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In March of this year, Elizabeth Warren announced her proposal to break up Big Tech in a blog post on Medium. She tried to paint the tech giants as dominant players crushing their smaller competitors and strangling the open internet. This line in particular stood out: “More than 70% of all Internet traffic goes through sites owned or operated by Google or Facebook.

This statistic immediately struck me as outlandish, but I knew I would need to do some digging to fact check it. After seeing the claim repeated in a recent profile of the Open Markets Institute — “Google and Facebook control websites that receive 70 percent of all internet traffic” — I decided to track down the original source for this surprising finding. 

Warren’s blog post links to a November 2017 Newsweek article — “Who Controls the Internet? Facebook and Google Dominance Could Cause the ‘Death of the Web’” — written by Anthony Cuthbertson. The piece is even more alarmist than Warren’s blog post: “Facebook and Google now have direct influence over nearly three quarters of all internet traffic, prompting warnings that the end of a free and open web is imminent.

The Newsweek article, in turn, cites an October 2017 blog post by André Staltz, an open source freelancer, on his personal website titled “The Web began dying in 2014, here’s how”. His takeaway is equally dire: “It looks like nothing changed since 2014, but GOOG and FB now have direct influence over 70%+ of internet traffic.” Staltz claims the blog post took “months of research to write”, but the headline statistic is merely aggregated from a December 2015 blog post by Parse.ly, a web analytics and content optimization software company.

Source: André Staltz

The Parse.ly article — “Facebook Continues to Beat Google in Sending Traffic to Top Publishers” — is about external referrals (i.e., outside links) to publisher sites (not total internet traffic) and says the “data set used for this study included around 400 publisher domains.” This is not even a random sample much less a comprehensive measure of total internet traffic. Here’s how they summarize their results: “Today, Facebook remains a top referring site to the publishers in Parse.ly’s network, claiming 39 percent of referral traffic versus Google’s share of 34 percent.” 

Source: Parse.ly

So, using the sources provided by the respective authors, the claim from Elizabeth Warren that “more than 70% of all Internet traffic goes through sites owned or operated by Google or Facebook” can be more accurately rewritten as “more than 70 percent of external links to 400 publishers come from sites owned or operated by Google and Facebook.” When framed that way, it’s much less conclusive (and much less scary).

But what’s the real statistic for total internet traffic? This is a surprisingly difficult question to answer, because there is no single way to measure it: Are we talking about share of users, or user-minutes, of bits, or total visits, or unique visits, or referrals? According to Wikipedia, “Common measurements of traffic are total volume, in units of multiples of the byte, or as transmission rates in bytes per certain time units.”

One of the more comprehensive efforts to answer this question is undertaken annually by Sandvine. The networking equipment company uses its vast installed footprint of equipment across the internet to generate statistics on connections, upstream traffic, downstream traffic, and total internet traffic (summarized in the table below). This dataset covers both browser-based and app-based internet traffic, which is crucial for capturing the full picture of internet user behavior.

Source: Sandvine

Looking at two categories of traffic analyzed by Sandvine — downstream traffic and overall traffic — gives lie to the narrative pushed by Warren and others. As you can see in the chart below, HTTP media streaming — a category for smaller streaming services that Sandvine has not yet tracked individually — represented 12.8% of global downstream traffic and Netflix accounted for 12.6%. According to Sandvine, “the aggregate volume of the long tail is actually greater than the largest of the short-tail providers.” So much for the open internet being smothered by the tech giants.

Source: Sandvine

As for Google and Facebook? The report found that Google-operated sites receive 12.00 percent of total internet traffic while Facebook-controlled sites receive 7.79 percent. In other words, less than 20 percent of all Internet traffic goes through sites owned or operated by Google or Facebook. While this statistic may be less eye-popping than the one trumpeted by Warren and other antitrust activists, it does have the virtue of being true.

Source: Sandvine

And if David finds out the data beneath his profile, you’ll start to be able to connect the dots in various ways with Facebook and Cambridge Analytica and Trump and Brexit and all these loosely-connected entities. Because you get to see inside the beast, you get to see inside the system.

This excerpt from the beginning of Netflix’s The Great Hack shows the goal of the documentary: to provide one easy explanation for Brexit and the election of Trump, two of the most surprising electoral outcomes in recent history.

Unfortunately, in attempting to tell a simple narrative, the documentary obscures more than it reveals about what actually happened in the Facebook-Cambridge Analytica data scandal. In the process, the film wildly overstates the significance of the scandal in either the 2016 US presidential election or the 2016 UK referendum on leaving the EU.

In this article, I will review the background of the case and show seven things the documentary gets wrong about the Facebook-Cambridge Analytica data scandal.

Background

In 2013, researchers published a paper showing that you could predict some personality traits — openness and extraversion — from an individual’s Facebook Likes. Cambridge Analytica wanted to use Facebook data to create a “psychographic” profile — i.e., personality type — of each voter and then micro-target them with political messages tailored to their personality type, ultimately with the hope of persuading them to vote for Cambridge Analytica’s client (or at least to not vote for the opposing candidate).

In this case, the psychographic profile is the person’s Big Five (or OCEAN) personality traits, which research has shown are relatively stable throughout our lives:

  1. Openness to new experiences
  2. Conscientiousness
  3. Extroversion
  4. Agreeableness
  5. Neuroticism

But how to get the Facebook data to create these profiles? A researcher at Cambridge University, Alex Kogan, created an app called thisismydigitallife, a short quiz for determining your personality type. Between 250,000 and 270,000 people were paid a small amount of money to take this quiz. 

Those who took the quiz shared some of their own Facebook data as well as their friends’ data (so long as the friends’ privacy settings allowed third-party app developers to access their data). 

This process captured data on “at least 30 million identifiable U.S. consumers”, according to the FTC. For context, even if we assume all 30 million were registered voters, that means the data could be used to create profiles for less than 20 percent of the relevant population. And though some may disagree with Facebook’s policy for sharing user data with third-party developers, collecting data in this manner was in compliance with Facebook’s terms of service at the time.

What crossed the line was what happened next. Kogan then sold that data to Cambridge Analytica, without the consent of the affected Facebook users and in express violation of Facebook’s prohibition on selling Facebook data between third and fourth parties. 

Upon learning of the sale, Facebook directed Alex Kogan and Cambridge Analytica to delete the data. But the social media company failed to notify users that their data had been misused or confirm via an independent audit that the data was actually deleted.

1. Cambridge Analytica was selling snake oil (no, you are not easily manipulated)

There’s a line in The Great Hack that sums up the opinion of the filmmakers and the subjects in their story: “There’s 2.1 billion people, each with their own reality. And once everybody has their own reality, it’s relatively easy to manipulate them.” According to the latest research from political science, this is completely bogus (and it’s the same marketing puffery that Cambridge Analytica would pitch to prospective clients).

The best evidence in this area comes from Joshua Kalla and David E. Broockman in a 2018 study published by American Political Science Review:

We argue that the best estimate of the effects of campaign contact and advertising on Americans’ candidates choices in general elections is zero. First, a systematic meta-analysis of 40 field experiments estimates an average effect of zero in general elections. Second, we present nine original field experiments that increase the statistical evidence in the literature about the persuasive effects of personal contact 10-fold. These experiments’ average effect is also zero.

In other words, a meta-analysis covering 49 high-quality field experiments found that in US general elections, advertising has zero effect on the outcome. (However, there is evidence “campaigns are able to have meaningful persuasive effects in primary and ballot measure campaigns, when partisan cues are not present.”)

But the relevant conclusion for the Cambridge Analytica scandal remains the same: in highly visible elections with a polarized electorate, it simply isn’t that easy to persuade voters to change their minds.

2. Micro-targeting political messages is overrated — people prefer general messages on shared beliefs

But maybe Cambridge Analytica’s micro-targeting strategy would result in above-average effects? The literature provides reason for skepticism here as well. Another paper by Eitan D. Hersh and Brian F. Schaffner in The Journal of Politics found that voters “rarely prefer targeted pandering to general messages” and “seem to prefer being solicited based on broad principles and collective beliefs.” It’s political tribalism all the way down. 

A field experiment with 56,000 Wisconsin voters in the 2008 US presidential election found that “persuasive appeals possibly reduced candidate support and almost certainly did not increase it,” suggesting that  “contact by a political campaign can engender a backlash.”

3. Big Five personality traits are not very useful for predicting political orientation

Or maybe there’s something special about targeting political messages based on a person’s Big Five personality traits? Again, there is little reason to believe this is the case. As Kris-Stella Trump mentions in an article for The Washington Post

The ‘Big 5’ personality traits … only predict about 5 percent of the variation in individuals’ political orientations. Even accurate personality data would only add very little useful information to a data set that includes people’s partisanship — which is what most campaigns already work with.

The best evidence we have on the importance of personality traits on decision-making comes from the marketing literature (n.b., it’s likely easier to influence consumer decisions than political decisions in today’s increasingly polarized electorate). Here too the evidence is weak:

In this successful study, researchers targeted ads, based on personality, to more than 1.5 million people; the result was about 100 additional purchases of beauty products than had they advertised without targeting.

More to the point, the Facebook data obtained by Cambridge Analytica couldn’t even accomplish the simple task of matching Facebook Likes to the Big Five personality traits. Here’s Cambridge University researcher Alex Kogan in Michael Lewis’s podcast episode about the scandal: 

We started asking the question of like, well, how often are we right? And so there’s five personality dimensions? And we said like, okay, for what percentage of people do we get all five personality categories correct? We found it was like 1%.

Eitan Hersh, an associate professor of political science at Tufts University, summed it up best: “Every claim about psychographics etc made by or about [Cambridge Analytica] is BS.

4. If Cambridge Analytica’s “weapons-grade communications techniques” were so powerful, then Ted Cruz would be president

The Great Hack:

Ted Cruz went from the lowest rated candidate in the primaries to being the last man standing before Trump got the nomination… Everyone said Ted Cruz had this amazing ground game, and now we know who came up with all of it. Joining me now, Alexander Nix, CEO of Cambridge Analytica, the company behind it all.

Reporting by Nicholas Confessore and Danny Hakim at The New York Times directly contradicts this framing on Cambridge Analytica’s role in the 2016 Republican presidential primary:

Cambridge’s psychographic models proved unreliable in the Cruz presidential campaign, according to Rick Tyler, a former Cruz aide, and another consultant involved in the campaign. In one early test, more than half the Oklahoma voters whom Cambridge had identified as Cruz supporters actually favored other candidates.

Most significantly, the Cruz campaign stopped using Cambridge Analytica’s services in February 2016 due to disappointing results, as Kenneth P. Vogel and Darren Samuelsohn reported in Politico in June of that year:

Cruz’s data operation, which was seen as the class of the GOP primary field, was disappointed in Cambridge Analytica’s services and stopped using them before the Nevada GOP caucuses in late February, according to a former staffer for the Texas Republican.

“There’s this idea that there’s a magic sauce of personality targeting that can overcome any issue, and the fact is that’s just not the case,” said the former staffer, adding that Cambridge “doesn’t have a level of understanding or experience that allows them to target American voters.”

Vogel later tweeted that most firms hired Cambridge Analytica “because it was seen as a prerequisite for receiving $$$ from the MERCERS.” So it seems campaigns hired Cambridge Analytica not for its “weapons-grade communications techniques” but for the firm’s connections to billionaire Robert Mercer.

5. The Trump campaign phased out Cambridge Analytica data in favor of RNC data for the general election

Just as the Cruz campaign became disillusioned after working with Cambridge Analytica during the primary, so too did the Trump campaign during the general election, as Major Garrett reported for CBS News:

The crucial decision was made in late September or early October when Mr. Trump’s son-in-law Jared Kushner and Brad Parscale, Mr. Trump’s digital guru on the 2016 campaign, decided to utilize just the RNC data for the general election and used nothing from that point from Cambridge Analytica or any other data vendor. The Trump campaign had tested the RNC data, and it proved to be vastly more accurate than Cambridge Analytica’s, and when it was clear the RNC would be a willing partner, Mr. Trump’s campaign was able to rely solely on the RNC.

And of the little work Cambridge Analytica did complete for the Trump campaign, none involved “psychographics,” The New York Times reported:

Mr. Bannon at one point agreed to expand the company’s role, according to the aides, authorizing Cambridge to oversee a $5 million purchase of television ads. But after some of them appeared on cable channels in Washington, D.C. — hardly an election battleground — Cambridge’s involvement in television targeting ended.

Trump aides … said Cambridge had played a relatively modest role, providing personnel who worked alongside other analytics vendors on some early digital advertising and using conventional micro-targeting techniques. Later in the campaign, Cambridge also helped set up Mr. Trump’s polling operation and build turnout models used to guide the candidate’s spending and travel schedule. None of those efforts involved psychographics.

6. There is no evidence that Facebook data was used in the Brexit referendum

Last year, the UK’s data protection authority fined Facebook £500,000 — the maximum penalty allowed under the law — for violations related to the Cambridge Analytica data scandal. The fine was astonishing considering that the investigation of Cambridge Analytica’s licensed data derived from Facebook “found no evidence that UK citizens were among them,” according to the BBC. This detail demolishes the second central claim of The Great Hack, that data fraudulently acquired from Facebook users enabled Cambridge Analytica to manipulate the British people into voting for Brexit. On this basis, Facebook is currently appealing the fine.

7. The Great Hack wasn’t a “hack” at all

The title of the film is an odd choice given the facts of the case, as detailed in the background section of this article. A “hack” is generally understood as an unauthorized breach of a computer system or network by a malicious actor. People think of a genius black hat programmer who overcomes a company’s cybersecurity defenses to profit off stolen data. Alex Kogan, the Cambridge University researcher who acquired the Facebook data for Cambridge Analytica, was nothing of the sort. 

As Gus Hurwitz noted in an article last year, Kogan entered into a contract with Facebook and asked users for their permission to acquire their data by using the thisismydigitallife personality app. Arguably, if there was a breach of trust, it was when the app users chose to share their friends’ data, too. The editorial choice to call this a “hack” instead of “data collection” or “data scraping” is of a piece with the rest of the film; when given a choice between accuracy and sensationalism, the directors generally chose the latter.

Why does this narrative persist despite the facts of the case?

The takeaway from the documentary is that Cambridge Analytica hacked Facebook and subsequently undermined two democratic processes: the Brexit referendum and the 2016 US presidential election. The reason this narrative has stuck in the public consciousness is that it serves everyone’s self-interest (except, of course, Facebook’s).

It lets voters off the hook for what seem, to many, to be drastic mistakes (i.e., electing a reality TV star president and undoing the European project). If we were all manipulated into making the “wrong” decision, then the consequences can’t be our fault! 

This narrative also serves Cambridge Analytica, to a point. For a time, the political consultant liked being able to tell prospective clients that it was the mastermind behind two stunning political upsets. Lastly, journalists like the story because they compete with Facebook in the advertising market and view the tech giant as an existential threat.

There is no evidence for the film’s implicit assumption that, but for Cambridge Analytica’s use of Facebook data to target voters, Trump wouldn’t have been elected and the UK wouldn’t have voted to leave the EU. Despite its tone and ominous presentation style, The Great Hack fails to muster any support for its extreme claims. The truth is much more mundane: the Facebook-Cambridge Analytica data scandal was neither a “hack” nor was it “great” in historical importance.

The documentary ends with a question:

But the hardest part in all of this is that these wreckage sites and crippling divisions begin with the manipulation of one individual. Then another. And another. So, I can’t help but ask myself: Can I be manipulated? Can you?

No — but the directors of The Great Hack tried their best to do so.

[This post is the seventh in an ongoing symposium on “Should We Break Up Big Tech?” that features analysis and opinion from various perspectives.]

[This post is authored by Alec Stapp, Research Fellow at the International Center for Law & Economics]

Should we break up Microsoft? 

In all the talk of breaking up “Big Tech,” no one seems to mention the biggest tech company of them all. Microsoft’s market cap is currently higher than those of Apple, Google, Amazon, and Facebook. If big is bad, then, at the moment, Microsoft is the worst.

Apart from size, antitrust activists also claim that the structure and behavior of the Big Four — Facebook, Google, Apple, and Amazon — is why they deserve to be broken up. But they never include Microsoft, which is curious given that most of their critiques also apply to the largest tech giant:

  1. Microsoft is big (current market cap exceeds $1 trillion)
  2. Microsoft is dominant in narrowly-defined markets (e.g., desktop operating systems)
  3. Microsoft is simultaneously operating and competing on a platform (i.e., the Microsoft Store)
  4. Microsoft is a conglomerate capable of leveraging dominance from one market into another (e.g., Windows, Office 365, Azure)
  5. Microsoft has its own “kill zone” for startups (196 acquisitions since 1994)
  6. Microsoft operates a search engine that preferences its own content over third-party content (i.e., Bing)
  7. Microsoft operates a platform that moderates user-generated content (i.e., LinkedIn)

To be clear, this is not to say that an antitrust case against Microsoft is as strong as the case against the others. Rather, it is to say that the cases against the Big Four on these dimensions are as weak as the case against Microsoft, as I will show below.

Big is bad

Tim Wu published a book last year arguing for more vigorous antitrust enforcement — including against Big Tech — called “The Curse of Bigness.” As you can tell by the title, he argues, in essence, for a return to the bygone era of “big is bad” presumptions. In his book, Wu mentions “Microsoft” 29 times, but only in the context of its 1990s antitrust case. On the other hand, Wu has explicitly called for antitrust investigations of Amazon, Facebook, and Google. It’s unclear why big should be considered bad when it comes to the latter group but not when it comes to Microsoft. Maybe bigness isn’t actually a curse, after all.

As the saying goes in antitrust, “Big is not bad; big behaving badly is bad.” This aphorism arose to counter erroneous reasoning during the era of structure-conduct-performance when big was presumed to mean bad. Thanks to an improved theoretical and empirical understanding of the nature of the competitive process, there is now a consensus that firms can grow large either via superior efficiency or by engaging in anticompetitive behavior. Size alone does not tell us how a firm grew big — so it is not a relevant metric.

Dominance in narrowly-defined markets

Critics of Google say it has a monopoly on search and critics of Facebook say it has a monopoly on social networking. Microsoft is similarly dominant in at least a few narrowly-defined markets, including desktop operating systems (Windows has a 78% market share globally): 

Source: StatCounter

Microsoft is also dominant in the “professional networking platform” market after its acquisition of LinkedIn in 2016. And the legacy tech giant is still the clear leader in the “paid productivity software” market. (Microsoft’s Office 365 revenue is roughly 10x Google’s G Suite revenue).

The problem here is obvious. These are overly-narrow market definitions for conducting an antitrust analysis. Is it true that Facebook’s platforms are the only service that can connect you with your friends? Should we really restrict the productivity market to “paid”-only options (as the EU similarly did in its Android decision) when there are so many free options available? These questions are laughable. Proper market definition requires considering whether a hypothetical monopolist could profitably impose a small but significant and non-transitory increase in price (SSNIP). If not (which is likely the case in the narrow markets above), then we should employ a broader market definition in each case.

Simultaneously operating and competing on a platform

Elizabeth Warren likes to say that if you own a platform, then you shouldn’t both be an umpire and have a team in the game. Let’s put aside the problems with that flawed analogy for now. What she means is that you shouldn’t both run the platform and sell products, services, or apps on that platform (because it’s inherently unfair to the other sellers). 

Warren’s solution to this “problem” would be to create a regulated class of businesses called “platform utilities” which are “companies with an annual global revenue of $25 billion or more and that offer to the public an online marketplace, an exchange, or a platform for connecting third parties.” Microsoft’s revenue last quarter was $32.5 billion, so it easily meets the first threshold. And Windows obviously qualifies as “a platform for connecting third parties.”

Just as in mobile operating systems, desktop operating systems are compatible with third-party applications. These third-party apps can be free (e.g., iTunes) or paid (e.g., Adobe Photoshop). Of course, Microsoft also makes apps for Windows (e.g., Word, PowerPoint, Excel, etc.). But the more you think about the technical details, the blurrier the line between the operating system and applications becomes. Is the browser an add-on to the OS or a part of it (as Microsoft Edge appears to be)? The most deeply-embedded applications in an OS are simply called “features.”

Even though Warren hasn’t explicitly mentioned that her plan would cover Microsoft, it almost certainly would. Previously, she left Apple out of the Medium post announcing her policy, only to later tell a journalist that the iPhone maker would also be prohibited from producing its own apps. But what Warren fails to include in her announcement that she would break up Apple is that trying to police the line between a first-party platform and third-party applications would be a nightmare for companies and regulators, likely leading to less innovation and higher prices for consumers (as they attempt to rebuild their previous bundles).

Leveraging dominance from one market into another

The core critique in Lina Khan’s “Amazon’s Antitrust Paradox” is that the very structure of Amazon itself is what leads to its anticompetitive behavior. Khan argues (in spite of the data) that Amazon uses profits in some lines of business to subsidize predatory pricing in other lines of businesses. Furthermore, she claims that Amazon uses data from its Amazon Web Services unit to spy on competitors and snuff them out before they become a threat.

Of course, this is similar to the theory of harm in Microsoft’s 1990s antitrust case, that the desktop giant was leveraging its monopoly from the operating system market into the browser market. Why don’t we hear the same concern today about Microsoft? Like both Amazon and Google, you could uncharitably describe Microsoft as extending its tentacles into as many sectors of the economy as possible. Here are some of the markets in which Microsoft competes (and note how the Big Four also compete in many of these same markets):

What these potential antitrust harms leave out are the clear consumer benefits from bundling and vertical integration. Microsoft’s relationships with customers in one market might make it the most efficient vendor in related — but separate — markets. It is unsurprising, for example, that Windows customers would also frequently be Office customers. Furthermore, the zero marginal cost nature of software makes it an ideal product for bundling, which redounds to the benefit of consumers.

The “kill zone” for startups

In a recent article for The New York Times, Tim Wu and Stuart A. Thompson criticize Facebook and Google for the number of acquisitions they have made. They point out that “Google has acquired at least 270 companies over nearly two decades” and “Facebook has acquired at least 92 companies since 2007”, arguing that allowing such a large number of acquisitions to occur is conclusive evidence of regulatory failure.

Microsoft has made 196 acquisitions since 1994, but they receive no mention in the NYT article (or in most of the discussion around supposed “kill zones”). But the acquisitions by Microsoft or Facebook or Google are, in general, not problematic. They provide a crucial channel for liquidity in the venture capital and startup communities (the other channel being IPOs). According to the latest data from Orrick and Crunchbase, between 2010 and 2018, there were 21,844 acquisitions of tech startups for a total deal value of $1.193 trillion

By comparison, according to data compiled by Jay R. Ritter, a professor at the University of Florida, there were 331 tech IPOs for a total market capitalization of $649.6 billion over the same period. Making it harder for a startup to be acquired would not result in more venture capital investment (and therefore not in more IPOs), according to recent research by Gordon M. Phillips and Alexei Zhdanov. The researchers show that “the passage of a pro-takeover law in a country is associated with more subsequent VC deals in that country, while the enactment of a business combination antitakeover law in the U.S. has a negative effect on subsequent VC investment.”

As investor and serial entrepreneur Leonard Speiser said recently, “If the DOJ starts going after tech companies for making acquisitions, venture investors will be much less likely to invest in new startups, thereby reducing competition in a far more harmful way.” 

Search engine bias

Google is often accused of biasing its search results to favor its own products and services. The argument goes that if we broke them up, a thousand search engines would bloom and competition among them would lead to less-biased search results. While it is a very difficult — if not impossible — empirical question to determine what a “neutral” search engine would return, one attempt by Josh Wright found that “own-content bias is actually an infrequent phenomenon, and Google references its own content more favorably than other search engines far less frequently than does Bing.” 

The report goes on to note that “Google references own content in its first results position when no other engine does in just 6.7% of queries; Bing does so over twice as often (14.3%).” Arguably, users of a particular search engine might be more interested in seeing content from that company because they have a preexisting relationship. But regardless of how we interpret these results, it’s clear this not a frequent phenomenon.

So why is Microsoft being left out of the antitrust debate now?

One potential reason why Google, Facebook, and Amazon have been singled out for criticism of practices that seem common in the tech industry (and are often pro-consumer) may be due to the prevailing business model in the journalism industry. Google and Facebook are by far the largest competitors in the digital advertising market, and Amazon is expected to be the third-largest player by next year, according to eMarketer. As Ramsi Woodcock pointed out, news publications are also competing for advertising dollars, the type of conflict of interest that usually would warrant disclosure if, say, a journalist held stock in a company they were covering.

Or perhaps Microsoft has successfully avoided receiving the same level of antitrust scrutiny as the Big Four because it is neither primarily consumer-facing like Apple or Amazon nor does it operate a platform with a significant amount of political speech via user-generated content (UGC) like Facebook or Google (YouTube). Yes, Microsoft moderates content on LinkedIn, but the public does not get outraged when deplatforming merely prevents someone from spamming their colleagues with requests “to add you to my professional network.”

Microsoft’s core areas are in the enterprise market, which allows it to sidestep the current debates about the supposed censorship of conservatives or unfair platform competition. To be clear, consumer-facing companies or platforms with user-generated content do not uniquely merit antitrust scrutiny. On the contrary, the benefits to consumers from these platforms are manifest. If this theory about why Microsoft has escaped scrutiny is correct, it means the public discussion thus far about Big Tech and antitrust has been driven by perception, not substance.


[This post is the sixth in an ongoing symposium on “Should We Break Up Big Tech?” that features analysis and opinion from various perspectives.]

[This post is authored by Thibault Schrepel, Faculty Associate at the Berkman Center at Harvard University and Assistant Professor in European Economic Law at Utrecht University School of Law.]

The pretense of ignorance

Over the last few years, I have published a series of antitrust conversations with Nobel laureates in economics. I have discussed big tech dominance with most of them, and although they have different perspectives, all of them agreed on one thing: they do not know what the effect of breaking up big tech would be. In fact, I have never spoken with any economist who was able to show me convincing empirical evidence that breaking up big tech would on net be good for consumers. The same goes for political scientists; I have never read any article that, taking everything into consideration, proves empirically that breaking up tech companies would be good for protecting democracies, if that is the objective (please note that I am not even discussing the fact that using antitrust law to do that would violate the rule of law, for more on the subject, click here).

This reminds me of Friedrich Hayek’s Nobel memorial lecture, in which he discussed the “pretense of knowledge.” He argued that some issues will always remain too complex for humans (even helped by quantum computers and the most advanced AI; that’s right!). Breaking up big tech is one such issue; it is simply impossible simultaneously to consider the micro and macro-economic impacts of such an enormous undertaking, which would affect, literally, billions of people. Not to mention the political, sociological and legal issues, all of which combined are beyond human understanding.

Ignorance + fear = fame

In the absence of clear-cut conclusions, here is why (I think), some officials are arguing for breaking up big tech. First, it may be possible that some of them actually believe that it would be great. But I am sure we agree that beliefs should not be a valid basis for such actions. More realistically, the answer can be found in the work of another Nobel laureate, James Buchanan, and in particular his 1978 lecture in Vienna entitled “Politics Without Romance.”

In his lecture and the paper that emerged from it, Buchanan argued that while markets fail, so do governments. The latter is especially relevant insofar as top officials entrusted with public power may, occasionally at least, use that power to benefit their personal interests rather than the public interest. Thus, the presumption that government-imposed corrections for market failures always accomplish the desired objectives must be rejected. Taking that into consideration, it follows that the expected effectiveness of public action should always be established as precisely and scientifically as possible before taking action. Integrating these insights from Hayek and Buchanan, we must conclude that it is not possible to know whether the effects of breaking up big tech would on net be positive.

The question then is why, in the absence of positive empirical evidence, are some officials arguing for breaking up tech giants then? Well, because defending such actions may help them achieve their personal goals. Often, it is more important for public officials to show their muscle and take action, rather showing great care about reaching a positive net result for society. This is especially true when it is practically impossible to evaluate the outcome due to the scale and complexity of the changes that ensue. That enables these officials to take credit for being bold while avoiding blame for the harms.

But for such a call to be profitable for the public officials, they first must legitimize the potential action in the eyes of the majority of the public. Until now, most consumers evidently like the services of tech giants, which is why it is crucial for the top officials engaged in such a strategy to demonize those companies and further explain to consumers why they are wrong to enjoy them. Only then does defending the breakup of tech giants becomes politically valuable.

Some data, one trend

In a recent paper entitled “Antitrust Without Romance,” I have analyzed the speeches of the five current FTC commissioners, as well as the speeches of the current and three previous EU Competition Commissioners. What I found is an increasing trend to demonize big tech companies. In other words, public officials increasingly seek to prepare the general public for the idea that breaking up tech giants would be great.

In Europe, current Competition Commissioner Margrethe Vestager has sought to establish an opposition between the people (referred under the pronoun “us”) and tech companies (referred under the pronoun “them”) in more than 80% of her speeches. She further describes these companies as engaging in manipulation of the public and unleashing violence. She says they, “distort or fabricate information, manipulate people’s views and degrade public debate” and help “harmful, untrue information spread faster than ever, unleashing violence and undermining democracy.” Furthermore, she says they cause, “danger of death.” On this basis, she mentions the possibility of breaking them up (for more data about her speeches, see this link).

In the US, we did not observe a similar trend. Assistant Attorney General Makan Delrahim, who has responsibility for antitrust enforcement at the Department of Justice, describes the relationship between people and companies as being in opposition in fewer than 10% of his speeches. The same goes for most of the FTC commissioners (to see all the data about their speeches, see this link). The exceptions are FTC Chairman Joseph J. Simons, who describes companies’ behavior as “bad” from time to time (and underlines that consumers “deserve” better) and Commissioner Rohit Chopra, who describes the relationship between companies and the people as being in opposition to one another in 30% of his speeches. Chopra also frequently labels companies as “bad.” These are minor signs of big tech demonization compared to what is currently done by European officials. But, unfortunately, part of the US doctrine (which does not hide political objectives) pushes for demonizing big tech companies. One may have reason to fear that such a trend will grow in the US as it has in Europe, especially considering the upcoming presidential campaign in which far-right and far-left politicians seem to agree about the need to break up big tech.

And yet, let’s remember that no-one has any documented, tangible, and reproducible evidence that breaking up tech giants would be good for consumers, or societies at large, or, in fact, for anyone (even dolphins, okay). It might be a good idea; it might be a bad idea. Who knows? But the lack of evidence either way militates against taking such action. Meanwhile, there is strong evidence that these discussions are fueled by a handful of individuals wishing to benefit from such a call for action. They do so, first, by depicting tech giants as representing the new elite in opposition to the people and they then portray themselves as the only saviors capable of taking action.

Epilogue: who knows, life is not a Tarantino movie

For the last 30 years, antitrust law has been largely immune to strategic takeover by political interests. It may now be returning to a previous era in which it was the instrument of a few. This transformation is already happening in Europe (it is expected to hit case law there quite soon) and is getting real in the US, where groups display political goals and make antitrust law a Trojan horse for their personal interests.The only semblance of evidence they bring is a few allegedly harmful micro-practices (see Amazon’s Antitrust Paradox), which they use as a basis for defending the urgent need of macro, structural measures, such as breaking up tech companies. This is disproportionate, but most of all and in the absence of better knowledge, purely opportunistic and potentially foolish. Who knows at this point whether antitrust law will come out intact of this populist and moralist episode? And who knows what the next idea of those who want to use antitrust law for purely political purposes will be. Life is not a Tarantino movie; it may end up badly.

[This post is the fifth in an ongoing symposium on “Should We Break Up Big Tech?” that features analysis and opinion from various perspectives.]

[This post is authored by William Rinehart, Director of Technology and Innovation Policy at American Action Forum.]

Back in May, the New York Times published an op-ed by Chris Hughes, one of the founders of Facebook, in which he called for the break up of his former firm. Hughes joins a growing chorus, including Senator Warren, Roger McNamee and others who have called for the break up of “Big Tech” companies. If Business Insider’s polling is correct, this chorus seems to be quite effective: Nearly 40 percent of Americans now support breaking up Facebook. 

Hughes’ position is perhaps understandable given his other advocacy activities. But it is also worth bearing in mind that he likely was never particularly familiar with or involved in Facebook’s technical backend or business development or sales. Rather, he was important in setting up the public relations and feedback mechanisms. This is relevant because the technical and organizational challenges in breaking up big tech are enormous and underappreciated. 

The Technics of Structural Remedies

As I explained at AAF last year,

Any trust-busting action would also require breaking up the company’s technology stack — a general name for the suite of technologies powering web sites. For example, Facebook developed its technology stack in-house to address the unique problems facing Facebook’s vast troves of data. Facebook created BigPipe to dynamically serve pages faster, Haystack to store billions of photos efficiently, Unicorn for searching the social graph, TAO for storing graph information, Peregrine for querying, and MysteryMachine to help with end-to-end performance analysis. The company also invested billions in data centers to quickly deliver video, and it split the cost of an undersea cable with Microsoft to speed up information travel. Where do you cut these technologies when splitting up the company?

That list, however, leaves out the company’s backend AI platform, known as Horizon. As Christopher Mims reported in the Wall Street Journal, Facebook put serious resources into creating Horizon and it has paid off. About a fourth of the engineers at the company were using this platform in 2017, even though only 30 percent of them were experts in it. The system, as Joaquin Candela explained, is powerful because it was built to be “a very modular layered cake where you can plug in at any level you want.” As Mim was careful to explain, the platform was designed to be “domain-specific,”  or highly modular. In other words, Horizon was meant to be useful across a range of complex problems and different domains. If WhatsApp and Instagram were separated from Facebook, who gets that asset? Does Facebook retain the core tech and then have to sell it at a regulated rate?

Lessons from Attempts to Manage Competition in the Tobacco Industry 

For all of the talk about breaking up Facebook and other tech companies, few really grasp just how lackluster this remedy has been in the past. The classic case to study isn’t AT&T or Standard Oil, but American Tobacco Company

The American Tobacco Company came about after a series of mergers in 1890 orchestrated by J.B. Duke. Then, between 1907 and 1911, the federal government filed and eventually won an antitrust lawsuit, which dissolved the trust into three companies. 

Duke was unique for his time because he worked to merge all of the previous companies into a working coherent firm. The organization that stood trial in 1907 was a modern company, organized around a functional structure. A single purchasing department managed all the leaf purchasing. Tobacco processing plants were dedicated to specific products without any concern for their previous ownership. The American Tobacco Company was rational in a way few other companies were at the time.  

These divisions were pulled apart over eight months. Factories, distribution and storage facilities, back offices and name brands were all separated by government fiat. It was a difficult task. As historian Allan M. Brandt details in “The Cigarette Century,”

It was one thing to identify monopolistic practices and activities in restraint of trade, and quite another to figure out how to return the tobacco industry to some form of regulated competition. Even those who applauded the breakup of American Tobacco soon found themselves critics of the negotiated decree restructuring the industry. This would not be the last time that the tobacco industry would successfully turn a regulatory intervention to its own advantage.

So how did consumers fare after the breakup? Most research suggests that the breakup didn’t substantially change the markets where American Tobacco was involved. Real cigarette prices for consumers were stable, suggesting there wasn’t price competition. The three companies coming out of the suit earned the same profit from 1912 to 1949 as the original American Tobacco Company Trust earned in its heyday from 1898 to 1908. As for the upstream suppliers, the price paid to tobacco farmers didn’t change either. The breakup was a bust.  

The difficulties in breaking up American Tobacco stand in contrast to the methods employed with Standard Oil and AT&T. For them, the split was made along geographic lines. Standard Oil was broken into 34 regional companies. Standard Oil of New Jersey became Exxon, while Standard Oil of California changed its name to Chevron. In the same way, AT&T was broken up in Regional Bell Operating Companies. Facebook doesn’t have geographic lines.

The Lessons of the Past Applied to Facebook

Facebook combines elements of the two primary firm structures and is thus considered a “matrix form” company. While the American Tobacco Company employed a functional organization, the most common form of company organization today is the divisional form. This method of firm rationalization separates the company’s operational functions by product, in order to optimize efficiencies. Under a divisional structure, each product is essentially a company unto itself. Engineering, finance, sales, and customer service are all unified within one division, which sits separate from other divisions within a company. Like countless other tech companies, Facebook merges elements of the two forms. It relies upon flexible teams to solve problems that tend to cross the normal divisional and functional bounds. Communication and coordination is prioritized among teams and Facebook invests heavily to ensure cross-company collaboration. 

Advocates think that undoing the WhatsApp and Instagram mergers will be easy, but there aren’t clean divisional lines within the company. Indeed, Facebook has been working towards a vast reengineering of its backend for some time that, when completed later this year or early 2020, will effectively merge all of the companies into one ecosystem.  Attempting to dismember this ecosystem would almost certainly be disastrous; not just a legal nightmare, but a technical and organizational nightmare as well.

Much like American Tobacco, any attempt to split off WhatsApp and Instagram from Facebook will probably fall flat on its face because government officials will have to create three regulated firms, each with essentially duplicative structures. As a result, the quality of services offered to consumers will likely be inferior to those available from the integrated firm. In other words, this would be a net loss to consumers.

Source: Benedict Evans

[N]ew combinations are, as a rule, embodied, as it were, in new firms which generally do not arise out of the old ones but start producing beside them; … in general it is not the owner of stagecoaches who builds railways. – Joseph Schumpeter, January 1934

Elizabeth Warren wants to break up the tech giants — Facebook, Google, Amazon, and Apple — claiming they have too much power and represent a danger to our democracy. As part of our response to her proposal, we shared a couple of headlines from 2007 claiming that MySpace had an unassailable monopoly in the social media market.

Tommaso Valletti, the chief economist of the Directorate-General for Competition (DG COMP) of the European Commission, said, in what we assume was a reference to our posts, “they go on and on with that single example to claim that [Facebook] and [Google] are not a problem 15 years later … That’s not what I would call an empirical regularity.”

We appreciate the invitation to show that prematurely dubbing companies “unassailable monopolies” is indeed an empirical regularity.

It’s Tough to Make Predictions, Especially About the Future of Competition in Tech

No one is immune to this phenomenon. Antitrust regulators often take a static view of competition, failing to anticipate dynamic technological forces that will upend market structure and competition.

Scientists and academics make a different kind of error. They are driven by the need to satisfy their curiosity rather than shareholders. Upon inventing a new technology or discovering a new scientific truth, academics often fail to see the commercial implications of their findings.

Maybe the titans of industry don’t make these kinds of mistakes because they have skin in the game? The profit and loss statement is certainly a merciless master. But it does not give CEOs the power of premonition. Corporate executives hailed as visionaries in one era often become blinded by their success, failing to see impending threats to their company’s core value propositions.

Furthermore, it’s often hard as outside observers to tell after the fact whether business leaders just didn’t see a tidal wave of disruption coming or, worse, they did see it coming and were unable to steer their bureaucratic, slow-moving ships to safety. Either way, the outcome is the same.

Here’s the pattern we observe over and over: extreme success in one context makes it difficult to predict how and when the next paradigm shift will occur in the market. Incumbents become less innovative as they get lulled into stagnation by high profit margins in established lines of business. (This is essentially the thesis of Clay Christensen’s The Innovator’s Dilemma).

Even if the anti-tech populists are powerless to make predictions, history does offer us some guidance about the future. We have seen time and again that apparently unassailable monopolists are quite effectively assailed by technological forces beyond their control.

PCs

Source: Horace Dediu

Jan 1977: Commodore PET released

Jun 1977: Apple II released

Aug 1977: TRS-80 released

Feb 1978: “I.B.M. Says F.T.C. Has Ended Its Typewriter Monopoly Study” (NYT)

Mobile

Source: Comscore

Mar 2000: Palm Pilot IPO’s at $53 billion

Sep 2006: “Everyone’s always asking me when Apple will come out with a cellphone. My answer is, ‘Probably never.’” – David Pogue (NYT)

Apr 2007: “There’s no chance that the iPhone is going to get any significant market share.” Ballmer (USA TODAY)

Jun 2007: iPhone released

Nov 2007: “Nokia: One Billion Customers—Can Anyone Catch the Cell Phone King?” (Forbes)

Sep 2013: “Microsoft CEO Ballmer Bids Emotional Farewell to Wall Street” (Reuters)

If there’s one thing I regret, there was a period in the early 2000s when we were so focused on what we had to do around Windows that we weren’t able to redeploy talent to the new device form factor called the phone.

Search

Source: Distilled

Mar 1998: “How Yahoo! Won the Search Wars” (Fortune)

Once upon a time, Yahoo! was an Internet search site with mediocre technology. Now it has a market cap of $2.8 billion. Some people say it’s the next America Online.

Sep 1998: Google founded

Instant Messaging

Sep 2000: “AOL Quietly Linking AIM, ICQ” (ZDNet)

AOL’s dominance of instant messaging technology, the kind of real-time e-mail that also lets users know when others are online, has emerged as a major concern of regulators scrutinizing the company’s planned merger with Time Warner Inc. (twx). Competitors to Instant Messenger, such as Microsoft Corp. (msft) and Yahoo! Inc. (yhoo), have been pressing the Federal Communications Commission to force AOL to make its services compatible with competitors’.

Dec 2000: “AOL’s Instant Messaging Monopoly?” (Wired)

Dec 2015: Report for the European Parliament

There have been isolated examples, as in the case of obligations of the merged AOL / Time Warner to make AOL Instant Messenger interoperable with competing messaging services. These obligations on AOL are widely viewed as having been a dismal failure.

Oct 2017: AOL shuts down AIM

Jan 2019: “Zuckerberg Plans to Integrate WhatsApp, Instagram and Facebook Messenger” (NYT)

Retail

Source: Seeking Alpha

May 1997: Amazon IPO

Mar 1998: American Booksellers Association files antitrust suit against Borders, B&N

Feb 2005: Amazon Prime launches

Jul 2006: “Breaking the Chain: The Antitrust Case Against Wal-Mart” (Harper’s)

Feb 2011: “Borders Files for Bankruptcy” (NYT)

Social

Feb 2004: Facebook founded

Jan 2007: “MySpace Is a Natural Monopoly” (TechNewsWorld)

Seventy percent of Yahoo 360 users, for example, also use other social networking sites — MySpace in particular. Ditto for Facebook, Windows Live Spaces and Friendster … This presents an obvious, long-term business challenge to the competitors. If they cannot build up a large base of unique users, they will always be on MySpace’s periphery.

Feb 2007: “Will Myspace Ever Lose Its Monopoly?” (Guardian)

Jun 2011: “Myspace Sold for $35m in Spectacular Fall from $12bn Heyday” (Guardian)

Music

Source: RIAA

Dec 2003: “The subscription model of buying music is bankrupt. I think you could make available the Second Coming in a subscription model, and it might not be successful.” – Steve Jobs (Rolling Stone)

Apr 2006: Spotify founded

Jul 2009: “Apple’s iPhone and iPod Monopolies Must Go” (PC World)

Jun 2015: Apple Music announced

Video

Source: OnlineMBAPrograms

Apr 2003: Netflix reaches one million subscribers for its DVD-by-mail service

Mar 2005: FTC blocks Blockbuster/Hollywood Video merger

Sep 2006: Amazon launches Prime Video

Jan 2007: Netflix streaming launches

Oct 2007: Hulu launches

May 2010: Hollywood Video’s parent company files for bankruptcy

Sep 2010: Blockbuster files for bankruptcy

The Only Winning Move Is Not to Play

Predicting the future of competition in the tech industry is such a fraught endeavor that even articles about how hard it is to make predictions include incorrect predictions. The authors just cannot help themselves. A March 2012 BBC article “The Future of Technology… Who Knows?” derided the naysayers who predicted doom for Apple’s retail store strategy. Its kicker?

And that is why when you read that the Blackberry is doomed, or that Microsoft will never make an impression on mobile phones, or that Apple will soon dominate the connected TV market, you need to take it all with a pinch of salt.

But Blackberry was doomed and Microsoft never made an impression on mobile phones. (Half credit for Apple TV, which currently has a 15% market share).

Nobel Prize-winning economist Paul Krugman wrote a piece for Red Herring magazine (seriously) in June 1998 with the title “Why most economists’ predictions are wrong.” Headline-be-damned, near the end of the article he made the following prediction:

The growth of the Internet will slow drastically, as the flaw in “Metcalfe’s law”—which states that the number of potential connections in a network is proportional to the square of the number of participants—becomes apparent: most people have nothing to say to each other! By 2005 or so, it will become clear that the Internet’s impact on the economy has been no greater than the fax machine’s.

Robert Metcalfe himself predicted in a 1995 column that the Internet would “go spectacularly supernova and in 1996 catastrophically collapse.” After pledging to “eat his words” if the prediction did not come true, “in front of an audience, he put that particular column into a blender, poured in some water, and proceeded to eat the resulting frappe with a spoon.”

A Change Is Gonna Come

Benedict Evans, a venture capitalist at Andreessen Horowitz, has the best summary of why competition in tech is especially difficult to predict:

IBM, Microsoft and Nokia were not beaten by companies doing what they did, but better. They were beaten by companies that moved the playing field and made their core competitive assets irrelevant. The same will apply to Facebook (and Google, Amazon and Apple).

Elsewhere, Evans tried to reassure his audience that we will not be stuck with the current crop of tech giants forever:

With each cycle in tech, companies find ways to build a moat and make a monopoly. Then people look at the moat and think it’s invulnerable. They’re generally right. IBM still dominates mainframes and Microsoft still dominates PC operating systems and productivity software. But… It’s not that someone works out how to cross the moat. It’s that the castle becomes irrelevant. IBM didn’t lose mainframes and Microsoft didn’t lose PC operating systems. Instead, those stopped being ways to dominate tech. PCs made IBM just another big tech company. Mobile and the web made Microsoft just another big tech company. This will happen to Google or Amazon as well. Unless you think tech progress is over and there’ll be no more cycles … It is deeply counter-intuitive to say ‘something we cannot predict is certain to happen’. But this is nonetheless what’s happened to overturn pretty much every tech monopoly so far.

If this time is different — or if there are more false negatives than false positives in the monopoly prediction game — then the advocates for breaking up Big Tech should try to make that argument instead of falling back on “big is bad” rhetoric. As for us, we’ll bet that we have not yet reached the end of history — tech progress is far from over.

 

Near the end of her new proposal to break up Facebook, Google, Amazon, and Apple, Senator Warren asks, “So what would the Internet look like after all these reforms?”

It’s a good question, because, as she herself notes, “Twenty-five years ago, Facebook, Google, and Amazon didn’t exist. Now they are among the most valuable and well-known companies in the world.”

To Warren, our most dynamic and innovative companies constitute a problem that needs solving.

She described the details of that solution in a blog post:

First, [my administration would restore competition to the tech sector] by passing legislation that requires large tech platforms to be designated as “Platform Utilities” and broken apart from any participant on that platform.

* * *

For smaller companies…, their platform utilities would be required to meet the same standard of fair, reasonable, and nondiscriminatory dealing with users, but would not be required to structurally separate….

* * *
Second, my administration would appoint regulators committed to reversing illegal and anti-competitive tech mergers….
I will appoint regulators who are committed to… unwind[ing] anti-competitive mergers, including:

– Amazon: Whole Foods; Zappos;
– Facebook: WhatsApp; Instagram;
– Google: Waze; Nest; DoubleClick

Elizabeth Warren’s brave new world

Let’s consider for a moment what this brave new world will look like — not the nirvana imagined by regulators and legislators who believe that decimating a company’s business model will deter only the “bad” aspects of the model while preserving the “good,” as if by magic, but the inevitable reality of antitrust populism.  

Utilities? Are you kidding? For an overview of what the future of tech would look like under Warren’s “Platform Utility” policy, take a look at your water, electricity, and sewage service. Have you noticed any improvement (or reduction in cost) in those services over the past 10 or 15 years? How about the roads? Amtrak? Platform businesses operating under a similar regulatory regime would also similarly stagnate. Enforcing platform “neutrality” necessarily requires meddling in the most minute of business decisions, inevitably creating unintended and costly consequences along the way.

Network companies, like all businesses, differentiate themselves by offering unique bundles of services to customers. By definition, this means vertically integrating with some product markets and not others. Why are digital assistants like Siri bundled into mobile operating systems? Why aren’t the vast majority of third-party apps also bundled into the OS? If you want utilities regulators instead of Google or Apple engineers and designers making these decisions on the margin, then Warren’s “Platform Utility” policy is the way to go.

Grocery Stores. To take one specific case cited by Warren, how much innovation was there in the grocery store industry before Amazon bought Whole Foods? Since the acquisition, large grocery retailers, like Walmart and Kroger, have increased their investment in online services to better compete with the e-commerce champion. Many industry analysts expect grocery stores to use computer vision technology and artificial intelligence to improve the efficiency of check-out in the near future.

Smartphones. Imagine how forced neutrality would play out in the context of iPhones. If Apple can’t sell its own apps, it also can’t pre-install its own apps. A brand new iPhone with no apps — and even more importantly, no App Store — would be, well, just a phone, out of the box. How would users even access a site or app store from which to download independent apps? Would Apple be allowed to pre-install someone else’s apps? That’s discriminatory, too. Maybe it will be forced to offer a menu of all available apps in all categories (like the famously useless browser ballot screen demanded by the European Commission in its Microsoft antitrust case)? It’s hard to see how that benefits consumers — or even app developers.

Source: Free Software Magazine

Internet Search. Or take search. Calls for “search neutrality” have been bandied about for years. But most proponents of search neutrality fail to recognize that all Google’s search results entail bias in favor of its own offerings. As Geoff Manne and Josh Wright noted in 2011 at the height of the search neutrality debate:

[S]earch engines offer up results in the form not only of typical text results, but also maps, travel information, product pages, books, social media and more. To the extent that alleged bias turns on a search engine favoring its own maps, for example, over another firm’s, the allegation fails to appreciate that text results and maps are variants of the same thing, and efforts to restrain a search engine from offering its own maps is no different than preventing it from offering its own search results.

Nevermind that Google with forced non-discrimination likely means Google offering only the antiquated “ten blue links” search results page it started with in 1998 instead of the far more useful “rich” results it offers today; logically it would also mean Google somehow offering the set of links produced by any and all other search engines’ algorithms, in lieu of its own. If you think Google will continue to invest in and maintain the wealth of services it offers today on the strength of the profits derived from those search results, well, Elizabeth Warren is probably already your favorite politician.

Source: Web Design Museum  

And regulatory oversight of algorithmic content won’t just result in an impoverished digital experience; it will inevitably lead to an authoritarian one, as well:

Any agency granted a mandate to undertake such algorithmic oversight, and override or reconfigure the product of online services, thereby controls the content consumers may access…. This sort of control is deeply problematic… [because it saddles users] with a pervasive set of speech controls promulgated by the government. The history of such state censorship is one which has demonstrated strong harms to both social welfare and rule of law, and should not be emulated.

Digital Assistants. Consider also the veritable cage match among the tech giants to offer “digital assistants” and “smart home” devices with ever-more features at ever-lower prices. Today the allegedly non-existent competition among these companies is played out most visibly in this multi-featured market, comprising advanced devices tightly integrated with artificial intelligence, voice recognition, advanced algorithms, and a host of services. Under Warren’s nondiscrimination principle this market disappears. Each device can offer only a connectivity platform (if such a service is even permitted to be bundled with a physical device…) — and nothing more.

But such a world entails not only the end of an entire, promising avenue of consumer-benefiting innovation, it also entails the end of a promising avenue of consumer-benefiting competition. It beggars belief that anyone thinks consumers would benefit by forcing technology companies into their own silos, ensuring that the most powerful sources of competition for each other are confined to their own fiefdoms by order of law.

Breaking business models

Beyond the product-feature dimension, Sen. Warren’s proposal would be devastating for innovative business models. Why is Amazon Prime Video bundled with free shipping? Because the marginal cost of distribution for video is close to zero and bundling it with Amazon Prime increases the value proposition for customers. Why is almost every Google service free to users? Because Google’s business model is supported by ads, not monthly subscription fees. Each of the tech giants has carefully constructed an ecosystem in which every component reinforces the others. Sen. Warren’s plan would not only break up the companies, it would prohibit their business models — the ones that both created and continue to sustain these products. Such an outcome would manifestly harm consumers.

Both of Warren’s policy “solutions” are misguided and will lead to higher prices and less innovation. Her cause for alarm is built on a multitude of mistaken assumptions, but let’s address just a few (Warren in bold):

  • “Nearly half of all e-commerce goes through Amazon.” Yes, but it has only 5% of total retail in the United States. As my colleague Kristian Stout says, “the Internet is not a market; it’s a distribution channel.”
  • “Amazon has used its immense market power to force smaller competitors like Diapers.com to sell at a discounted rate.” The real story, as the founders of Diapers.com freely admitted, is that they sold diapers as what they hoped would be a loss leader, intending to build out sales of other products once they had a base of loyal customers:

And so we started with selling the loss leader product to basically build a relationship with mom. And once they had the passion for the brand and they were shopping with us on a weekly or a monthly basis that they’d start to fall in love with that brand. We were losing money on every box of diapers that we sold. We weren’t able to buy direct from the manufacturers.

Like all entrepreneurs, Diapers.com’s founders took a calculated risk that didn’t pay off as hoped. Amazon subsequently acquired the company (after it had declined a similar buyout offer from Walmart). (Antitrust laws protect consumers, not inefficient competitors). And no, this was not a case of predatory pricing. After many years of trying to make the business profitable as a subsidiary, Amazon shut it down in 2017.

  • “In the 1990s, Microsoft — the tech giant of its time — was trying to parlay its dominance in computer operating systems into dominance in the new area of web browsing. The federal government sued Microsoft for violating anti-monopoly laws and eventually reached a settlement. The government’s antitrust case against Microsoft helped clear a path for Internet companies like Google and Facebook to emerge.” The government’s settlement with Microsoft is not the reason Google and Facebook were able to emerge. Neither company entered the browser market at launch. Instead, they leapfrogged the browser entirely and created new platforms for the web (only later did Google create Chrome).

    Furthermore, if the Microsoft case is responsible for “clearing a path” for Google is it not also responsible for clearing a path for Google’s alleged depredations? If the answer is that antitrust enforcement should be consistently more aggressive in order to rein in Google, too, when it gets out of line, then how can we be sure that that same more-aggressive enforcement standard wouldn’t have curtailed the extent of the Microsoft ecosystem in which it was profitable for Google to become Google? Warren implicitly assumes that only the enforcement decision in Microsoft was relevant to Google’s rise. But Microsoft doesn’t exist in a vacuum. If Microsoft cleared a path for Google, so did every decision not to intervene, which, all combined, created the legal, business, and economic environment in which Google operates.

Warren characterizes Big Tech as a weight on the American economy. In fact, nothing could be further from the truth. These superstar companies are the drivers of productivity growth, all ranking at or near the top for most spending on research and development. And while data may not be the new oil, extracting value from it may require similar levels of capital expenditure. Last year, Big Tech spent as much or more on capex as the world’s largest oil companies:

Source: WSJ

Warren also faults Big Tech for a decline in startups, saying,

The number of tech startups has slumped, there are fewer high-growth young firms typical of the tech industry, and first financing rounds for tech startups have declined 22% since 2012.

But this trend predates the existence of the companies she criticizes, as this chart from Quartz shows:

The exact causes of the decline in business dynamism are still uncertain, but recent research points to a much more mundane explanation: demographics. Labor force growth has been declining, which has led to an increase in average firm age, nudging fewer workers to start their own businesses.

Furthermore, it’s not at all clear whether this is actually a decline in business dynamism, or merely a change in business model. We would expect to see the same pattern, for example, if would-be startup founders were designing their software for acquisition and further development within larger, better-funded enterprises.

Will Rinehart recently looked at the literature to determine whether there is indeed a “kill zone” for startups around Big Tech incumbents. One paper finds that “an increase in fixed costs explains most of the decline in the aggregate entrepreneurship rate.” Another shows an inverse correlation across 50 countries between GDP and entrepreneurship rates. Robert Lucas predicted these trends back in 1978, pointing out that productivity increases would lead to wage increases, pushing marginal entrepreneurs out of startups and into big companies.

It’s notable that many in the venture capital community would rather not have Sen. Warren’s “help”:

Arguably, it is also simply getting harder to innovate. As economists Nick Bloom, Chad Jones, John Van Reenen and Michael Webb argue,

just to sustain constant growth in GDP per person, the U.S. must double the amount of research effort searching for new ideas every 13 years to offset the increased difficulty of finding new ideas.

If this assessment is correct, it may well be that coming up with productive and profitable innovations is simply becoming more expensive, and thus, at the margin, each dollar of venture capital can fund less of it. Ironically, this also implies that larger firms, which can better afford the additional resources required to sustain exponential growth, are a crucial part of the solution, not the problem.

Warren believes that Big Tech is the cause of our social ills. But Americans have more trust in Amazon, Facebook, and Google than in the political institutions that would break them up. It would be wise for her to reflect on why that might be the case. By punishing our most valuable companies for past successes, Warren would chill competition and decrease returns to innovation.

Finally, in what can only be described as tragic irony, the most prominent political figure who shares Warren’s feelings on Big Tech is President Trump. Confirming the horseshoe theory of politics, far-left populism and far-right populism seem less distinguishable by the day. As our colleague Gus Hurwitz put it, with this proposal Warren is explicitly endorsing the unitary executive theory and implicitly endorsing Trump’s authority to direct his DOJ to “investigate specific cases and reach specific outcomes.” Which cases will he want to have investigated and what outcomes will he be seeking? More good questions that Senator Warren should be asking. The notion that competition, consumer welfare, and growth are likely to increase in such an environment is farcical.

The German Bundeskartellamt’s Facebook decision is unsound from either a competition or privacy policy perspective, and will only make the fraught privacy/antitrust relationship worse.

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Last week, I objected to Senator Warner relying on the flawed AOL/Time Warner merger conditions as a template for tech regulatory policy, but there is a much deeper problem contained in his proposals.  Although he does not explicitly say “big is bad” when discussing competition issues, the thrust of much of what he recommends would serve to erode the power of larger firms in favor of smaller firms without offering a justification for why this would result in a superior state of affairs. And he makes these recommendations without respect to whether those firms actually engage in conduct that is harmful to consumers.

In the Data Portability section, Warner says that “As platforms grow in size and scope, network effects and lock-in effects increase; consumers face diminished incentives to contract with new providers, particularly if they have to once again provide a full set of data to access desired functions.“ Thus, he recommends a data portability mandate, which would theoretically serve to benefit startups by providing them with the data that large firms possess. The necessary implication here is that it is a per se good that small firms be benefited and large firms diminished, as the proposal is not grounded in any evaluation of the competitive behavior of the firms to which such a mandate would apply.

Warner also proposes an “interoperability” requirement on “dominant platforms” (which I criticized previously) in situations where, “data portability alone will not produce procompetitive outcomes.” Again, the necessary implication is that it is a per se good that established platforms share their services with start ups without respect to any competitive analysis of how those firms are behaving. The goal is preemptively to “blunt their ability to leverage their dominance over one market or feature into complementary or adjacent markets or products.”

Perhaps most perniciously, Warner recommends treating large platforms as essential facilities in some circumstances. To this end he states that:

Legislation could define thresholds – for instance, user base size, market share, or level of dependence of wider ecosystems – beyond which certain core functions/platforms/apps would constitute ‘essential facilities’, requiring a platform to provide third party access on fair, reasonable and non-discriminatory (FRAND) terms and preventing platforms from engaging in self-dealing or preferential conduct.

But, as  i’ve previously noted with respect to imposing “essential facilities” requirements on tech platforms,

[T]he essential facilities doctrine is widely criticized, by pretty much everyone. In their respected treatise, Antitrust Law, Herbert Hovenkamp and Philip Areeda have said that “the essential facility doctrine is both harmful and unnecessary and should be abandoned”; Michael Boudin has noted that the doctrine is full of “embarrassing weaknesses”; and Gregory Werden has opined that “Courts should reject the doctrine.”

Indeed, as I also noted, “the Supreme Court declined to recognize the essential facilities doctrine as a distinct rule in Trinko, where it instead characterized the exclusionary conduct in Aspen Skiing as ‘at or near the outer boundary’ of Sherman Act § 2 liability.”

In short, it’s very difficult to know when access to a firm’s internal functions might be critical to the facilitation of a market. It simply cannot be true that a firm becomes bound under onerous essential facilities requirements (or classification as a public utility) simply because other firms find it more convenient to use its services than to develop their own.

The truth of what is actually happening in these cases, however, is that third-party firms are choosing to anchor their business to the processes of another firm which generates an “asset specificity” problem that they then seek the government to remedy:

A content provider that makes itself dependent upon another company for distribution (or vice versa, of course) takes a significant risk. Although it may benefit from greater access to users, it places itself at the mercy of the other — or at least faces great difficulty (and great cost) adapting to unanticipated, crucial changes in distribution over which it has no control.

This is naturally a calculated risk that a firm may choose to make, but it is a risk. To pry open Google or Facebook for the benefit of competitors that choose to play to Google and Facebook’s user base, rather than opening markets of their own, punishes the large players for being successful while also rewarding behavior that shies away from innovation. Further, such a policy would punish the large platforms whenever they innovate with their services in any way that might frustrate third-party “integrators” (see, e.g., Foundem’s claims that Google’s algorithm updates meant to improve search quality for users harmed Foundem’s search rankings).  

Rather than encouraging innovation, blessing this form of asset specificity would have the perverse result of entrenching the status quo.

In all of these recommendations from Senator Warner, there is no claim that any of the targeted firms will have behaved anticompetitively, but merely that they are above a certain size. This is to say that, in some cases, big is bad.

Senator Warner’s policies would harm competition and innovation

As Geoffrey Manne and Gus Hurwitz have recently noted these views run completely counter to the last half-century or more of economic and legal learning that has occurred in antitrust law. From its murky, politically-motivated origins through the early 60’s when the Structure-Conduct-Performance (“SCP”) interpretive framework was ascendant, antitrust law was more or less guided by the gut feeling of regulators that big business necessarily harmed the competitive process.

Thus, at its height with SCP, “big is bad” antitrust relied on presumptions that large firms over a certain arbitrary threshold were harmful and should be subjected to more searching judicial scrutiny when merging or conducting business.

A paradigmatic example of this approach can be found in Von’s Grocery where the Supreme Court prevented the merger of two relatively small grocery chains. Combined, the two chains would have constitutes a mere 9 percent of the market, yet the Supreme Court, relying on the SCP aversion to concentration in itself, prevented the merger despite any procompetitive justifications that would have allowed the combined entity to compete more effectively in a market that was coming to be dominated by large supermarkets.

As Manne and Hurwitz observe: “this decision meant breaking up a merger that did not harm consumers, on the one hand, while preventing firms from remaining competitive in an evolving market by achieving efficient scale, on the other.” And this gets to the central defect of Senator Warner’s proposals. He ties his decisions to interfere in the operations of large tech firms to their size without respect to any demonstrable harm to consumers.

To approach antitrust this way — that is, to roll the clock back to a period before there was a well-defined and administrable standard for antitrust — is to open the door for regulation by political whim. But the value of the contemporary consumer welfare test is that it provides knowable guidance that limits both the undemocratic conduct of politically motivated enforcers as well as the opportunities for private firms to engage in regulatory capture. As Manne and Hurwitz observe:

Perhaps the greatest virtue of the consumer welfare standard is not that it is the best antitrust standard (although it is) — it’s simply that it is a standard. The story of antitrust law for most of the 20th century was one of standard-less enforcement for political ends. It was a tool by which any entrenched industry could harness the force of the state to maintain power or stifle competition.

While it is unlikely that Senator Warner intends to entrench politically powerful incumbents, or enable regulation by whim, those are the likely effects of his proposals.

Antitrust law has a rich set of tools for dealing with competitive harm. Introducing legislation to define arbitrary thresholds for limiting the potential power of firms will ultimately undermine the power of those tools and erode the welfare of consumers.

 

The world discovered something this past weekend that the world had already known: that what you say on the Internet stays on the Internet, spread intractably and untraceably through the tendrils of social media. I refer, of course, to the Cambridge Analytica/Facebook SNAFU (or just Situation Normal): the disclosure that Cambridge Analytica, a company used for election analytics by the Trump campaign, breached a contract with Facebook in order to unauthorizedly collect information on 50 million Facebook users. Since the news broke, Facebook’s stock is off by about 10 percent, Cambridge Analytica is almost certainly a doomed company, the FTC has started investigating both, private suits against Facebook are already being filed, the Europeans are investigating as well, and Cambridge Analytica is now being blamed for Brexit.

That is all fine and well, and we will be discussing this situation and its fallout for years to come. I want to write about a couple of other aspects of the story: the culpability of 270,000 Facebook users in disclosing the data of 50 million of their peers, and what this situation tells us about evergreen proposals to “open up the social graph” by making users’ social media content portable.

I Have Seen the Enemy and the Enemy is Us

Most discussion of Cambridge Analytica’s use of Facebook data has focused on the large number of user records Cambridge Analytica obtained access to – 50 million – and the fact that it obtained these records through some problematic means (and Cambridge Analytica pretty clearly breached contracts and acted deceptively to obtain these records). But one needs to dig a deeper to understand the mechanics of what actually happened. Once one does this, the story becomes both less remarkable and more interesting.

(For purposes of this discussion, I refer to Cambridge Analytica as the actor that obtained the records. It’s actually a little more complicated: Cambridge Analytica worked with an academic researcher to obtain these records. That researcher was given permission by Facebook to work with and obtain data on users for purposes relating to his research. But he exceeded that scope of authority, sharing the data that he collected with CA.)

The 50 million users’ records that Cambridge Analytica obtained access to were given to Cambridge Analytica by about 200,000 individual Facebook users. Those 270,000 users become involved with Cambridge Analytica by participating in an online quiz – one of those fun little throwaway quizzes that periodically get some attention on Facebook and other platforms. As part of taking that quiz, those 270,000 users agreed to grant Cambridge Analytica access to their profile information, including information available through their profile about their friends.

This general practice is reasonably well known. Any time a quiz or game like this has its moment on Facebook it is also accompanied by discussion of how the quiz or game is likely being used to harvest data about users. The terms of use of these quizzes and games almost always disclose that such information is being collected. More telling, any time a user posts a link to one of these quizzes or games, some friend will will invariably leave a comment warning about these terms of service and of these data harvesting practices.

There are two remarkable things about this. The first remarkable thing is that there is almost nothing remarkable about the fact that Cambridge Analytica obtained this information. A hundred such data harvesting efforts have preceded Cambridge Analytica; and a hundred more will follow it. The only remarkable things about the present story is that Cambridge Analytica was an election analytics firm working for Donald Trump – never mind that by all accounts the data collected proved to be of limited use generally in elections or that when Cambridge Analytica started working for the Trump campaign they were tasked with more mundane work that didn’t make use of this data.

More remarkable is that Cambridge Analytica didn’t really obtain data about 50 million individuals from Facebook, or from a Facebook quiz. Cambridge Analytica obtained this data from those 50 million individuals’ friends.

There are unquestionably important questions to be asked about the role of Facebook in giving users better control over, or ability to track uses of, their information. And there are questions about the use of contracts such as that between Facebook and Cambridge Analytica to control how data like this is handled. But this discussion will not be complete unless and until we also understand the roles and responsibilities of individual users in managing and respecting the privacy of their friends.

Fundamentally, we lack a clear and easy way to delineate privacy rights. If I share with my friends that I participated in a political rally, that I attended a concert, that I like certain activities, that I engage in certain illegal activities, what rights do I have to control how they subsequently share that information? The answer in the physical world, in the American tradition, is none – at least, unless I take affirmative steps to establish such a right prior to disclosing that information.

The answer is the same in the online world, as well – though platforms have substantial ability to alter this if they so desire. For instance, Facebook could change the design of its system to prohibit users from sharing information about their friends with third parties. (Indeed, this is something that most privacy advocates think social media platforms should do.) But such a “solution” to the delineation problem has its own problems. It assumes that the platform is the appropriate arbiter of privacy rights – a perhaps questionable assumption given platforms’ history of getting things wrong when it comes to privacy. More trenchant, it raises questions about users’ ability to delineate or allocate their privacy differently than allowed by the platforms, particularly where a given platform may not allow the delineation or allocation of rights that users prefer.

The Badness of the Open Graph Idea

One of the standard responses to concerns about how platforms may delineate and allow users to allocate their privacy interests is, on the one hand, that competition among platforms would promote desirable outcomes and that, on the other hand, the relatively limited and monopolistic competition that we see among firms like Facebook is one of the reasons that consumers today have relatively poor control over their information.

The nature of competition in markets such as these, including whether and how to promote more of it, is a perennial and difficult topic. The network effects inherent in markets like these suggest that promoting competition may in fact not improve consumer outcomes, for instance. Competition could push firms to less consumer-friendly privacy positions if that allows better monetization and competitive advantages. And the simple fact that Facebook has lost 10% of its value following the Cambridge Analytica news suggests that there are real market constraints on how Facebook operates.

But placing those issues to the side for now, the situation with Cambridge Analytica offers an important cautionary tale about one of the perennial proposals for how to promote competition between social media platforms: “opening up the social graph.” The basic idea of these proposals is to make it easier for users of these platforms to migrate between platforms or to use the features of different platforms through data portability and interoperability. Specific proposals have taken various forms over the years, but generally they would require firms like Facebook to either make users’ data exportable in a standardized form so that users could easily migrate it to other platforms or to adopt a standardized API that would allow other platforms to interoperate with data stored on the Facebook platform.

In other words, proposals to “open the social graph” are proposals to make it easier to export massive volumes of Facebook user data to third parties at efficient scale.

If there is one lesson from the past decade that is more trenchant than that delineation privacy rights is difficult it is that data security is even harder.

These last two points do not sum together well. The easier that Facebook makes it for its users’ data to be exported at scale, the easier Facebook makes it for its users’ data to be exfiltrated at scale. Despite its myriad problems, Cambridge Analytica at least was operating within a contractual framework with Facebook – it was a known party. Creating external API for exporting Facebook data makes it easier for unknown third-parties to anonymously obtain user information. Indeed, even if the API only works to allow trusted third parties to to obtain such information, the problem of keeping that data secured against subsequent exfiltration multiplies with each third party that is allowed access to that data.

Last week the editorial board of the Washington Post penned an excellent editorial responding to the European Commission’s announcement of its decision in its Google Shopping investigation. Here’s the key language from the editorial:

Whether the demise of any of [the complaining comparison shopping sites] is specifically traceable to Google, however, is not so clear. Also unclear is the aggregate harm from Google’s practices to consumers, as opposed to the unlucky companies. Birkenstock-seekers may well prefer to see a Google-generated list of vendors first, instead of clicking around to other sites…. Those who aren’t happy anyway have other options. Indeed, the rise of comparison shopping on giants such as Amazon and eBay makes concerns that Google might exercise untrammeled power over e-commerce seem, well, a bit dated…. Who knows? In a few years we might be talking about how Facebook leveraged its 2 billion users to disrupt the whole space.

That’s actually a pretty thorough, if succinct, summary of the basic problems with the Commission’s case (based on its PR and Factsheet, at least; it hasn’t released the full decision yet).

I’ll have more to say on the decision in due course, but for now I want to elaborate on two of the points raised by the WaPo editorial board, both in service of its crucial rejoinder to the Commission that “Also unclear is the aggregate harm from Google’s practices to consumers, as opposed to the unlucky companies.”

First, the WaPo editorial board points out that:

Birkenstock-seekers may well prefer to see a Google-generated list of vendors first, instead of clicking around to other sites.

It is undoubtedly true that users “may well prefer to see a Google-generated list of vendors first.” It’s also crucial to understanding the changes in Google’s search results page that have given rise to the current raft of complaints.

As I noted in a Wall Street Journal op-ed two years ago:

It’s a mistake to consider “general search” and “comparison shopping” or “product search” to be distinct markets.

From the moment it was technologically feasible to do so, Google has been adapting its traditional search results—that familiar but long since vanished page of 10 blue links—to offer more specialized answers to users’ queries. Product search, which is what is at issue in the EU complaint, is the next iteration in this trend.

Internet users today seek information from myriad sources: Informational sites (Wikipedia and the Internet Movie Database); review sites (Yelp and TripAdvisor); retail sites (Amazon and eBay); and social-media sites (Facebook and Twitter). What do these sites have in common? They prioritize certain types of data over others to improve the relevance of the information they provide.

“Prioritization” of Google’s own shopping results, however, is the core problem for the Commission:

Google has systematically given prominent placement to its own comparison shopping service: when a consumer enters a query into the Google search engine in relation to which Google’s comparison shopping service wants to show results, these are displayed at or near the top of the search results. (Emphasis in original).

But this sort of prioritization is the norm for all search, social media, e-commerce and similar platforms. And this shouldn’t be a surprise: The value of these platforms to the user is dependent upon their ability to sort the wheat from the chaff of the now immense amount of information coursing about the Web.

As my colleagues and I noted in a paper responding to a methodologically questionable report by Tim Wu and Yelp leveling analogous “search bias” charges in the context of local search results:

Google is a vertically integrated company that offers general search, but also a host of other products…. With its well-developed algorithm and wide range of products, it is hardly surprising that Google can provide not only direct answers to factual questions, but also a wide range of its own products and services that meet users’ needs. If consumers choose Google not randomly, but precisely because they seek to take advantage of the direct answers and other options that Google can provide, then removing the sort of “bias” alleged by [complainants] would affirmatively hurt, not help, these users. (Emphasis added).

And as Josh Wright noted in an earlier paper responding to yet another set of such “search bias” charges (in that case leveled in a similarly methodologically questionable report by Benjamin Edelman and Benjamin Lockwood):

[I]t is critical to recognize that bias alone is not evidence of competitive harm and it must be evaluated in the appropriate antitrust economic context of competition and consumers, rather individual competitors and websites. Edelman & Lockwood´s analysis provides a useful starting point for describing how search engines differ in their referrals to their own content. However, it is not useful from an antitrust policy perspective because it erroneously—and contrary to economic theory and evidence—presumes natural and procompetitive product differentiation in search rankings to be inherently harmful. (Emphasis added).

We’ll have to see what kind of analysis the Commission relies upon in its decision to reach its conclusion that prioritization is an antitrust problem, but there is reason to be skeptical that it will turn out to be compelling. The Commission states in its PR that:

The evidence shows that consumers click far more often on results that are more visible, i.e. the results appearing higher up in Google’s search results. Even on a desktop, the ten highest-ranking generic search results on page 1 together generally receive approximately 95% of all clicks on generic search results (with the top result receiving about 35% of all the clicks). The first result on page 2 of Google’s generic search results receives only about 1% of all clicks. This cannot just be explained by the fact that the first result is more relevant, because evidence also shows that moving the first result to the third rank leads to a reduction in the number of clicks by about 50%. The effects on mobile devices are even more pronounced given the much smaller screen size.

This means that by giving prominent placement only to its own comparison shopping service and by demoting competitors, Google has given its own comparison shopping service a significant advantage compared to rivals. (Emphasis added).

Whatever truth there is in the characterization that placement is more important than relevance in influencing user behavior, the evidence cited by the Commission to demonstrate that doesn’t seem applicable to what’s happening on Google’s search results page now.

Most crucially, the evidence offered by the Commission refers only to how placement affects clicks on “generic search results” and glosses over the fact that the “prominent placement” of Google’s “results” is not only a difference in position but also in the type of result offered.

Google Shopping results (like many of its other “vertical results” and direct answers) are very different than the 10 blue links of old. These “universal search” results are, for one thing, actual answers rather than merely links to other sites. They are also more visually rich and attractively and clearly displayed.

Ironically, Tim Wu and Yelp use the claim that users click less often on Google’s universal search results to support their contention that increased relevance doesn’t explain Google’s prioritization of its own content. Yet, as we note in our response to their study:

[I]f a consumer is using a search engine in order to find a direct answer to a query rather than a link to another site to answer it, click-through would actually represent a decrease in consumer welfare, not an increase.

In fact, the study fails to incorporate this dynamic even though it is precisely what the authors claim the study is measuring.

Further, as the WaPo editorial intimates, these universal search results (including Google Shopping results) are quite plausibly more valuable to users. As even Tim Wu and Yelp note:

No one truly disagrees that universal search, in concept, can be an important innovation that can serve consumers.

Google sees it exactly this way, of course. Here’s Tim Wu and Yelp again:

According to Google, a principal difference between the earlier cases and its current conduct is that universal search represents a pro-competitive, user-serving innovation. By deploying universal search, Google argues, it has made search better. As Eric Schmidt argues, “if we know the answer it is better for us to answer that question so [the user] doesn’t have to click anywhere, and in that sense we… use data sources that are our own because we can’t engineer it any other way.”

Of course, in this case, one would expect fewer clicks to correlate with higher value to users — precisely the opposite of the claim made by Tim Wu and Yelp, which is the surest sign that their study is faulty.

But the Commission, at least according to the evidence cited in its PR, doesn’t even seem to measure the relative value of the very different presentations of information at all, instead resting on assertions rooted in the irrelevant difference in user propensity to click on generic (10 blue links) search results depending on placement.

Add to this Pinar Akman’s important point that Google Shopping “results” aren’t necessarily search results at all, but paid advertising:

[O]nce one appreciates the fact that Google’s shopping results are simply ads for products and Google treats all ads with the same ad-relevant algorithm and all organic results with the same organic-relevant algorithm, the Commission’s order becomes impossible to comprehend. Is the Commission imposing on Google a duty to treat non-sponsored results in the same way that it treats sponsored results? If so, does this not provide an unfair advantage to comparison shopping sites over, for example, Google’s advertising partners as well as over Amazon, eBay, various retailers, etc…?

Randy Picker also picks up on this point:

But those Google shopping boxes are ads, Picker told me. “I can’t imagine what they’re thinking,” he said. “Google is in the advertising business. That’s how it makes its money. It has no obligation to put other people’s ads on its website.”

The bottom line here is that the WaPo editorial board does a better job characterizing the actual, relevant market dynamics in a single sentence than the Commission seems to have done in its lengthy releases summarizing its decision following seven full years of investigation.

The second point made by the WaPo editorial board to which I want to draw attention is equally important:

Those who aren’t happy anyway have other options. Indeed, the rise of comparison shopping on giants such as Amazon and eBay makes concerns that Google might exercise untrammeled power over e-commerce seem, well, a bit dated…. Who knows? In a few years we might be talking about how Facebook leveraged its 2 billion users to disrupt the whole space.

The Commission dismisses this argument in its Factsheet:

The Commission Decision concerns the effect of Google’s practices on comparison shopping markets. These offer a different service to merchant platforms, such as Amazon and eBay. Comparison shopping services offer a tool for consumers to compare products and prices online and find deals from online retailers of all types. By contrast, they do not offer the possibility for products to be bought on their site, which is precisely the aim of merchant platforms. Google’s own commercial behaviour reflects these differences – merchant platforms are eligible to appear in Google Shopping whereas rival comparison shopping services are not.

But the reality is that “comparison shopping,” just like “general search,” is just one technology among many for serving information and ads to consumers online. Defining the relevant market or limiting the definition of competition in terms of the particular mechanism that Google (or Foundem, or Amazon, or Facebook…) happens to use doesn’t reflect the extent of substitutability between these different mechanisms.

Properly defined, the market in which Google competes online is not search, but something more like online “matchmaking” between advertisers, retailers and consumers. And this market is enormously competitive. The same goes for comparison shopping.

And the fact that Amazon and eBay “offer the possibility for products to be bought on their site” doesn’t take away from the fact that they also “offer a tool for consumers to compare products and prices online and find deals from online retailers of all types.” Not only do these sites contain enormous amounts of valuable (and well-presented) information about products, including product comparisons and consumer reviews, but they also actually offer comparisons among retailers. In fact, Fifty percent of the items sold through Amazon’s platform, for example, are sold by third-party retailers — the same sort of retailers that might also show up on a comparison shopping site.

More importantly, though, as the WaPo editorial rightly notes, “[t]hose who aren’t happy anyway have other options.” Google just isn’t the indispensable gateway to the Internet (and definitely not to shopping on the Internet) that the Commission seems to think.

Today over half of product searches in the US start on Amazon. The majority of web page referrals come from Facebook. Yelp’s most engaged users now access it via its app (which has seen more than 3x growth in the past five years). And a staggering 40 percent of mobile browsing on both Android and iOS now takes place inside the Facebook app.

Then there are “closed” platforms like the iTunes store and innumerable other apps that handle copious search traffic (including shopping-related traffic) but also don’t figure in the Commission’s analysis, apparently.

In fact, billions of users reach millions of companies every day through direct browser navigation, social media, apps, email links, review sites, blogs, and countless other means — all without once touching Google.com. So-called “dark social” interactions (email, text messages, and IMs) drive huge amounts of some of the most valuable traffic on the Internet, in fact.

All of this, in turn, has led to a competitive scramble to roll out completely new technologies to meet consumers’ informational (and merchants’ advertising) needs. The already-arriving swarm of VR, chatbots, digital assistants, smart-home devices, and more will offer even more interfaces besides Google through which consumers can reach their favorite online destinations.

The point is this: Google’s competitors complaining that the world is evolving around them don’t need to rely on Google. That they may choose to do so does not saddle Google with an obligation to ensure that they can always do so.

Antitrust laws — in Europe, no less than in the US — don’t require Google or any other firm to make life easier for competitors. That’s especially true when doing so would come at the cost of consumer-welfare-enhancing innovations. The Commission doesn’t seem to have grasped this fundamental point, however.

The WaPo editorial board gets it, though:

The immense size and power of all Internet giants are a legitimate focus for the antitrust authorities on both sides of the Atlantic. Brussels vs. Google, however, seems to be a case of punishment without crime.

Recent years have seen an increasing interest in incorporating privacy into antitrust analysis. The FTC and regulators in Europe have rejected these calls so far, but certain scholars and activists continue their attempts to breathe life into this novel concept. Elsewhere we have written at length on the scholarship addressing the issue and found the case for incorporation wanting. Among the errors proponents make is a persistent (and woefully unsubstantiated) assertion that online data can amount to a barrier to entry, insulating incumbent services from competition and ensuring that only the largest providers thrive. This data barrier to entry, it is alleged, can then allow firms with monopoly power to harm consumers, either directly through “bad acts” like price discrimination, or indirectly by raising the costs of advertising, which then get passed on to consumers.

A case in point was on display at last week’s George Mason Law & Economics Center Briefing on Big Data, Privacy, and Antitrust. Building on their growing body of advocacy work, Nathan Newman and Allen Grunes argued that this hypothesized data barrier to entry actually exists, and that it prevents effective competition from search engines and social networks that are interested in offering services with heightened privacy protections.

According to Newman and Grunes, network effects and economies of scale ensure that dominant companies in search and social networking (they specifically named Google and Facebook — implying that they are in separate markets) operate without effective competition. This results in antitrust harm, they assert, because it precludes competition on the non-price factor of privacy protection.

In other words, according to Newman and Grunes, even though Google and Facebook offer their services for a price of $0 and constantly innovate and upgrade their products, consumers are nevertheless harmed because the business models of less-privacy-invasive alternatives are foreclosed by insufficient access to data (an almost self-contradicting and silly narrative for many reasons, including the big question of whether consumers prefer greater privacy protection to free stuff). Without access to, and use of, copious amounts of data, Newman and Grunes argue, the algorithms underlying search and targeted advertising are necessarily less effective and thus the search product without such access is less useful to consumers. And even more importantly to Newman, the value to advertisers of the resulting consumer profiles is diminished.

Newman has put forth a number of other possible antitrust harms that purportedly result from this alleged data barrier to entry, as well. Among these is the increased cost of advertising to those who wish to reach consumers. Presumably this would harm end users who have to pay more for goods and services because the costs of advertising are passed on to them. On top of that, Newman argues that ad networks inherently facilitate price discrimination, an outcome that he asserts amounts to antitrust harm.

FTC Commissioner Maureen Ohlhausen (who also spoke at the George Mason event) recently made the case that antitrust law is not well-suited to handling privacy problems. She argues — convincingly — that competition policy and consumer protection should be kept separate to preserve doctrinal stability. Antitrust law deals with harms to competition through the lens of economic analysis. Consumer protection law is tailored to deal with broader societal harms and aims at protecting the “sanctity” of consumer transactions. Antitrust law can, in theory, deal with privacy as a non-price factor of competition, but this is an uneasy fit because of the difficulties of balancing quality over two dimensions: Privacy may be something some consumers want, but others would prefer a better algorithm for search and social networks, and targeted ads with free content, for instance.

In fact, there is general agreement with Commissioner Ohlhausen on her basic points, even among critics like Newman and Grunes. But, as mentioned above, views diverge over whether there are some privacy harms that should nevertheless factor into competition analysis, and on whether there is in fact  a data barrier to entry that makes these harms possible.

As we explain below, however, the notion of data as an antitrust-relevant barrier to entry is simply a myth. And, because all of the theories of “privacy as an antitrust harm” are essentially predicated on this, they are meritless.

First, data is useful to all industries — this is not some new phenomenon particular to online companies

It bears repeating (because critics seem to forget it in their rush to embrace “online exceptionalism”) that offline retailers also receive substantial benefit from, and greatly benefit consumers by, knowing more about what consumers want and when they want it. Through devices like coupons and loyalty cards (to say nothing of targeted mailing lists and the age-old practice of data mining check-out receipts), brick-and-mortar retailers can track purchase data and better serve consumers. Not only do consumers receive better deals for using them, but retailers know what products to stock and advertise and when and on what products to run sales. For instance:

  • Macy’s analyzes tens of millions of terabytes of data every day to gain insights from social media and store transactions. Over the past three years, the use of big data analytics alone has helped Macy’s boost its revenue growth by 4 percent annually.
  • Following its acquisition of Kosmix in 2011, Walmart established @WalmartLabs, which created its own product search engine for online shoppers. In the first year of its use alone, the number of customers buying a product on Walmart.com after researching a purchase increased by 20 percent. According to Ron Bensen, the vice president of engineering at @WalmartLabs, the combination of in-store and online data could give brick-and-mortar retailers like Walmart an advantage over strictly online stores.
  • Panera and a whole host of restaurants, grocery stores, drug stores and retailers use loyalty cards to advertise and learn about consumer preferences.

And of course there is a host of others uses for data, as well, including security, fraud prevention, product optimization, risk reduction to the insured, knowing what content is most interesting to readers, etc. The importance of data stretches far beyond the online world, and far beyond mere retail uses more generally. To describe even online giants like Amazon, Apple, Microsoft, Facebook and Google as having a monopoly on data is silly.

Second, it’s not the amount of data that leads to success but building a better mousetrap

The value of knowing someone’s birthday, for example, is not in that tidbit itself, but in the fact that you know this is a good day to give that person a present. Most of the data that supports the advertising networks underlying the Internet ecosphere is of this sort: Information is important to companies because of the value that can be drawn from it, not for the inherent value of the data itself. Companies don’t collect information about you to stalk you, but to better provide goods and services to you.

Moreover, data itself is not only less important than what can be drawn from it, but data is also less important than the underlying product it informs. For instance, Snapchat created a challenger to  Facebook so successfully (and in such short time) that Facebook attempted to buy it for $3 billion (Google offered $4 billion). But Facebook’s interest in Snapchat wasn’t about its data. Instead, Snapchat was valuable — and a competitive challenge to Facebook — because it cleverly incorporated the (apparently novel) insight that many people wanted to share information in a more private way.

Relatedly, Twitter, Instagram, LinkedIn, Yelp, Pinterest (and Facebook itself) all started with little (or no) data and they have had a lot of success. Meanwhile, despite its supposed data advantages, Google’s attempts at social networking — Google+ — have never caught up to Facebook in terms of popularity to users (and thus not to advertisers either). And scrappy social network Ello is starting to build a significant base without data collection for advertising at all.

At the same time it’s simply not the case that the alleged data giants — the ones supposedly insulating themselves behind data barriers to entry — actually have the type of data most relevant to startups anyway. As Andres Lerner has argued, if you wanted to start a travel business, the data from Kayak or Priceline would be far more relevant. Or if you wanted to start a ride-sharing business, data from cab companies would be more useful than the broad, market-cross-cutting profiles Google and Facebook have. Consider companies like Uber, Lyft and Sidecar that had no customer data when they began to challenge established cab companies that did possess such data. If data were really so significant, they could never have competed successfully. But Uber, Lyft and Sidecar have been able to effectively compete because they built products that users wanted to use — they came up with an idea for a better mousetrap.The data they have accrued came after they innovated, entered the market and mounted their successful challenges — not before.

In reality, those who complain about data facilitating unassailable competitive advantages have it exactly backwards. Companies need to innovate to attract consumer data, otherwise consumers will switch to competitors (including both new entrants and established incumbents). As a result, the desire to make use of more and better data drives competitive innovation, with manifestly impressive results: The continued explosion of new products, services and other apps is evidence that data is not a bottleneck to competition but a spur to drive it.

Third, competition online is one click or thumb swipe away; that is, barriers to entry and switching costs are low

Somehow, in the face of alleged data barriers to entry, competition online continues to soar, with newcomers constantly emerging and triumphing. This suggests that the barriers to entry are not so high as to prevent robust competition.

Again, despite the supposed data-based monopolies of Facebook, Google, Amazon, Apple and others, there exist powerful competitors in the marketplaces they compete in:

  • If consumers want to make a purchase, they are more likely to do their research on Amazon than Google.
  • Google flight search has failed to seriously challenge — let alone displace —  its competitors, as critics feared. Kayak, Expedia and the like remain the most prominent travel search sites — despite Google having literally purchased ITA’s trove of flight data and data-processing acumen.
  • People looking for local reviews go to Yelp and TripAdvisor (and, increasingly, Facebook) as often as Google.
  • Pinterest, one of the most highly valued startups today, is now a serious challenger to traditional search engines when people want to discover new products.
  • With its recent acquisition of the shopping search engine, TheFind, and test-run of a “buy” button, Facebook is also gearing up to become a major competitor in the realm of e-commerce, challenging Amazon.
  • Likewise, Amazon recently launched its own ad network, “Amazon Sponsored Links,” to challenge other advertising players.

Even assuming for the sake of argument that data creates a barrier to entry, there is little evidence that consumers cannot easily switch to a competitor. While there are sometimes network effects online, like with social networking, history still shows that people will switch. MySpace was considered a dominant network until it made a series of bad business decisions and everyone ended up on Facebook instead. Similarly, Internet users can and do use Bing, DuckDuckGo, Yahoo, and a plethora of more specialized search engines on top of and instead of Google. And don’t forget that Google itself was once an upstart new entrant that replaced once-household names like Yahoo and AltaVista.

Fourth, access to data is not exclusive

Critics like Newman have compared Google to Standard Oil and argued that government authorities need to step in to limit Google’s control over data. But to say data is like oil is a complete misnomer. If Exxon drills and extracts oil from the ground, that oil is no longer available to BP. Data is not finite in the same way. To use an earlier example, Google knowing my birthday doesn’t limit the ability of Facebook to know my birthday, as well. While databases may be proprietary, the underlying data is not. And what matters more than the data itself is how well it is analyzed.

This is especially important when discussing data online, where multi-homing is ubiquitous, meaning many competitors end up voluntarily sharing access to data. For instance, I can use the friend-finder feature on WordPress to find Facebook friends, Google connections, and people I’m following on Twitter who also use the site for blogging. Using this feature allows WordPress to access your contact list on these major online players.

Friend-Finder

Further, it is not apparent that Google’s competitors have less data available to them. Microsoft, for instance, has admitted that it may actually have more data. And, importantly for this discussion, Microsoft may have actually garnered some of its data for Bing from Google.

If Google has a high cost per click, then perhaps it’s because it is worth it to advertisers: There are more eyes on Google because of its superior search product. Contra Newman and Grunes, Google may just be more popular for consumers and advertisers alike because the algorithm makes it more useful, not because it has more data than everyone else.

Fifth, the data barrier to entry argument does not have workable antitrust remedies

The misguided logic of data barrier to entry arguments leaves a lot of questions unanswered. Perhaps most important among these is the question of remedies. What remedy would apply to a company found guilty of leveraging its market power with data?

It’s actually quite difficult to conceive of a practical means for a competition authority to craft remedies that would address the stated concerns without imposing enormous social costs. In the unilateral conduct context, the most obvious remedy would involve the forced sharing of data.

On the one hand, as we’ve noted, it’s not clear this would actually accomplish much. If competitors can’t actually make good use of data, simply having more of it isn’t going to change things. At the same time, such a result would reduce the incentive to build data networks to begin with. In their startup stage, companies like Uber and Facebook required several months and hundreds of thousands, if not millions, of dollars to design and develop just the first iteration of the products consumers love. Would any of them have done it if they had to share their insights? In fact, it may well be that access to these free insights is what competitors actually want; it’s not the data they’re lacking, but the vision or engineering acumen to use it.

Other remedies limiting collection and use of data are not only outside of the normal scope of antitrust remedies, they would also involve extremely costly court supervision and may entail problematic “collisions between new technologies and privacy rights,” as the last year’s White House Report on Big Data and Privacy put it.

It is equally unclear what an antitrust enforcer could do in the merger context. As Commissioner Ohlhausen has argued, blocking specific transactions does not necessarily stop data transfer or promote privacy interests. Parties could simply house data in a standalone entity and enter into licensing arrangements. And conditioning transactions with forced data sharing requirements would lead to the same problems described above.

If antitrust doesn’t provide a remedy, then it is not clear why it should apply at all. The absence of workable remedies is in fact a strong indication that data and privacy issues are not suitable for antitrust. Instead, such concerns would be better dealt with under consumer protection law or by targeted legislation.