The other major regulatory shift we should consider is a separation of platforms and commerce to create a more equitable and competitive digital landscape. The power of Big Tech is all too reminiscent of the power held by nineteenth-century railroad barons. They, too, dominated their economy and society. And they, too, were able to price gouge, drive competitors out of business, and avoid taxation and regulation, largely by buying off politicians. Yet eventually, they were curbed by a number of regulatory changes, including the creation of the Interstate Commerce Commission, which included some provisions that the industry favored, as well as many it lobbied against. Rather than crush innovation, the ICC ushered in a period of prosperity by allowing technology benefits to be widely shared.
Many experts would argue that Big Tech companies with strong network effects are natural monopolies and should be regulated like utilities, with government oversight to make sure that they can’t prevent competitors from using the networks fairly, or use predatory pricing or unreasonable terms of service to gain undue control over the Internet—which is, of course, the railroad of the twenty-first century. This may mean bringing back older antitrust ideas, such as the concept of the essential facilities doctrine, which the Supreme Court used in 1912 to compel the railroads that controlled the only bridges over the Mississippi River in St. Louis to grant access to their rivals on nondiscriminatory terms. It’s easy to see the parallels for Google, Amazon, Facebook, and Apple today—all of which hold huge power over their respective ecosystems.4 This idea is, of course, already in the public conversation, and has been proposed by a number of policy makers, including Massachusetts senator and Democratic presidential candidate Elizabeth Warren. She has also compared Big Tech to the railroads and believes that companies with more than $25 billion in global revenue should not be allowed to own a platform “utility” and also be a participant on that platform.
Finally, we should consider taking antitrust policy back to a broader interpretation of political power, as I described at length in chapter 9, one in which societal welfare, rather than just that of consumers, is taken into account. This is the only way to enforce fairness and economic competitiveness in an era in which the big technology companies, who have blanketed Washington with money and lobbyists, are exerting kudzu-like control over the political economy.
Who Profits from Our Data, and How Can We Better Share the Benefits?
I have no doubt that even if they are well regulated, Big Tech firms will continue to turn disproportionate profits, because as we’ve already learned, their key inputs—our data—are had for free. In an era in which most wealth will live in data, intellectual property, and other intangible assets, it will be important to come up with more equitable ways to share that pie.
There are those who believe that even to have the discussion of how better to share the spoils of surveillance capitalism is to capitulate to it. You can certainly make that argument. But the fact is that the horse is out of the barn. I’d argue that while we are spending the time to figure out exactly how to regulate and curb the power of Big Tech, we should also make sure that it isn’t mining our biggest natural resource for free.
As we learned earlier in this book, the extraction of personal data is America’s fastest growing industry, one that will be worth $197.7 billion by 2022 if current trends hold—more than the total value of American agricultural output.5 If data is the new oil, then the United States is the Saudi Arabia of the digital era. The leading Internet platform companies are the new Aramco and ExxonMobil. But the tech platform companies are not the only ones in the digital surveillance business. Data brokers such as credit bureaus, healthcare firms, and credit card companies collect and sell all sorts of sensitive personal user data to other businesses and organizations that do not have the scale to collect it themselves. These include retailers, banks, mortgage lenders, colleges, universities, charities, and—as if we could forget—political campaigns.
This is one reason we haven’t seen more companies outside Silicon Valley pushing for antitrust action against the big technology companies—they are the ones buying what the Valley is selling. The advent of the Internet of things, in which Web-enabled sensors are embedded in objects all around us, will exponentially expand the opportunities for digital resource extraction. Every company is getting into this business. As a result, we may not be able to simply regulate away all the problems that are being posed by surveillance capitalism.
That’s why it is worth considering whether the companies that extract our digital oil should have to pay for it. California has also proposed a “digital dividend” paid by data collectors to the owners of this resource—all of us. It is akin to the way Alaska and countries including Norway have created wealth funds into which a percentage of revenues from commodities are invested for the benefit of future generations. The extractors can afford it. Google and Facebook have high double-digit profit margins because they do not pay for their raw inputs—our data. But we should own our own personal information. And if the extractors use it, they should have to compensate us.
The four major categories of data harvesters—platforms, data brokers, credit cards, and healthcare firms—could pay every American who uses the Internet a set fee, using a portion of their own revenue. Or the extractors could be forced to put a portion of that money into a public fund that invests in education and infrastructure. Education in particular would be an excellent use of such funds, given that all the shifts that I’ve outlined in this book will require the retraining of a twenty-first-century workforce; it seems only fair that Big Tech—which often complains about the lack of adequate education in the United States—should have to help pay for that. Meanwhile, a 50 percent levy on digital revenue could likewise plug the majority of an American infrastructure spending gap estimated to be $135 billion by 2022.6 That seems more than a fair exchange for allowing the data collectors free access to the country’s most valuable resource. If data is a resource, then perhaps we need a sovereign wealth fund for it.
Taxing data extractors cannot, however, be a get-out-of-jail-free card that allows them to run roughshod over individual privacy or civil liberty. For users of platform technology, transparency could be increased with “opt-in” provisions that allow them more control over how their data is used (as is the case with the EU’s General Data Protection Regulation, and the even tougher proposals in California). The “opt-in” language should be clear and simple, with the burden of proof for violations on companies rather than individuals. Big Tech companies should also be required to keep audit logs of the data they feed into their algorithms, and be prepared to explain their algorithms to the public.
“A recurring pattern has developed,” says Frank Pasquale at the University of Maryland, “in which some entity complains about a major Internet company’s practices, the company claims that its critics don’t understand how its algorithms sort and rank content, and befuddled onlookers are left to sift through rival stories in the press.” Companies should be prepared to make themselves open to algorithmic audits, as suggested by mathematician and Big Tech critic Cathy O’Neil, in case of complaints or concerns about algorithmic bias that could allow for discrimination in the workplace, healthcare, education, and so on.7
Individuals should also have their digital rights legalized. Former Wired editor John Battelle has proposed a digital bill of rights that would assign possession of data to its true owner, which is, of course, the user and generator of that data, not the company that made off with it. He believes this notion should be so central that it should be enshrined as an amendment to the Constitution. As the Europeans have put it, people should also have a “right to be forgotten,” in which companies must delete any data held on individuals should they wish it. Two million Europeans have already made the choice to opt out. Finally, I would like to see a digital consumer protection bureau, with tough rules around discrimination by algorithms, and a system for e
nsuring that individuals can access and understand how their personal data is being used, as we can with credit scores today.
All of this relates to the need for more transparency and simplicity in the discussion about Big Tech. Complexity (or the illusion of it) is too often used to avoid legitimate public interest questions, such as how propagandists get their messages across, or how users are tracked and valued. Companies should help us understand by opening the black box of their algorithms. This needn’t be a competitive disadvantage; research has shown that it is the amount of data plugged into an algorithm, rather than the cleverness of the algorithm itself, that is the asset. And one could argue that greater transparency is a revenue generator, in that the more users trust what companies are doing, the more willing they may be to part with valuable data.
And the more trusting investors might be of the Big Tech platforms, which have lost so much trust. As one senior policy maker’s aide pointed out to me when I began researching this book, data is the most valuable commodity on the planet, and yet companies that traffic in it don’t have to declare its value clearly on their financial statements. Currently, the monetary value of data gets shoehorned into “goodwill” on financial statements or, more often, is left out entirely.
That should change, for all kinds of reasons, not the least of which is that investors can’t get a remotely accurate picture of what a tech company is worth without understanding the value of exactly what they are trafficking in. (Imagine if you couldn’t see the value of the assets held by GM or Ford on their balance sheets.) But even more important is the fact that when we are the product, when our data is what’s being collected, we have a right to know how much it’s worth—and then decide, as a society, if we should be receiving some of that value ourselves.
We should also consider whether the public sector, rather than private companies, should be the repository of some data wealth, and help ensure that private sector actors have equal access to it and that citizens have more control over just how it is monetized. The conventional wisdom has been that in the brave new world of big data and artificial intelligence, which will drive global growth over the next several decades, there can be only two models: China’s surveillance state, in which the government knows and directs all; or the light touch regulation of the United States, which has bred a collection of monopoly powers that may well be choking off job creation and growth in the larger economy.
But there is a third way—one that France and other countries are pursuing—that aims for a middle ground. In Europe, the public sector already holds a large amount of data—in health, transportation, defense, security, and the environment—of the sort that will be needed to develop artificial intelligence and other big data applications. Companies could potentially access these large troves of data held by state institutions, but with public oversight. Citizens would have a say, via elected officials, in the sort of research and big data applications that this data could be used to develop. And companies large and small would have equal access to the gold mine; this would address one of the most frequent complaints I hear from data-driven start-ups in the United States, which is that the biggest players have walled off access to crucial data.
A Fair System of Tax for the Digital Age
Tech, like finance, has hugely benefited from those intangible riches like data and information that can be so easily moved to the tax haven du jour, for the very reason that they are intangible—these assets are virtual rather than physical (like factories or machinery or brick-and-mortar stores) and so can be located anywhere. But the revelations of the Panama Papers, which uncovered how rich companies and individuals around the world were offshoring vast sums of money,8 have helped to galvanize public debate around how to create a fairer system of tax for the information age, and the United Kingdom, France, India, and others are now suggesting fundamental shifts in the nature of corporate taxation in an effort to level the playing field.
“The current system favors intangible rich firms over those that make money from tangible assets, and multinational firms over small, local companies,” says Nobel Prize–winning economist and Columbia University professor Joseph E. Stiglitz, who heads up the Independent Commission for the Reform of International Corporate Taxation, a group of academics and policy makers pushing for global tax reform. “Firms like this can use financial engineering to play all sorts of games,” says Stiglitz, who favors a global flat tax on such firms to avoid a zero-sum race to the bottom to the lowest-cost tax havens.9
How would this actually work in practice? A key idea found in many of the proposals from tax reform advocates is to tax revenues at the point of sale, rather than profits, which would reduce the sort of financial engineering that allows IP- and data-rich companies like Apple and Google to offshore profits in tax havens like Ireland and the Netherlands.
The problem was first raised at the global level by the Organization for Economic Co-operation and Development in 2012, via its Base Erosion and Profit Shifting initiative; it’s now under discussion in forums like the United Nations, the World Bank, and the International Monetary Fund. The issue has been turbocharged by an increasing awareness that the companies that hold the majority of wealth today have no need of a major physical presence in their various markets, or even a fixed national headquarters.
One of the key points that tax reform advocates make is that the labor market disruption caused by Big Tech (which was covered in chapter 8) is forcing states to revamp educational systems, improve vocational training, and invest a lot more to create a twenty-first-century workforce—which, of course, requires tax revenue. But while nearly every country agrees that the current system isn’t working, there’s not yet consensus on what the new system should be.
The United Kingdom, for example, has said that if there’s no international consensus, it plans to unilaterally pass a minimum digital tax. A number of EU finance ministers have come out in support of a tax on revenue versus profits. Other countries, such as India, have already implemented “equalization” levies on payments in excess of $1,500 to foreign enterprises without permanent establishment in the country. This means that when, say, Amazon makes a sale there, a certain amount of tax is withheld on the payment. China and Germany are inclined to buy into the U.S. philosophy of a minimum corporate tax, since they have large companies (which include not just tech firms but automakers) to protect. The United Kingdom and France want to locate value in data and users. And here in the United States, while Trump set a de facto floor on digital tax, he has also inflamed the debate about where value lives in the digital age. All of this points to the fact that in a fractured and politically polarized world, tax on digital goods may become yet another aspect of global trade relations to be weaponized.
Whatever happens, it will represent a big shift in the old order, and the Silicon Valley giants are, of course, complaining bitterly about all of it. At a 2017 OECD conference at the University of California, Berkeley, Robert Johnson, a representative for the Silicon Valley Tax Directors Group, insisted that “raw user data isn’t like oil….Value is created by the development and production of goods and services, not consumption.”10
Yet, data is exactly like oil. In fact, it’s even more valuable. Crafting a smart and fair system of digital taxation will not be easy, as the outcry over the various international plans suggests. But at a time when corporations hold more economic power relative to government than ever before, finding a way to reclaim some of that wealth for citizens will be essential to ensuring a functioning democracy.
A Digital New Deal
The prospect of massive technology-related job displacement is a major source of public anxiety about Big Tech—so much so that a relatively unknown entrepreneur named Andrew Yang, the founder of a nonprofit organization that links college graduates to start-up employment, launched a 2020 White House bid on an anti-AI platform. He will not be successful, but the issue—the
human cost of artificial intelligence, big data, and automation—will be a major topic in the 2020 U.S. elections. The answer to the question of whether AI will help or hurt workers depends first on your time frame. Technology is always a net job creator over the long run, but, as Keynes put it, in the long run we are all dead.
Perhaps more salient, then, is the second key factor: your socioeconomic class. In the next five years or so, as digital technologies make their way into every industry, they will benefit those at the top with the skills and education to leverage the productivity advantages they afford, and will therefore be likely to increase the winner-takes-all trend in global labor markets. This has massive consequences. While digitalization has the potential to boost productivity and growth, it may also hold back demand if it compresses labor’s share of income and increases inequality. One 2018 McKinsey survey of global executives found that the majority believed they would need to retrain or replace more than a quarter of their workforce by 2023 to digitize their businesses. At a conference in that same year, I heard chief executives from large U.S. multinationals discussing ways in which technology would be able to replace 30 to 40 percent of the jobs in their companies over the next few years—and fretting about the political impact of layoffs on that scale.
I would like to propose a radical solution: Do not lay them off. I am not asking corporate America to keep workers on as charity. I am suggesting that the public and private sector come together in what could be a kind of digital New Deal. As many jobs as will be replaced by automation, there are other areas—customer service, data analysis, and so on—that desperately need talent. Companies that pledge to retain workers and retrain them for new jobs should be offered tax incentives to do so. The United States should take a page out of the post–financial crisis German playbook, in which large-scale layoffs were avoided as both the public and private sector found ways to continue to use labor even as demand dipped. Companies were given government subsidies to keep workers on, and spent the cash on factory upgrades, technical improvements, and training costs, all of which helped German companies grab market share from U.S. rivals in China when growth returned. Corporations also contributed spare workers to public schemes that benefited the larger economy.
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