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[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.

I’m of two minds on the issue of tech expertise in Congress.

Yes there is good evidence that members of Congress and Congressional staff don’t have broad technical expertise. Scholars Zach Graves and Kevin Kosar have detailed these problems, as well as Travis Moore who wrote, “Of the 3,500 legislative staff on the Hill, I’ve found just seven that have any formal technical training.” Moore continued with a description of his time as a staffer that I think is honest,

In Congress, especially in a member’s office, very few people are subject-matter experts. The best staff depend on a network of trusted friends and advisors, built from personal relationships, who can help them break down the complexities of an issue.

But on the other hand, it is not clear that more tech expertise at Congress’ disposal would lead to better outcomes. Over at the American Action Forum, I explored this topic in depth. Since publishing that piece in October, I’ve come to recognize two gaps that I didn’t address in that original piece. The first relates to expert bias and the second concerns office organization.  

Expert Bias In Tech Regulation

Let’s assume for the moment that legislators do become more technically proficient by any number of means. If policymakers are normal people, and let me tell you, they are, the result will be overconfidence of one sort or another. In psychology research, overconfidence includes three distinct ways of thinking. Overestimation is thinking that you are better than you are. Overplacement is the belief that you are better than others. And overprecision is excessive faith that you know the truth.

For political experts, overprecision is common. A long-term study of  over 82,000 expert political forecasts by Philip E. Tetlock found that this group performed worse than they would have if they just randomly chosen an outcome. In the technical parlance, this means expert opinions were not calibrated; there wasn’t a correspondence between the predicted probabilities and the observed frequencies. Moreover, Tetlock found that events that experts deemed impossible occurred with some regularity. In a number of fields, these non-likely events came into being as much as 20 or 30 percent of the time. As Tetlock and co-author Dan Gardner explained, “our ability to predict human affairs is impressive only in its mediocrity.”    

While there aren’t many studies on the topic of expertise within government, workers within agencies have been shown to have overconfidence as well. As researchers Xinsheng Liu, James Stoutenborough, and Arnold Vedlitz discovered in surveying bureaucrats,   

Our analyses demonstrate that (a) the level of issue‐specific expertise perceived by individual bureaucrats is positively associated with their work experience/job relevance to climate change, (b) more experienced bureaucrats tend to be more overconfident in assessing their expertise, and (c) overconfidence, independently of sociodemographic characteristics, attitudinal factors and political ideology, correlates positively with bureaucrats’ risk‐taking policy choices.    

The expert bias literature leads to two lessons. First, more expertise doesn’t necessarily lead to better predictions or outcomes. Indeed, there are good reasons to suspect that more expertise would lead to overconfident policymakers and more risky political ventures within the law.

But second, and more importantly, what is meant by tech expertise needs to be more closely examined. Advocates want better decision making processes within government, a laudable goal. But staffing government agencies and Congress with experts doesn’t get you there. Like countless other areas, there is a diminishing marginal predictive return for knowledge. Rather than an injection of expertise, better methods of judgement should be pursued. Getting to that point will be a much more difficult goal.

The Production Function of Political Offices

As last year was winding down, Google CEO Sundar Pichai appeared before the House Judiciary Committee to answer questions regarding Google’s search engine. The coverage of the event by various outlets was similar in taking to task members for their the apparent lack of knowledge about the search engine. Here is how Mashable’s Matt Binder described the event,  

The main topic of the hearing — anti-conservative bias within Google’s search engine — really puts how little Congress understands into perspective. Early on in the hearing, Rep. Lamar Smith claimed as fact that 96 percent of Google search results come from liberal sources. Besides being proven false with a simple search of your own, Google’s search algorithm bases search rankings on attributes such as backlinks and domain authority. Partisanship of the news outlet does not come into play. Smith asserted that he believe the results are being manipulated, regardless of being told otherwise.

Smith wasn’t alone as both Representative Steve Chabot and Representative Steve King brought up concerns of anti-conservative bias. Towards the end of piece Binder laid bare his concern, which is shared by many,

There are certainly many concerns and critiques to be had over algorithms and data collection when it comes to Google and its products like Google Search and Google Ads. Sadly, not much time was spent on this substance at Tuesday’s hearing. Google-owned YouTube, the second most trafficked website in the world after Google, was barely addressed at the hearing tool. [sic]

Notice the assumption built into this critique. True substantive debate would probe the data collection practices of Google instead of the bias of its search results. Using this framing, it seems clear that Congressional members don’t understand tech. But there is a better way to understand this hearing, which requires asking a more mundane question: Why is it that political actors like Representatives Chabot, King, and Smith were so concerned with how they appeared in Google results?

Political scientists Gary Lee Malecha and Daniel J. Reagan offer a convincing answer in The Public Congress. As they document, political offices over the past two decades have been reorientated by the 24-hours news cycle. Legislative life now unfolds live in front of cameras and microphones and on videos online. Over time, external communication has risen to a prominent role in Congressional political offices, in key ways overtaking policy analysis.

While this internal change doesn’t lend to any hard and fast conclusions, it could help explain why emboldened tech expertise hasn’t been a winning legislative issue. The demand just isn’t there. And based on the priorities they do display a preference for, it might not yield any benefits, while also giving offices a potential cover.      

All of this being said, there are convincing reasons why more tech expertise could be beneficial. Yet, policymakers and the public shouldn’t assume that these reforms will be unalloyed goods.

The negativity that surrounded the deal at its announcement made Whole Foods seem like an innocent player, but it is important to recall that they were hemorrhaging and were looking to exit. Throughout the 2010s, the company lost its market leading edge as others began to offer the same kinds of services and products. Still, the company was able to sell near the top of its value to Amazon because it was able to court so many suitors. Given all of these features, Whole Foods could have been using the exit as a mechanism to appropriate another firm’s rent.

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