, if a computer does not lower prices when demand is down and supply is up, then arguably the humans may be on some sort of inquiry notice to figure out what is going on.  In at least certain of these cases, one can at least imagine a rule that holds the company responsible for setting the wheel in motion and knowingly turning a blind eye to the results.

In the difficult case, competitors’ algorithms communicate and conspire with each other, and somehow the results are sufficiently masked or cloaked so that no one is any the wiser.  Although this variant seems improbable, we may not be able to entirely rule it out a priori.  At the moment, with no case having presented these facts, the best one can probably say is that the competitors’ liability is not entirely certain.  Perhaps there also might be an argument that the software manufacturer should bear some sort of liability for its creation – although it is not at all clear that the language of the Sherman Act would support such liability.  Algorithms can make pricing more competitive, and we should be reluctant to adopt a rule that interferes with those pro-competitive efficiencies.

[1] Deng, Ai, When Machines Learn to Collude: Lessons from a Recent Research Study on Artificial Intelligence (August 30, 2017), available at SSRN: https://ssrn.com/abstract=3029662.

[2] See https://www.justice.gov/opa/pr/e-commerce-exec-and-online-retailer-charged-price-fixing-wall-posters (Dec. 4, 2015).  An earlier plea agreement regarding similar activity was reached with David Topkins.

Can Computers Conspire to Fix Prices?

English: The famous red eye of HAL 9000

The famous red eye of HAL 9000 (Photo credit: Wikipedia)

Strange as it sounds, maybe we’re getting closer to the day we have to seriously consider liability for computer conspiracies.

On April 6, David Topkins, a former executive of an e-commerce seller of posters, prints and framed art agreed to plead guilty for conspiring to fix the prices of posters sold online.  Given the ongoing DOJ investigation, details are sketchy, but according to the DOJ press release,

Topkins and his co-conspirators agreed to fix the prices of certain posters sold in the United States through Amazon Marketplace.  To implement their agreements, the defendant and his co-conspirators adopted specific pricing algorithms for the sale of certain posters with the goal of coordinating changes to their respective prices and wrote computer code that instructed algorithm-based software to set prices in conformity with this agreement.

 Apparently the computers weren’t completely in control — but what if they are?  According to a recent paper, that time may be coming:

The development of self-learning and independent computers has long captured our imagination. The HAL 9000 computer, in the 1968 film, 2001: A Space Odyssey, for example, assured, “I am putting myself to the fullest possible use, which is all I think that any conscious entity can ever hope to do.” Machine learning raises many challenging legal and ethical questions as to the relationship between man and machine, humans’ control — or lack of it — over machines, and accountability for machine activities.

While these issues have long captivated our interest, few would envision the day when these developments (and the legal and ethical challenges raised by them) would become an antitrust issue. Sophisticated computers are central to the competitiveness of present and future markets. With the accelerating development of AI, they are set to change the competitive landscape and the nature of competitive restraints. As pricing mechanisms shift to computer pricing algorithms, so too will the types of collusion. We are shifting from the world where executives expressly collude in smoke-filled hotel rooms to a world where pricing algorithms continually monitor and adjust to each other’s prices and market data.

Our paper addresses these developments and considers the application of competition law to an advanced ‘computerised trade environment.’ After discussing the way in which computerised technology is changing the competitive landscape, we explore four scenarios where AI can foster anticompetitive collusion and the legal and ethical challenges each scenario raises.

Ariel Ezrachi & Maurice E. Stucke, AI & Collusion (Apr. 8, 2015).

U.S. Criminal Antitrust Enforcement in 2012 Was Robust

The U.S. DOJ recently reported its 2012 enforcement statistics.  In FY 2012, the Antitrust Division recovered over $1.1 billion (yes, billion with a “b”) in criminal fines.  See here.  That figure does not include alternative penalties, disgorgement, and restitution — e.g., the more than $200 million secured for state and federal agencies in the municipal bonds investigation.  So all told, DOJ recovered over $1.3 billion in 2012.  This appears to be an all-time record (at the least, it’s the highest number since 2003).

The link above also reveals that the average prison sentence for individuals has been steadily increasing (up to 25 months for the 2010-2012 period). 

Interestingly, although total fines were at a record level, the number of criminal cases dropped — from 90 in 2011 to 67 in 2012.  But that appears to be statistical noise;  in most years since 2003, the number of cases has fluctuated between 32 and 72.

Two companies account for the lion’s share of the 2012 fines: Yazaki Corporation (auto parts) — $470 million, and AU Optronics (LCD screens) — $500 million.  Furukawa Electric Co. (automotive wire harnesses) was fined $200 million.   See here.

Price fixing is not cool.

What To Do With a DOJ Antitrust Subpoena

My article on the ten things to do if you ever receive a DOJ antitrust subpoena is now up over at InHouse Blog.

Archer Daniels Midland Price-Fixing Video from “Fair Fight in the Marketplace”

I recently stumbled upon this YouTube video from “Fair Fight in the Marketplace.”  This segment shows the real story of the Archer Daniels Midland (ADM) price-fixing case, the basis for the movie “The Informant!“, and includes excerpts from the actual FBI undercover footage of conspiracy meetings shot by Mark Whitacre, played by Matt Damon in the movie.

From the YouTube description: “Fair Fight in the Marketplace provides an engaging look at our antitrust laws that give protection to both American consumers and businesses. The half-hour program also considers a more fundamental question: can a set of regulations created by the Sherman Act at the end of the 19th century be relevant in todays era of digital technology and high-speed communications?

Hosted by NPR and Fox News commentator Mara Liasson, the program provides a short, colorful history of the antitrust laws in America and features three recent case studies.”

Archer Daniels Midland Segment from Fair Fight in the Marketplace

Much of the ADM conspiracy took place overseas.  In related news, the recently convicted AU Optronics Corp. executive apparently intends to appeal his conviction on the basis that, among other things, the Sherman Act doesn’t reach the foreign activity at issue in his case.  (Although he apparently will now file his appeal without former acting Solicitor General Neal Katyal.  Katyal was previously the lead counsel for the Guantanamo Bay detainees in the Supreme Court case Hamdan v. Rumsfeld, which held that military commissions set up by the Bush administration to try detainees at Guantanamo Bay violate both the UCMJ and the four Geneva Conventions, so he probably would have had some interesting things to say about extraterritoriality.)

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New Download Available — Ten Things To Do When Your Company Receives a DOJ Grand Jury Subpoena


I’ve posted a new file in the Downloads section — a short paper on “Ten Things To Do When Your Company Receives a DOJ Grand Jury Subpoena.”  This is a somewhat newer version of my “Nine Things To Do” article.  It covers many of the same basic points in a slightly more concise way.

If you haven’t checked out the Downloads section yet, now’s a good time to do so.  Just click the Downloads navigation button in the menu bar above.  Or you can click here.

Reminder: the DOJ Has Criminal Antitrust Enforcement Powers Beyond Price Fixing

On May 3, the U.S. DOJ announced that an executive of South Korean-based Hyosung Corporation agreed to plead guilty and to serve time in a U.S. prison for obstruction of justice charges in connection with an automated teller machine (ATM) merger investigation conducted by the Antitrust Division, the Department of Justice announced today.

According to a two-count felony charge filed in the U.S. District Court in Washington, D.C., Kyoungwon Pyo, in his role as senior vice president for corporate strategy of Hyosung Corporation, an affiliate of Nautilus Hyosung Holdings Inc. (NHI), altered and directed subordinates to alter numerous existing corporate documents before they were submitted to the Department of Justice and the Federal Trade Commission (FTC) in conjunction with mandatory premerger filings. The department said that Pyo’s actions took place in or about July and August 2008. At the time, the department was investigating Korea-based NHI’s proposed acquisition of Triton Systems of Delaware Inc. NHI abandoned the proposed acquisition of competitor Triton Systems before the Antitrust Division reached a decision determining whether to challenge the transaction.

After receiving the premerger filings, the Antitrust Division opened a civil merger investigation of the proposed acquisition. The department said that in or about August and September 2008, Pyo falsified additional documents in response to a document request from the Antitrust Division with the intention of impairing their integrity and availability for use in an official proceeding. The department said that, among other things, the alterations misrepresented and minimized the competitive impact of the proposed acquisition.

NHI was previously charged with obstruction of justice, which carries a maximum criminal fine for a corporation of $500,000 per count.  In October 2011, NHI pleaded guilty and paid a $200,000 criminal fine for its role in the obstruction of justice charges.  According to Pyo’s plea agreement, which is subject to court approval, Pyo has agreed to serve five months in prison.

Moral of the story: it is vitally important when dealing with the U.S. DOJ to maintain the utmost level of transparency and candor.

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