Yves here. Get a cup of coffee. This is an in-depth but accessible discussion of how the Big Tech monopolists abused their powers to secure and perfect their advantaged positions. The good news is that the government sleeping giant has awoken to the threat they pose to its authority, and it pulling out antitrust weapons with the aim of cutting the monopolists down to size.
By Maurice Stucke, Professor of Law, University of Tennessee. Originally published at the Institute for New Economic Thinking website
Consider a conversation Alastair Mactaggart had among friends at a social outing. The San Francisco real estate developer asked an engineer working for Google whether we should be worried about privacy. “Wasn’t ‘privacy’ just a bunch of hype?” Mactaggart asked. The Google engineer’s reply was chilling: “If people just understood how much we knew about them, they’d be really worried.”
Enforcers, policymakers, scholars, and the public are increasingly concerned about Google, Apple, Facebook, and Amazon. The public sentiment is that a few platforms, in possessing so much data, possess too much power. Something is amiss.
More than two-thirds of U.S. voters believe that tech giants like Google and Facebook should be subject to federal antitrust review, according to a 2019 Harvard CAPS/Harris Poll survey. Sixty-eight percent said that internet giants have largely built products and offered services to maximize their profits and accumulate market power, and 67 percent believe that the tech giants have taken steps to reduce competition in the market. In a 2020 survey, a majority of Americans again
· were concerned about the amount of data online platforms stored about them (85%);
· were concerned that platforms were collecting and holding this data about consumers to build out more comprehensive consumer profiles (81%); and
· supported more government regulation of platforms (60%) and mandating interoperability features (61%) to deal with the growing power of large online platforms that may be hurting competition and consumers.
The long winter of antitrust dormancy has ended. In 2020, the federal government and state attorneys general have sued Google for monopolizing the general search services, search advertising, and search text advertising markets and Facebook for monopolizing the personal social networking market in the United States. Given the Congressional findings from its inquiry of the digital platform economy, we can expect additional antitrust lawsuits against these data-opolies, as well as legislative reform. Drawing from the recently uncovered evidence from the governmental inquiries by Australia, the UK, and the US, as well as the Google and Facebook complaints, this article examines the new anti-monopoly movement taking hold across the globe.
Part I outlines the emerging consensus among policymakers and enforcers on several attributes of the digital platform economy. To understand why these data-opolies’ power is so durable, and how they successfully leveraged their power into other markets, Part II outlines three anticompetitive tactics these data-opolies employ: the now-casting radar, the acquire-copy-kill (“ACK”) strategy, and the Venus flytrap strategy for opening and then closing their platforms. As neither market forces nor current laws deter this anticompetitive behavior, Part III summarizes ten promising reforms that are being proposed to rein in these data-opolies. Part IV concludes with signs of hope.
I. Current Consensus
Today there is a consensus among policymakers and enforcers on several attributes of the digital platform economy, including:
The Importance of Scale, Network Effects, and Data. Economies of scale “arise where average costs decrease with increasing scale”and production. We see economies of scale in the brick-and-mortar economy, such as newspapers, automobiles, tissue paper, and the manufacturing of military airborne radios. But, as the EU Special Advisors Report noted,
the digital world pushes this phenomenon to the extreme. Once created, information can be transmitted to a large number of people at very low cost. Once a search engine or mapping service has been developed and is running, it can usually serve fairly cheaply hundreds of thousands of users. This is not to say that servicing these users is not costly but rather that the costs rise much more slowly than the number of users.
As the United States and State Attorneys General allege in their recent monopolization complaint against Google, “[d]eveloping a general search index of this scale, as well as viable search algorithms, would require an upfront investment of billions of dollars. The costs for maintaining a scaled general search business can reach hundreds of millions of dollars a year.” Likewise, while Facebook toppled Myspace, it is much harder for any entrant to displace Facebook at its current scale: “Facebook’s internal documents confirm that it is very difficult to win users with a social networking product built around a particular social ‘mechanic’ (i.e., a particular way to connect and interact with others, such as photo-sharing) that is already being used by an incumbent with dominant scale.”
Besides economies of scale, there are two other significant barriers to entry in many digital platform markets: network effects and quickly accessing (velocity) a large volume and variety of data.As the States allege in their complaint against Facebook, “The more data Facebook accumulates by surveilling the activities of its users and the more time the company convinces users to spend engaging on Facebook services, the more money the company makes through its advertising business.”
Winner-Take-All-or-Most Markets. Because of these economies of scale, multiple network effects, and data-opolies’ extraction of data from multiple avenues, digital platform markets can quickly tip in one or two companies’ favor. The mobile operating system market, for example, went from multiple competitors in 2010 (with Google and Apple collectively accounting for 39 percent of unit sales), to a duopoly eight years later. Likewise, in 2008, which was two years after its launch, Facebook had already eclipsed Myspace in the number of active users. As the States allege in their antitrust complaint, Facebook aimed to tip every other geographic market to its favor:
In October 2008, responding to a request from Facebook Chief Operating Officer Sheryl Sandberg to top Facebook executives, the Vice President of Partnerships wrote that one of his goals was to “try to tip every single major market where FB hasn’t yet tipped … .” He listed nine countries or regions of the world that fell into that category. The United States was conspicuously absent because Facebook was well aware of its growing power in the United States.
The Durability of GAFA’s Power – Once these markets tip in the platforms’ favor, their market power is quite durable. Although we often hear that competition is a click away, the reality is otherwise. The current market valuations of Google, Apple, Facebook, and Amazon suggest that investors do not anticipate disruption that would radically change their dominance. The Australian competition authority calculated in 2019 that “50-67% of the current share price for Facebook can be attributed to expectations for future growth” and “46-64% of the current share price for Google can be attributed to expectations for future growth.” As the U.K.’s competition authority calculated, the global returns on capital were over 40 percent for Google and 50 percent for Facebook, which are well above their cost of capital, which was 9 percent. Google’s profit margins were “greater than 20% for nine out of the last 10 years, close to three times larger than the average for a U.S. firm.”
Apple likewise reaps monopoly profits, with its services category enjoying the highest margins (63.7% in the fiscal year 2019 and 67.2% for Apple’s quarter ending in June 2020). Indeed, the House Report noted concerns of Apple, during the pandemic, canvassing its App Store “to extract commissions from businesses that have been forced to change their business model in order to survive during the pandemic.”
Amazon, which extracts monopoly fees from third-party sellers on its platform, also took advantage of the pandemic to exploit these sellers:
As the COVID-19 pandemic pushes more American shoppers online, Amazon’s market power has grown. Evidence shows that Amazon is willing to use its increased market power in e-commerce during this crisis to exert pressure on suppliers and favor its own first-party products over those sold by third-party sellers. Amazon initially responded to the sudden surge in sales by refusing to accept or deliver non-essential supplies from its third-party sellers—a stance that would seem reasonable except that Amazon continued to ship its own non-essential products while restricting third-party sellers’ ability to use alternative distribution channels to continue selling through Prime.
These data-opolies’ profits are far higher to reward shareholders with a fair return; they are “staggering,” and represent the platforms’ ability to exploit their monopoly power. We ultimately pay the price.
II. Understanding the Data-opolies’ Playbook – How to Acquire and Sustain a Durable Competitive Advantage
So how did these data-opolies become so powerful, and how were they able to leverage their dominance into other markets? The conventional wisdom is that these powerful platforms take advantage of pre-existing market forces, such as network effects, passively. The companies’ executives are, in effect, the superior surfers who pick the right surfboard for the right wave, and shift their weight and feet while riding the wave for that extra boost of acceleration and momentum. The four companies picked the right products and services – whether Google Maps, Apple iTunes, Amazon Prime, or Facebook Messenger — for the market, adjusted their services along the way, and used the underlying network effects to propel the company to dominance. That is legal under E.U. and U.S. antitrust law. As Judge Learned Hand wrote in an influential legal opinion, “The successful competitor, having been urged to compete, must not be turned upon when he wins.”
But the newly uncovered evidence (including the data-opolies’ internal documents) from recent government reports and the government’s antitrust complaints reveal a more chilling and sobering reality. These platforms do not simply rely on business acumen and superior products. Instead, they all use the same anticompetitive playbook to attain and extend their dominance.
A. The Now-Casting Radar
Google, Apple, Facebook, and Amazon misappropriate data that they collect from us and the companies that rely on their platforms to sustain their competitive advantage. They closely track real-time data across markets, which provide them with near-perfect market intelligence of potential and actual competitors. So Google and Facebook, for example, can see what apps we download and whether these apps pose a potential threat to their dominance. Each platform weaponizes the data to identify nascent competitive threats, a tool we call the nowcasting radar.
The internal corporate documents uncovered in the House Report show how Google, Facebook, Apple, and Amazon capture both personal data and commercially-sensitive data about rivals to provide themselves multiple competitive advantages, which earlier monopolies lacked:
the investigation revealed that the dominant platforms have misappropriated the data of third parties that rely on their platforms, effectively collecting information from customers only to weaponize it against them as rivals.
For example, the investigation produced documents showing that Google used the Android operating system to closely track usage trends and growth patterns of third-party apps—near-perfect market intelligence that Google can use to gain an edge over those same apps.
Facebook used its platform tools to identify and then acquire fast-growing third-party apps, thwarting competitive threats at key moments.
A former Amazon employee told the Subcommittee that Amazon has used the data of third-party merchants to inform Amazon’s own private label strategy, identifying which third-party products were selling well and then introducing copycat versions.
Amazon initially denied doing this to Congress, until it was caught. In November 2020, the European Commission announced its preliminary findings that Amazon violated the competition laws by systemically using non-public, commercially-sensitive information of independent sellers who sell on Amazon’s marketplace, to benefit Amazon’s own competing retail businesses.
To appreciate how this near-perfect market intelligence can chill innovation and competition, consider Google’s “Lockbox” Project. Google used the data flowing through its Android mobile operating system to closely monitor competing apps:
Since at least 2012, Google has collected installation metrics for third-party apps, which it combined with data analyzing search queries.
These early documents outline the early stages of Google’s “Lockbox,” a project to collate data that provided Google with a range of competitor insights and market intelligence, ranging from an understanding of how installation of the Amazon app corresponded to a trend in Amazon shopping queries to a close tracking of trends relating to Candy Crush and Angry Birds. While Lockbox began as a way to collect data on the installation of apps, Google quickly realized it could harness it to yield other insights as well. One document from 2013 identified a list of additional data points that the company desired, including “[m]ore signals (including uninstalls and device app mapping)” and “reliable and long term app usage data,” for which the document noted Google Play Services could help. In short, Google began seeking out ways to collect specific usage data that enabled Google to track not just which apps a user has, but also how frequently they use the apps and for how long. Documents obtained by the Subcommittee suggest that by 2015, Google’s Lockbox data had succeeded in tracking more than just install rates. Google’s internal reports show that Google was tracking in real-time the average number of days users were active on any particular app, as well as their “total time spent” in first- and third-party apps. Google subsequently used this data to benchmark the company’s first-party apps against third-party apps, suggesting that Google was using Lockbox data to assess the relative strengths and weaknesses of its own offerings.
Google’s documents show how Lockbox furnishes Google with near-perfect market intelligence, which Google has used to inform strategic moves and potential business transactions.
So the data-opolies use the “near-perfect market intelligence” from their nowcasting radar offensively (to favor their products, services, and apps and disadvantage competing products and services) and defensively (to aim their sniper rifle at potential threats as well as weaker rivals).
B. Platforms’ Acquire-Copy-or-Kill (ACK) Strategy
Once the powerful platforms identify a nascent competitive threat, they typically employ an Acquire-Copy-or-Kill (ACK) strategy.
Killer Acquisitions. As Facebook’s CEO said in an internal e-mail, “it is better to buy than compete.” The data-opolies acquired many of these smaller rivals to protect and expand their dominance, a tactic policymakers have dubbed “killer acquisitions.” As the House Report notes, since 1998, Google, Amazon, Facebook, and Apple have purchased over 500 companies. Google alone “purchased well over 260 companies—a figure that likely understates the full breadth of Google’s acquisitions, given that many of the firm’s purchases have gone unreported.”
The antitrust agencies did not block a single merger, which is troubling given the incriminating evidence of the House subcommittee found. As the House Report notes, the data-opolies used the network effects offensively to acquire these threats and deprive others of gaining scale:
Mr. Zuckerberg told the company’s Chief Financial Officer in 2012 that network effects and winner-take-all markets were a motivating factor in acquiring competitive threats like Instagram. He said: [T]here are network effects around social products and a finite number of different social mechanics to invent. Once someone wins at a specific mechanic, it’s difficult for others to supplant them without doing something different. It’s possible someone beats Instagram by building something that is better to the point that they get network migration, but this is harder as long as Instagram keeps running as a product … one way of looking at this is that what we’re really buying is time. Even if some new competitors springs[sic] up, buying Instagram now … will give us a year or more to integrate their dynamics before anyone can get close to their scale again. Within that time, if we incorporate the social mechanics they were using, those new products won’t get much traction since we’ll already have their mechanics deployed at scale… .
Mr. Zuckerberg also stressed the competitive significance of having a first-mover advantage in terms of network effects prior to acquiring WhatsApp. In the context of market strategies for Messenger competing with WhatsApp, Mr. Zuckerberg told the company’s growth and product management teams that “being first is how you build a brand and a network effect.”
So, the killer acquisitions strategy not only extinguishes competitive threats, but it can also keep them “out of the hands of other firms that are well-positioned to use them to compete” and prevent competitors or potential competitors “from having access to next generation technology that might threaten” the data-opoly. As the states allege in their complaint against Facebook, we ultimately pay the price with less competition, less investment, less innovation, and fewer choices.
Copy to Deprive Scale. If the start-up, like Snapchat, rebuffs the acquisition, they could incur the data-opoly’s wrath. Facebook, for example, coupled “its acquisition strategy with exclusionary tactics that snuffed out competitive threats and sent the message to technology firms that, in the words of one participant, if you stepped into Facebook’s turf or resisted pressure to sell, Zuckerberg would go into ‘destroy mode’ subjecting your business to the ‘wrath of Mark.’”
In 2013, Snapchat rebuffed Facebook’s $3 billion offer. Thereafter, Facebook’s Instagram “introduced the Instagram Stories feature, which allows users to post content that is available for only 24 hours, and which was ‘nearly identical to the central feed in Snapchat, which [was] also called Stories.’” Within one year of its introduction, Instagram Stories “had more daily active users (200 million) than Snapchat Stories (161 million),” and by 2018, Instagram Stories had doubled the number of its users over Snapchat.
The dominant platform uses network effects offensively by copying the start-up’s product or service to deprive the rival of scale. Despite Facebook’s privacy scandals, it is hard for Facebook users to switch to other social networks. Unless most, if not all, of their friends and acquaintances also switch to the same network, no one will likely switch. So, even if a rival platform offers better features or privacy protections, one will not switch unless one can also convince others to switch to the innovative start-up. The data-opolies count on this “stickiness,” as the House Report found,
… an internal survey prepared for Facebook’s senior management team about Google+ explained that “[p]eople who are big fans of G+ are having a hard time convincing their friends to participate because … switching costs would be high due to friend density on Facebook.” And in 2012, the company indicated that people’s significant time investment on Facebook building their identity and connections on the platform increased the company’s “stickiness.”
To increase stickiness further, the data-opoly can copy the innovative platform’s features. For every platform, there are only a limited number of innovative features that are immediately available. By cloning the innovative features, the data-opoly further reduces the risk that users will switch. This can also reduce the incentives for start-ups to innovate and enter any market that the data-opoly might perceive as potentially threatening their power.
So, the data-opoly cannibalizes, rather than innovates. As Facebook noted internally,
Even if some new competitors springs[sic] up, buying Instagram, Path, Foursquare, etc [sic] now will give us a year or more to integrate their dynamics before anyone can get close to their scale again. Within that time, if we incorporate the social mechanics they were using, those new products won’t get much traction since we’ll already have their mechanics deployed at scale.
Kill the Threat. Alternatively, the data-opolies can kill the start-up using myriad anticompetitive means, including hindering the start-up from achieving scale, scraping its content, cutting off its oxygen supply by reducing the start-up product’s interoperability with the dominant platform’s, and preferencing the data-opolies’ products and making it harder for consumers to find and use the competing product.
Google, for example, favorably positioned and displayed its “comparison shopping” services on the first page of its general search results, which Google internally recognized as inferior,while demoting superior offerings by rivals to the fourth page of results or even further down. This self-preferencing dries up the traffic to the rivals’ websites. The European Commission found Google’s self-preferencing led to “sudden drops of traffic to certain rival [comparative shopping] websites of 85% in the United Kingdom, up to 92% in Germany and 80% in France.”
This self-preferencing is “network effects in reverse.” Google, in reducing traffic to its rivals’ flight information, comparison shopping services, or restaurant reviews websites, causes them to have fewer consumers, which leads to fewer listings and less revenue, which leads to reduced investment—which, in turn, contributes to a further decline in traffic. To avoid this downward spiral, the rivals must recover their lost traffic, and often the only option is by advertising on Google with paid search ads. By forcing its rivals to advertise on its platforms, Google can then glean competitively-sensitive data about its rivals, thereby bolstering its now-casting radar.
But it gets worse. To further thwart rivals from capturing more ad revenues, Google, at times, scraped (basically stole) their sites’ content. Google gave these third-party websites a Hobson’s choice: either “permit Google to take their content, or else be removed from Google’s search results entirely.”
Ultimately competition and society pay the price from this self-preferencing, as the House Report notes:
Over the course of the investigation, numerous third parties also told the Subcommittee that self-preferencing and discriminatory treatment by the dominant platforms forced businesses to lay off employees and divert resources away from developing new products and towards paying a dominant platform for advertisements or other ancillary services. They added that some of the harmful business practices of the platforms discouraged investors from supporting their business and made it challenging to grow and sustain a business even with highly popular products. Without the opportunity to compete fairly, businesses and entrepreneurs are dissuaded from investing and, over the long term, innovation suffers.
C. Colonizing New Digital Platform Markets
No monopoly wants to repeat its predecessors’ mistakes, especially missteps that contributed to the decline in power. One fear is missing important market trends. By 2014, many U.S. adults were spending more time on their smartphones (on average 34 hours per month) than on their personal computers (27 hours on average). Microsoft, while monopolizing the PC operating system market for years, failed to timely develop an operating system for mobile phones. When it introduced its Windows phone, the network effects were already working in Google’s and Apple’s favor.
So too we’ll likely migrate from our phones and spend more time on other platforms, such as wearables, digital personal assistants, gaming and virtual reality, and driverless cars. Google, for example, raises this risk in its 2019 annual report: “People access the Internet through a growing variety of devices such as desktop computers, mobile phones, smartphones, laptops and tablets, video game consoles, voice-activated speakers, wearables, automobiles, and television-streaming devices. Our products and services may be less popular on these new interfaces.”Facebook also raises this risk in its 2019 annual report and internally.
Concerned about missing the next wave, the data-opolies follow a similar pattern of colonizing new digital platforms where users may eventually migrate, and execute their anticompetitive Venus flytrap playbook.
The Venus flytrap secretes a sweet sap to attract insects. Once the plant’s leaves snap shut, the entrapped insects have little chance to escape. “The prey would need to overpower the ‘escaping’ force, which is very strong and can reach up to 4 N.”
So too the data-opolies open their newly colonized platforms with inducements to attract developers, users, and manufacturers. Once they dominate that market, they close their platform to extract supra-competitive fees from sellers, app developers, and advertisers, as well as data from users. The government’s antitrust complaint showed how Google deployed this tactic to dominate the mobile phone operating system market:
In 2007, Google released the Android code for free under an open-source license. Being “open source” means that anyone can access the source code and use it to make their own, modified operating system—a “fork.” This was key to Android’s adoption.
First, Google’s apparent lack of control over an open-source operating system attracted skeptical manufacturers and carriers of mobile phones to use Android instead of the other choices then available. As the Android team leader observed to Google’s board of directors, “Google was historically seen as a threat” to these distributors. But an open-source model suggested that they—and not Google—would ultimately retain control over their devices and the app ecosystem on those devices.
Second, once enough major distributors agreed to use Android, the operating system attracted developers looking for wide distribution of their apps. As more app developers focused their efforts on designing Android apps, Android became more attractive to consumers, which in turn led even more developers to design for Android. The result was a must-have ecosystem of Android apps.
Third, to help the Android ecosystem achieve critical mass and to advance the network effects, Google “shared” its search advertising and app store revenues with distributors as further inducement to give up control. As one senior executive explained about Android Market, an earlier name for Google’s app store, “Android Market is a bitter pill for carriers, and generous revenue share is the sugar that makes it go down smoother.” In other words, beginning over ten years ago, Google used revenue sharing to attract partners to Android; as discussed below, Google uses revenue sharing to keep them locked in today.
By 2010, the Android team leader noted that “Android is poised for world domination—the success story of the decade.” He was right; the strategy worked./
Once dominant, Google used its control over its app store to extract rents. If phone manufacturers wanted interoperability with Google’s apps and wanted Google’s app store loaded on their phones, then they had to use Google’s version of Android (and not a competing version) and had to preload and feature Google’s search engine, browser, and other apps (and not competitors’). So Google’s Android began as an open mobile phone operating system, which once dominant, was snapped shut with anticompetitive tying and anti-fragmentation agreements.
Google repeated this strategy for its other products. Its search engine, which was once “a ‘turnstile’ to the rest of the web” evolved into “a ‘walled garden’ that increasingly keeps users within its sites.”
Likewise, for years, Google Maps was open, as Google “offered a free tier of the Maps API, incentivizing developers to build their apps with Google Maps.” After acquiring its only significant rival, Waze, Google controlled an estimated 81 percent share of the market for navigation mapping services. With its dominance secured, Google in 2018 “introduced a single ‘pay-as-you-go’ pricing plan for the core mapping APIs.” This shift, which “dramatically reduced the number of free Maps API calls a firm could make—from 25,000 per day to around 930 per day,” amounted “to a price increase of 1,400%.”
After dominating these platforms, Google then turned its sights to colonize other platforms, where it can ensure that its search engine is the preferred (or only) option. As the United States alleged, “Google is now positioning itself to dominate search access points on the next generation of search platforms: internet-enabled devices such as smart speakers, home appliances, and automobiles (so-called internet-of-things, or IoT, devices).”
As the states and FTC allege in their complaints, Facebook employed a similar Venus flytrap strategy for its social network.
The result is that the data-opolies expand their long shadow, acquiring, copying, or killing off potential threats, chilling innovation, taxing all the businesses reliant on their platforms, extracting our data, and fostering our addiction to their products.
III. How Can We Rein in these Data-opolies?
In their annual reports, the data-opolies identify intense competition as a risk factor. Despite these claims, their monopolies are secure. Even during the current pandemic, Amazon, Apple, Google, and Facebook raked in “$38 billion in profits on nearly $240 billion in revenue” in the third quarter of 2020.
Antitrust law is not significantly deterring these data-opolies. Earlier in 2020, while under the microscope of the United States and other antitrust authorities who were investigating Google’s anticompetitive conduct, Google actually coerced distributors into contracts that were “even more exclusionary than the agreements they replaced.”
The emerging consensus is that the data-opolies will continue to leverage their power into other markets, and the digital platform economy will not perform efficiently or in our interest. There are multiple market failures, including:
(i) In leveraging their power to new markets, data-opolies are expanding, rather than shrinking.
(ii) Privacy competition is stifled. In many markets where there is competition, it is a toxic variety. Companies compete to extract more data from us (but not for us).
(iii) The data-opolies’ products are intentionally addictive and thereby erode individuals’ ability to make free choices. A former Facebook product manager told the House Subcommittee staff, that as a product manager at Facebook “your only job is to get an extra minute. It’s immoral. They don’t ask where it’s coming from. They can monetize a minute of activity at a certain rate. So the only metric is getting another minute.”
If the current laws are inadequate to address the current market failures, what can be done? Several policy reforms address the data-opolies’ anticompetitive playbook. Other policies seek to ameliorate their anticompetitive effects, and a few address the source of their power.
The most promising remedies proposed thus far include the following:
First is a greater need for a more proactive antitrust review of dominant platforms. The 2020 House Antitrust Report is as much an indictment on the U.S. antitrust enforcers, as the data-opolies. In its investigation, the House Subcommittee “uncovered evidence that the antitrust agencies failed, at key occasions, to stop monopolists from rolling up their competitors and failed to protect the American people from abuses of monopoly power. Forceful agency action is critical.”
We are already witnessing an antitrust resurgence with the announcement of task forces in 2019 by the U.S. Department of Justice and Federal Trade Commission; administrative and legislative hearings; investigations by numerous state attorneys general, investigations by European Commission, EU Member States, and competition authorities in Australia, India, Argentina, Brazil, and Korea. The monopolization cases against Google and Facebook, the first significant monopolization cases in the United States over twenty years, follow the European Commission’s three cases against Google and Germany’s case against Facebook, with more cases likely.
Second is updating and strengthening the competition laws.One problem in the United States is the Supreme Court’s rambling the wilds of economic theory, and the lower courts picking up the Court’s dicta to make it harder to enforce the antitrust laws. As the House Republicans noted in their separate report, it “is appropriate for Congress to remind the agencies and the courts of the original Congressional intent behind the antitrust laws, including that our enforcement agencies should be able to bring cases, like a review of Facebook’s acquisition of Instagram, based on potential competition doctrine without facing impossible evidentiary burdens.”
The House Report recommends that Congress consider reasserting antitrust’s anti-monopoly goals. As data-opolies’ anticompetitive actions pose economic, social, and political risks, so too Congress should “consider reasserting the original intent and broad goals of the antitrust laws, by clarifying that they are designed to protect not just consumers, but also workers, entrepreneurs, independent businesses, open markets, a fair economy, and democratic ideals.” The House Report also recommends rehabilitating monopolization law by, among other things, incorporating Europe’s abuse of dominance standard.To get at the data-opolies’ anticompetitive playbook, the House Report calls for revitalizing current antitrust doctrines that the courts have marginalized, such as
· the monopoly leveraging theory (where the data-opolies leverage their power to colonize new platforms),
· duty to deal/essential facilities doctrine (so that the data-opoly cannot hinder or eliminate interoperability with other services, such as Facebook preventing users of the video-sharing platform Vine to find their friends they already knew on Facebook’s platform through Facebook’s “Find Contacts” feature),
· tying claims (so that Google cannot coerce phone manufacturers into preloading on their smartphones and setting as the default Google’s search engine, Chrome browser, and other apps as conditions for receiving the Google Play app store),
· predatory pricing standards (by eliminating the Supreme Court’s recoupment element, which has made successfully bringing a case impossible, even with evidence of predation, such as Amazon’s tactics against Diapers.com),
· stronger standards against the data-opolies’ self-preferencing their products and services (so that Google cannot favor its vertical searches, such as Google Flights, Google Hotel Ads, and Google Local Search One-Boxes, by placing them prominently at the top of the search results, where the user is more inclined to click),and
· stronger standards against anticompetitive product designs.
The House Report also recommends cutting back much of the Supreme Court’s bad dicta that have mired antitrust enforcement. So, rather than having to prove market power with circumstantial evidence (such as the plaintiff showing the defendant’s high market share in a relevant antitrust market, a lengthy, uncertain process that primarily benefits testifying economic experts), the agencies and courts can rely on direct evidence of monopoly power (such as evidence that the platform is coercing others to do things they would not have to do in a competitive market).
Third are measures to deter data hoarding. These include measures to improve the flow of data to rivals, including promoting multi-homing by users, targeting data-opolies’ use of individuals’ default bias to entrench their market power (such as Google paying Apple $12 billion to be the default search engine on Safari), reducing switching costs (such as improving data portability and interoperability), and imposing, at times, a duty for data-opolies to share data with rivals, while safeguarding individuals’ privacy interests.
Fourth is improving privacy protections. Notice-and-consent privacy policies have failed. Users need to regain their control over their privacy and data and prevent the data-opolies from collecting far more data than they could if competition were robust and healthy. While the competition policies differ on what measures must be undertaken, they recognize that stronger privacy protections are necessary, but not sufficient, to prevent the data-opolies’ data hoarding.
Fifth is targeting killer acquisitions. Every jurisdiction that has studied these digital platform markets has called for greater antitrust scrutiny of data-driven and platform-related mergers and acquisitions, such as the European Commission’s and DOJ’s scrutiny of Google’s proposed acquisition of Fitbit. To prevent data-opolies from acquiring these nascent competitive threats, the House Report recommends clarifying that proving harm post-merger would not require the agency to prove that the nascent competitor would have been a successful entrant in a but-for world. Moreover, the House Report proposes “a presumption against acquisitions of startups by dominant firms, particularly those that serve as direct competitors, as well as those operating in adjacent or related markets.”
Sixth is ex-ante codes of conduct enforced by a regulatory agency. Many companies live in fear today of the four powerful platforms. A change in the platforms’ algorithms can dry up their search traffic and reduce their visibility, whether in the app store or Amazon’s shopping network. Given the data-opolies’ superior bargaining power over advertisers, website publishers, app developers, news organizations, and individuals, the aim here is to improve the process for redressing the market participants’ complaints involving these platforms, as antitrust enforcement typically takes too long, the relief often comes too late, and happens too infrequently to be relied upon. As it is difficult, outside of copyright, trademark, and patent law, to prevent dominant firms from copying their rivals, these policy proposals turn to the K in the ACK strategy by making it harder for the dominant platforms to kill off these smaller rivals and wield their power against those that rely on the platforms. So, the U.K. and Australian competition authorities have urged for regulations, ex-ante codes of conduct, and an independent ombudsman to redress the anti-competitive behavior of these data-opolies. The independent agency would quickly resolve these disputes using the code of conduct.
Seventh is to expand the enforcer’s toolbox to prevent the platforms from colonizing and dominating new platforms. This includes considering new theories of harm under the existing laws, including “the use of covert tracking and data collection to exclude competitors” and incorporating “into their analysis the impact of data on alternative dimensions of competition, such as quality and innovation.” It also involves creating new competition tools, such as ones “to deal with structural competition problems across markets which cannot be tackled or addressed in the most effective manner on the basis of the current competition rules (e.g. preventing markets from tipping).” So rather than waiting for the colonized platforms (like wearables or digital assistants Alexa, Siri, and Google Home) to tip to one or two of these data-oplies, the agency can intercede with interim measures and market sector reviews.
Eighth are policies to address specific problems in markets dominated by these data-opolies. For example, measures are sought to increase transparency in the online advertising markets. Other measures seek to reduce the regulatory imbalance in how the traditional news media is treated versus the digital platforms in terms of content.
Ninth are structural remedies. As enforcers increasingly recognize, behavioral remedies are generally less effective than structural remedies. So competition authorities are weighing proposals to break-up the platforms, or spin off parts of their businesses. The FTC’s and states’ antitrust cases against Facebook, for example, are seeking “divestiture of assets, divestiture or reconstruction of businesses (including, but not limited to, Instagram and/or WhatsApp).”
Tenth is cooperation. No agency can undertake this on its own. The privacy, consumer protection, and antitrust agencies around the globe must collaborate to develop a “common strategy” to rein in these data-opolies. We are already seeing greater convergence with the House Report relying on the findings of the EU, UK, and Australian authorities, and the work of the International Competition Network and OECD.
2020 was a horrible year on so many levels, but there are signs of hope for reinvigorating competition and returning the political and economic power from the data-polies to citizens and companies.
In contrast to the divisive partisanship in 2020 on so many issues, antitrust in 2020 was one area of bi-partisanship with thoughtful concerns raised on both sides of the Congressional aisle.
The antitrust complaints against Google and Facebook are not only well-pled but modern. The conventional concerns about monopolies are higher prices and lower output. But the Complaints consider the data-opolies’ impact on privacy and data collection. The Google Complaint also incorporates the insights of behavioral economics on the power of defaults.
In addition to the first significant monopolization cases – against Google and Facebook – in over 20 years, 2020 was also a year where the dangers of the platforms were effectively evoked through the highly popular Netflix documentary, The Social Dilemma, and numerous well-written books and articles on the economic, social, and political harms of these powerful platforms.
With strong intellectual leadership at DOJ Antitrust Division and FTC, there is a good chance of legislative reform during the Biden administration.
But change can also be effectuated from within these data-opolies. Neo-classical economic theory posits that individuals pursue their self-interest, namely wealth maximization. So one would expect that the data-opolies’ employees would all support political candidates who wouldn’t threaten their firms’ monopoly profits. After all, the greater the monopoly profits, the greater the likelihood that the employees would profit thereby. One wouldn’t expect many of the data-opolies’ employees to support politicians who vow to strengthen the antitrust laws, and certainly not politicians who promise to break up their companies.
But Google’s, Amazon’s, Facebook’s, and Apple’s employees financially supported in the 2020 presidential primaries two progressive Democratic candidates, Bernie Sanders and Elizabeth Warren, who promised to break them up.
Facebook employees donated $29,233 to Donald Trump in contrast to $248,672 to Bernie Sanders, and $89,304 to Elizabeth Warren.
Google same story. The top individual recipients, besides Joe Biden ($3,661,162), were Bernie Sanders ($989,682) and Elizabeth Warren ($701,658). Donald Trump, in contrast, received only $68,748.
Likewise, for Amazon, the top individual recipients in the 2020 elections were Joe Biden ($1,737,402), Bernie Sanders ($803,200), and Elizabeth Warren ($242,532). Donald Trump, in contrast, received $164,174.
The top individual recipients from Apple employees, besides Joe Biden ($1,398,859), were Bernie Sanders ($389,051) and Elizabeth Warren ($192,607). Donald Trump, in contrast, received $63,650.
One explanation is that Donald Trump is tougher on antitrust, with the Obama administration giving Big Tech a free pass (outside of collusion). After all, the FTC, during the Obama administration, overruled its legal staff, in not challenging Google’s anticompetitive practices. But during the presidential primaries, it was uncertain that the Trump administration would sue the data-opolies, and antitrust enforcement during the Trump administration was otherwise uneven and controversial.Moreover, for the past 40 years, Republican administrations, unlike the Eisenhower and Nixon administrations, have been tolerant of monopolies and their abuses. The Department of Justice, for example, brought only four monopolization cases during the entire twenty-year period of the Reagan, Bush Sr., and George W. Bush administrations.
So, what is going on here? It is unlikely that so many GAFA employees suffer from Stockholm Syndrome, in identifying with the goals of their oppressors.
Most of us desire purposeful work. One recent survey found a high correlation between well-being and purposeful work: “Whereas only 6% of those who have low levels of purpose in their work have high levels of overall wellbeing, fully 59% of those with high purpose in work have high wellbeing.”
But as some have observed of the dominant social network, “Facebook created a town hall for fighting.” Facebook built a machine to foster divisive, extreme positions to attract our attention and data. Not surprisingly, many Facebook employees are increasingly disillusioned, according to one internal survey:
Only 51% of respondents said they believed that Facebook was having a positive impact on the world, down 23 percentage points from the company’s last survey in May  and down 5.5 percentage points from the same period last year . In response to a question about the company’s leadership, only 56% of employees had a favorable response, compared to 76% in May  and more than 60% last year 
They too, as we see from the Facebook complaints, question the ethics of their employer’s actions. It must be hard to go home and feel good about bullying and destroying smaller rivals, having your platform be weaponized to destabilize democracies, and surveilling and manipulating individuals to maximize ad revenues. So, the workers may desire change for the betterment of their employers Google, Apple, Facebook, and Amazon and society.
Few would want to live in a dystopia, where we labor as data-serfs for the data-opolies. We would rather use our talents for the betterment of others, creating as Harvard Business School Professor Michael Porter calls, shared value in providing “economic value in a way that also creates value for society by addressing its needs and challenges.” We would prefer to compete in markets where the rules of the game are clear and fair and apply to all. We want to preserve opportunities for our children for meaningful, purposeful work.
So, we don’t have to live in a post-privacy plutocracy. But to emerge from this antitrust winter, we must continue to demand antitrust reform and enforcement, along with sufficient privacy protections.
 Max Greenwood, Majority Supports Antitrust Review of Tech Giants: Poll, The Hill.com, Aug. 5, 2019, https://thehill.com/policy/technology/456221-majority-supports-antitrust-review-of-tech-giants-poll
 Consumer Reports, Press Release: Consumer Reports survey finds that most Americans support government regulation of online platforms, Sept. 24, 2020, https://advocacy.consumerreports.org/press_release/consumer-reports-survey-finds-that-most-americans-support-government-regulation-of-online-platforms/.
 Investigation of Competition in Digital Markets, Majority Staff Report and Recommendations, Subcommittee on Antitrust, Commercial and Administrative Law of the Committee on the Judiciary (Oct. 2020), https://judiciary.house.gov/up… [hereinafter House Report].
 UK Competition and Markets Authority, Online Platforms and Digital Advertising Market Study: Market Study Final Report ¶ 23 (1 July 2020), https://assets.publishing.service.gov.uk/media/5fa557668fa8f5788db46efc/Final_report_Digital_ALT_TEXT.pdf[hereinafter CMA Final Report].
 See, e.g., Compl., United States v. United Technologies, Case 1:20-cv-00824 (D.D.C filed March 26, 2020), https://www.justice.gov/atr/case-document/file/1262896/download.
 Jacques Crémer, Yves-Alexandre de Montjoye & Heike Schweitzer, Special Advisers’ Report: Digital Policy for the Digital Era at 20 (2019), https://ec.europa.eu/competition/publications/reports/kd0419345enn.pdf; see also ICN Unilateral Conduct Working Group, Report on the Results of the ICN Survey on Dominance/Substantial Market Power in Digital Markets at 5 (July 2020), https://www.internationalcompetitionnetwork.org/wp-content/uploads/2020/07/UCWG-Report-on-dominance-in-digital-markets.pdf [hereinafter ICN Study].
 Compl. ¶ 22, United States v. Google, Case 1:20-cv-03010 (D.D.C. filed Oct. 20, 2020), https://www.justice.gov/opa/pr…[hereinafter Google Compl.]; see also id. at ¶ 35 (“Google has long recognized that without adequate scale its rivals cannot compete. Greater scale improves the quality of a general search engine’s algorithms, expands the audience reach of a search advertising business, and generates greater revenue and profits”).
 Compl. ¶ 6, FTC v. Facebook (D.C.C. filed Dec. 9, 2020), https://www.ftc.gov/enforcement/cases-proceedings/191-0134/facebook-inc-ftc-v [hereinafter FTC Facebook Compl.].
 See, e.g., ICN Study at 23-24; FTC Facebook Compl. ¶ 6; States FTC Compl. ¶ 41; House Report at 17, 37-38, 40-41, 42-44.
 Compl. ¶ 3, New York v. Facebook (D.D.C. filed Dec. 9, 2020), https://ag.ny.gov/press-release/2020/attorney-general-james-leads-multistate-lawsuit-seeking-end-facebooks-illegal[hereinafter States Facebook Compl.].
 House Report at 37-38.
 Felix Richter, Smartphone OS: The Smartphone Duopoly, Statista, May 20, 2019, https://www-statista-com.proxy.lib.utk.edu/chart/3268/smartphone-os-market-share/.
 States Facebook Compl. ¶ 67.
 Australian Competition and Consumer Commission, Digital Platforms Inquiry – Final Report at 7 (July 26, 2019), https://www.accc.gov.au/publications/digital-platforms-inquiry-final-report [hereinafter ACCC Final Report] (based on the share price for Alphabet and Facebook on 20 June 2019).
 CMA Final Report at ¶¶ 12 & 2.78.
 House Report at 175.
 House Report at 337.
 House Report at 351.
 House Report at 261.
 FTC Facebook Compl. ¶ 4 (characterizing Facebook’s 2019 profits of over $18.5 billion).
 CMA Final Report at ¶ 2.80.
 United States v. Aluminum Co. of Am., 148 F.2d 416, 430 (2d Cir. 1945).
 Maurice E. Stucke & Allen P. Grunes, Big Data and Competition Policy ¶ 18.28 (2016).
 House Report at 379.
 Dana Mattioli, Amazon Scooped Up Data From Its Own Sellers to Launch Competing Products, Wall St. J., April 23, 2020, https://www.wsj.com/articles/amazon-scooped-up-data-from-its-own-sellers-to-launch-competing-products-11587650015.
 European Commission, Press Release, Antitrust: Commission Sends Statement of Objections to Amazon for the Use of Non-Public Independent Seller Data and Opens Second Investigation into Its E-Commerce Business Practices (10 November 2020), https://ec.europa.eu/commission/presscorner/detail/en/ip_20_2077.
 House Report at 218 (footnotes omitted).
 FTC Facebook Compl. ¶ 72.
 House Report at 11.
 House Report at 174.
 House Report at 143.
 States Facebook Compl. ¶ 185.
 States Facebook Compl. ¶ 185.
 States Facebook Compl. ¶ 6.
 House Report at 164.
 House Report at 164-65.
 FTC Facebook Compl. ¶¶ 65-66.
 House Report at 145.
 House Report at 152.
 House Report at 187 & 191. As one Google employee internally acknowledged, “if Google ranked its own content according to the same criteria that it applied to competitors, ‘it will never rank.’” House Report at 190.
 Case AT.39740 — Google Search (Shopping), https://ec.europa.eu/competition/elojade/isef/case_details.cfm?proc_code=1_39740.
 European Commission, Press release, Antitrust: Commission Fines Google €2.42 Billion for Abusing Dominance as Search Engine by Giving Illegal Advantage to Own Comparison Shopping Service (27 June 2017), https://ec.europa.eu/commission/presscorner/detail/en/IP_17_1784.
 House Report at 189-90.
 House Report at 192.
 House Report at 192.
 House Report at 184.
 House Report at 382-83.
 Greg Sterling, Nielsen: More Time On Internet Through Smartphones Than PCs, Marketing Land, Feb. 11, 2014 at 9:57 am, https://marketingland.com/nielsen-time-accessing-internet-smartphones-pcs-73683.
 Alphabet Form 10-K for the fiscal year ended December 31, 2019, https://www.sec.gov/Archives/edgar/data/1652044/000165204420000008/goog10-k2019.htm, at p. 13.
 Facebook Form 10-K for the fiscal year ended December 31, 2019, https://sec.report/Document/0001326801-20-000013/, at p. 11 (identifying the risk that “users adopt new technologies where our products may be displaced in favor of other products or services, or may not be featured or otherwise available”).
 FTC Facebook Compl. ¶ 8 (“Facebook’s leadership has learned and recognized that the sharpest competitive threats to Facebook Blue come not from ‘Facebook clones,’ but from differentiated services and during periods of transition”).
 Alexander G. Volkov et al., Venus Flytrap Biomechanics: Forces in the Dionaea Muscipula Trap, 170 Journal of Plant Physiology 25 (2013), https://doi.org/10.1016/j.jplph.2012.08.009, http://www.sciencedirect.com/science/article/pii/S017616171200332X.
 Google Compl. ¶¶ 60-64.
 House Report at 194.
 House Report at 194.
 House Report at 239.
 House Report at 239.
 House Report at 239.
 Google Compl. ¶ 12.
 Rani Molla, As Covid-19 Surges, The World’s Biggest Tech Companies Report Staggering Profits: Despite Antitrust Investigations And A Recession, Big Tech Is Doing Great, Vox, Oct. 30, 2020, https://www.vox.com/recode/2020/10/30/21541699/big-tech-google-facebook-amazon-apple-coronavirus-profits.
 Google Compl. ¶ 12.
 Ariel Ezrachi and I explore this in Competition Overdose: How Free Market Mythology Transformed Us from Citizen Kings to Market Servants (2020).
 House Report at 135.
 House Report at 7.
 Rep. Ken Buck et al., House Judiciary Committee Subcommittee on Antitrust, Commercial, and Administrative Law, The Third Way 10 (2020), https://buck.house.gov/sites/buck.house.gov/files/wysiwyg_uploaded/Buck%20Report.pdf.
 House Report at 392.
 House Report at 396.
 House Report at 396-97.
 House Report at 398; States Facebook Compl. ¶¶ 213-214; FTC Facebook Compl. ¶ 155.
 House Report at 398.
 House Report at 397.
 House Report at 398-99; CMA Report Appendix P, ¶¶ 3.132-3.134.
 House Report at 398-99; CMA Report Appendix P, ¶¶ 3.132-3.134.
 House Report at 399.
 Google Compl. ¶¶ 47, 175, 182; CMA Final Report at ¶ 89.
 House Report at 20, 385-87.
 See, e.g., Australian Government Response and Implementation Roadmap for the Digital Platforms Inquiry (12 December 2019), https://treasury.gov.au/publication/p2019-41708; the proposed EU ePrivacy Regulation. “Regulation of the European Parliament and of the Council concerning the respect for private life and the protection of personal data in electronic communications and repealing Directive 2002/58/EC; ACCC Final Report at 34-35 (recommend updating definition of personal information to capture potential online identifiers of individuals; strengthening privacy notifications and consent requirements with pro-consumer privacy defaults; enable the erasure of personal information; private causes of action for privacy violations; and higher penalties under the privacy statute).
 House Report at 394-95.
 House Report at 395.
 See, e.g., Paul Sandle, Britain Proposes Tailored Competition Rules for Google and Facebook, Reuters, Dec. 8, 2020, https://mobile-reuters-com.cdn.ampproject.org/c/s/mobile.reuters.com/article/amp/idUSKBN28I1A5; 2019-2020 Parliament of the Commonwealth of Australia, House of Representatives, Treasury Laws Amendment (News Media And Digital Platforms Mandatory Bargaining Code) Bill 2020, Explanatory Memorandum, https://parlinfo.aph.gov.au/parlInfo/download/legislation/ems/r6652_ems_2fe103c0-0f60-480b-b878-1c8e96cf51d2/upload_pdf/JC000725.pdf;fileType=application%2Fpdf; European Commission, Digital Services Act package: Ex ante regulatory instrument for large online platforms with significant network effects acting as gate-keepers in the European Union’s internal market (2020), https://ec.europa.eu/info/law/better-regulation/have-your-say/initiatives/12418-Digital-Services-Act-package-ex-ante-regulatory-instrument-of-very-large-online-platforms-acting-as-gatekeepers; CMA Final Report at ¶¶ 77-82, 123, 7.50 (outlining other jurisdictions’ proposals); CMA Online Platforms and Digital Advertising: Market Study Interim Report at ¶¶ 6.19-6.53 (2019); ACCC Final Report at 37 (amending the law so that unfair contract terms are identified and prohibited (not just voidable), and impose civil pecuniary penalties when they are used in any standard form consumer or small business contract). In June 2019, the European Council of the European Union adopted a regulation that seeks to improve relationships between digital platforms and businesses, by providing businesses with a more transparent, fair and predictable online business environment, as well as an efficient system for seeking redress. Platform-to-Business Regulation (EU) 2019/1150 (entered into force in June 2019 and will apply as of 12 July 2020).
 OECD, Big Data: Bringing Competition Policy to the Digital Era Executive Summary (26 April 2017), http://www.oecd.org/competition/big-data-bringing-competition-policy-to-the-digital-era.htm.
 European Commission, Press Release, Antitrust: Commission Consults Stakeholders on a Possible New Competition Tool, Brussels, 2 June 2020.
 European Commission, Press release, Antitrust: Commission Imposes Interim Measures on Broadcom in TV and Modem Chipset Markets, 16 October 2019, https://ec.europa.eu/commission/presscorner/detail/en/ip_19_6109.
 The UK, for example, can undertake market studies “using powers under section 5 of the Enterprise Act 2002 (EA02) which allows the CMA to obtain information and conduct research. They allow a wide consideration of issues affecting the market. They can include a range of outcomes including recommendations to government, enforcement action and referral for market investigation.” UK Competition and Markets Authority, Press Release: CMA Launches Immediate Review of Audit Sector, 9 October 2018, https://www.gov.uk/government/news/cma-launches-immediate-review-of-audit-sector.
 CMA Final Report at ¶¶ 102-104; ACCC Final Report at 12.
 ACCC Final Report at 32 (codes of conduct on designated digital platforms to govern their relationships with news media businesses, “ensure that they treat news media businesses fairly, reasonably and transparently in their dealings with them, and provide commitments on the sharing of data with news media businesses, the early notification of changes to the ranking or display of news content, that the digital platform’s actions will not impede news media businesses’ opportunities to monetise their content appropriately on the digital platform’s sites or apps, or on the media businesses’ own sites or apps, and where the digital platform obtains value, directly or indirectly, from content produced by news media businesses, that the digital platform will fairly negotiate with news media businesses as to how that revenue should be shared, or how the news media businesses should be compensated”).
 FTC Facebook Compl. at p. 51; see also States Facebook Compl. at p. 75.
 OECD Consumer Data Rights and Competition, supra note, at ¶ 193 (quoting Wolfgang Kerber, “Digital markets, data, and privacy: competition law, consumer law and data protection”, Journal of Intellectual Property Law & Practice, p. jpw150 (2016), http://dx.doi.org/10.1093/jiplp/jpw150; Common Understanding of G7 Competition Authorities on “Competition and the Digital Economy, Paris, 5th June 2019, http://www.autoritedelaconcurrence.fr/doc/g7_common_understanding.pdf(calling for the promotion of greater international cooperation and convergence).
 Elizabeth Warren, Here’s How We Can Break Up Big Tech, Medium, Mar. 8, 2019, https://medium.com/@teamwarren/heres-how-we-can-break-up-big-tech-9ad9e0da324c; Bernie Sanders, Issues: Corporate Accountability and Democracy, https://berniesanders.com/issues/corporate-accountability-and-democracy/.
 Overall, 87.7% of Facebook employees’ contributions in the 2020 election cycle went to Democrats (with $1,316,568 to Joe Biden), and 12.27% to Republicans. https://www.opensecrets.org/orgs/facebook-inc/recipients?id=D000033563.
 Overall 93.72% of Google employees’ contributions went to Democrats. https://www.opensecrets.org/orgs/alphabet-inc/recipients?id=D000067823
 Overall 85.12% of Amazon employees’ contributions went to Democrats. https://www.opensecrets.org/orgs/amazon-com/recipients?id=D000023883
 Overall 92.62% of Apple’s employees’ contributions went to Democrats. https://www.opensecrets.org/orgs/apple-inc/recipients?id=D000021754
 Brody Mullins, Rolfe Winkler and Brent Kendall, Inside the U.S. Antitrust Probe of Google, Wall St. J., March 19, 2015, https://www.wsj.com/articles/inside-the-u-s-antitrust-probe-of-google-1426793274.
 For a critical assessment, see Chris Sagers, The Utter Failure of the Trump Administration’s Antitrust Chief, Slate, Aug. 10, 2020, https://slate.com/business/2020/08/antitrust-doj-delrahim-trump.html. For a defense, see Roger Alford, Regarding Those Marijuana Mergers: A Response to Accusers Who Question the DOJ, Just Security, July 13, 2020, https://www.justsecurity.org/71295/regarding-those-marijuana-mergers-a-response-to-accusers-who-question-the-doj/.
 U.S. Dep’t of Justice, Antitrust Division Workload Statistics FY 1980 – 1989, https://www.justice.gov/atr/antitrust-division-workload-statistics-fy-1980-1989; U.S. Dep’t of Justice, Antitrust Division Workload Statistics FY 1990-1999, https://www.justice.gov/sites/default/files/atr/legacy/2009/06/09/246419.pdf; U.S. Dep’t of Justice, Antitrust Division Workload Statistics FY 2000 – 2009, https://www.justice.gov/sites/default/files/atr/legacy/2012/04/04/281484.pdf.
 Bates College & Gallup, Forging Pathways to Purposeful Work, The Role of Higher Education 6 (2019).
 Charlie Warzel, What Facebook Fed the Baby Boomers, N.Y. Times, Nov. 24, 2020, https://www.nytimes.com/2020/11/24/opinion/facebook-disinformation-boomers.html?referringSource=articleShare.
 Ryan Mac & Craig Silverman, Plunging Morale And Self-Congratulations: Inside Facebook The Day Before The Presidential Election, BuzzFeed, Nov. 3, 2020, https://www.buzzfeednews.com/article/ryanmac/inside-facebook-24-hours-before-election-day.
 Harvard Bus. School, Institute for Strategy & Competitiveness, Creating Shared Value, https://www.isc.hbs.edu/creating-shared-value/Pages/default.aspx.