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The Networks of Control

When the keys to the online market are in the hands of the powerful few, is virtual competition truly open to all?
stucke edited
He was using his power to get sex. Photograph: Pascal Le Segretain/Getty Images

Are monopolies extinct in the data-driven economy?  Some argue yes. Pointing to the transformative powers of disruptive innovation, they reject concerns about monopolization. As Google’s chairman said, “the reason that you should trust us is that if we were to violate that trust people would move immediately to someone else.”[1] Barriers to entry are negligible, he noted, “because competition is just one click away.”[2]

Others disagree. While competitors may be a click away, competition is not. Digital giants may abuse their power, push out competitors, and exploit users. Illustrative is the EU Commission’s recently fining Google 2.4 billion Euros.[3] As a complainant in that case said: “For well over a decade, Google’s search engine has played a decisive role in determining what most of us read, use and purchase online. Left unchecked, there are few limits to this gatekeeper power. Google can deploy its insidious search manipulation practices to commandeer the lion’s share of traffic and revenues in virtually any online sector of its choosing, quietly crushing competition, innovation, and consumer choice in the process.”[4]

Should we worry about the digital giants?

One underlying dispute is over the ease in entering the data-driven markets.  If “competition is a click away” and entry is invariably easy, then monopolies are less of a concern.

Under the traditional antitrust factors, entry into the search engine market may seem easy, obviating the need for intervention. Search engines are free and easy to use. Users can switch easily among Google, Bing, Yahoo!, and DuckDuckGo. Seemingly users are not locked-in by any data portability issues. Thus, in chastising the U.S. Federal Trade Commission for even investigating Google for monopolization, one U.S. senator claimed that “[c]ompared to almost any other market in the history of antitrust regulation, online search has effectively zero barriers to entry.”[5]

But if entry were easy, Google could not behave like a monopoly (by intentionally degrading the quality of its search results in order to promote its own comparison shopping service). Moreover, Microsoft would not have spent over 4.5 billion dollars in developing its algorithms and building the physical capacity necessary to operate its search engine Bing.[6] 

So what is going on here?

One problem is that traditional antitrust analysis may not fully appreciate important entry barriers - namely data-driven network effects.  In a network environment where the winner takes it all, reality may be that “competition is for losers.”[7]

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"The implications go beyond our wallets. One concern is how economic power may translate to political power..."
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Network effects occur when our value of a product or service increases as others also use it.  As more people use a telephone, for example, the more people you can call, the more use you get from your phone.  These classic network effects are familiar in the brick-and-mortar economy. So, what’s new in the data-driven economy? The stakes are larger because the data-driven economy can amplify at least five, potentially interrelated, network effects:

  • First are the traditional direct network effects already familiar to courts and antitrust agencies. As more people use the social network, Facebook, for example, the more people with whom one can interact, the easier it is to connect with other people, and the greater one’s utility in using Facebook, and sharing data with others.

 

  • A second traditional, albeit indirect, network effect is the positive feedback loop in attracting manufacturers and developers. We already see this network effect for digital personal assistants. As more people use Amazon’s Alexa, for example, more manufacturers will make smart-products which the digital personal assistant can control, the more companies will develop new skills for Alexa (like ordering beer and pizza), and the more appealing Alexa becomes to prospective purchasers, which in turns attracts more manufacturers and software developers.

 

  • A third network effect involves learning-by-doing. We see this data-driven network effect with search engines. Each person’s utility from using the search engine increases as others use it too. As more people use the search engine, the more trial-and-error experiments, the more likely the search engine’s algorithm can learn consumers’ preferences, the more relevant the search results will likely be, which in turn will likely attract others to that search engine, and the positive feedback continues.

 

  • A fourth network effect involves the scope of personal data collected on us and predicting our unique needs. The leading platforms already expend a lot of effort to better track us, collect our personal data, and profile us. Here the feedback loop adds a dimension: it is no longer the learning-by-doing from earlier queries by billions of other users, but an additional layer of trial-and-error in predicting individual tastes and preferences from the variety of personal data the super-platform collects about you. 

 

  • The fifth network effect involves “spill-over effects.”  Here the concern is how network effects on the “free” (consumer) side can spill over to the “paid” (provider) side, and each side can reinforce the other. For instance, as more people are attracted to the platform’s services (like its search engine), the more advertisers will use the platform, the more relevant and targeted the advertisements, the likelier that users will click on the ads, and the more profits the platform has to expand its range of free services and to ensure that its existing services remain the default on various portals to the Internet.

 

The EU Commission, in its Google decision, found high entry barriers in the search engine market, in part because of these network effects.  These high entry barriers enabled Google to abuse its power. When entering the comparison shopping markets, Google knew that its shopping service was inferior.  (One internal Google document, for example, stated “Froogle simply doesn’t work.”) Instead of competing on the merits, Google “systematically” favored its own comparison shopping service in its search engine results, while demoting competing services. Google’s prominent placement of its own comparison shopping service resulted in more clicks and paved the way to its domination. “Even on a desktop,” the Commission noted, “the ten highest-ranking generic search results on page 1 together generally receive approximately 95% of all clicks on generic search results… The first result on page 2 of Google’s generic search results receives only about 1% of all clicks.”[8]

We do not claim that data-driven network effects always lead to monopolies, or may always facilitate abuse. Our point is that other courts and competition authorities, if they consider only the traditional entry barriers and traditional network effects, may be too lax when assessing mergers and monopolistic abuses. They will inflate the competitiveness of online markets, while discounting the power of data giants to exclude rivals with a better sales platform, search engine or social network, and block disruptive privacy innovations.

What should we do about it?

Big is not necessarily bad; enforcement should be deployed carefully so as to not chill competition and innovation. But, at the same time, we cannot uncritically assume that data-driven online markets necessarily self-correct. Nor can we assume that disruptive innovation will always safeguard our welfare. To put it differently - competition is not always a click away.

Importantly, the implications go beyond our wallets.  One concern in an economy dominated by a few powerful gatekeepers is how economic power may translate to political power – be it through payment by third parties or as a result of the platform itself opting to advance one agenda over another.[9]  The marketplace of ideas, just like online markets for goods and services, may be manipulated.

Officials, until recently, have not considered the greater social, political, and ethical concerns when a few data-opolies amass our personal data and influence the news many people receive and the entertainment they watch.  Antitrust, in its present form, cannot easily mitigate the privacy, consumer protection, and competition risks posed by the data giants. As our book Virtual Competition[10] discusses, we must explore revising or creating new legal safeguards to promote competition, privacy and our well-being in this new environment.  Otherwise, monopolies are not only possible, but in some in data-driven markets, given the network effects, very likely. The consequences are troubling: our welfare reduced, our economy can become even less inclusive, we can enjoy even less privacy, and our democracy and democratic ideals will diminish.



[1] Shane Richmond, ‘Google’s Eric Schmidt: You Can Trust Us with Your Data’, The Telegraph, 1 July 2010, http://www.telegraph.co.uk/technology/google/7864223/Googles-Eric-Schmidt-You-can-trust-us-with-your-data.html.

[2] Eric Schmidt, Executive Chairman of Google, ‘Why Google Works’, Huffington Post, 20 January 2015, http://www.huffingtonpost.com/eric-schmidt/why-google-works_b_6502132.html.

[3] EU Commission Press release: http://europa.eu/rapid/press-release_IP-17-1784_en.htm

[4] Natasha Lomas, ‘Google fined $2.7BN for EU antitrust violations over shopping searches’ TechCrunch, June 27, 2017, https://techcrunch.com/2017/06/27/google-fined-e2-42bn-for-eu-antitrust-violations-over-shopping-searches/

[6] ‘The FTC Report on Google’s Business Practices’, 8 August 2012, p 76, available at http://graphics.wsj.com/google-ftc-report/.

[7] Peter Thiel, ‘Competition Is for Losers’, Wall Street Journal, 12 September 2014.

[8] N 3 above.

[9]  Robert Pitofsky, “The Political Content of Antitrust”, 127 U. Pa. L. Rev. 1051 (1979).

[10] Ariel Ezrachi & Maurice E. Stucke, Virtual Competition: The Promise and Perils of the Algorithm-Driven Economy (HUP 2016).

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