In saying that attention is scarce, I mean that there is not enough of it available today to meet our needs. That’s what I set out to show in this part of the book. I’ll start by defining attention, before presenting several examples of needs that either are already no longer met due to a lack of attention, such as the need for meaning, or are at risk of not being met in the near future. After that, I will consider how much human attention is currently caught up in Industrial Age activities and how an increasing amount of attention is being trapped through our current uses of digital technology, such as advertising-based social networks. I will also discuss why market-based capitalism cannot be used to allocate attention.
While digital technology is being used to capture rapidly increasing amounts of our attention, we should also consider what the bulk of attention is dedicated to today. Not surprisingly, since we are just beginning to transition out of it, the vast bulk of human attention is focused on Industrial Age activities, in particular labor and consumption. For example, in the US many people spend 40 or more hours a week on the job, which amounts to 35 per cent of waking hours (assuming eight hours of sleep per night). People in the US now spend around 10 and a half hours a day consuming media (including traditional television and radio in addition to Facebook, YouTube, Netflix and similar services, podcasts, games, and more), which (setting aside simultaneous usage) amounts to over 60 per cent of waking time ("The Nielsen Total Audience Report," 2020). To understand why so much of our attention is spoken for, I present the concept of the “job loop.”
Thinking dispassionately about labor is hard, because over the last couple of centuries we have become convinced that employment is essential to both the economy and individual dignity. Let’s start from the perspective of production. If you want to make products or deliver a service, you require a series of inputs, including buildings and machines (capital), raw materials or parts (supplies), and human workers (labor). For much of history, capital and labor have been complementary: as the owner of a company, you couldn’t use your physical capital without having labor to operate it. That was true for manufacturing and even more so for services, which often use little capital and consist primarily of labor.
However, there is nothing in economics that says that all production processes should require labor. The opposite idea is an artifact of the production functions that were technologically available when economists developed the theory of production. If company owners are able to figure out how to do something cheaper or better by using less or no labor, that’s what they will choose to do. When it was acquired by Facebook for $19 billion, for example, WhatsApp had fewer than 50 employees.
Having no labor at all might make sense for a single company, but it does not for the economy as a whole as it is currently constructed. Who will buy goods and services produced by automated systems if people are unemployed and don’t have any money? Walter Reuther, head of the United Automobile Workers union in the 1950s, often told a story about an exchange he had with an official of the Ford motor company (who, as the story became famous in its own right, became Henry Ford II):
Ford official: How are you going to collect union dues from these guys [robots]? Walter Reuther: How are you going to get them to buy Fords? (O'Toole, 2011)
If we all had inherited wealth or sufficient income from capital, an economy without labor would not be a problem, and we could enjoy the benefits of cheaper products and services courtesy of robots and automation.
The possibility of a slump in consumer demand due to less labor long seemed not just unlikely but impossible. There was a virtuous loop at the heart of economic growth: the ‘job loop.’
In today’s economy, the majority of people sell their labor, producing goods and services and receiving wages in return. With their wages, they buy smartphones, books, tools, houses and cars. They also buy the professional assistance of attorneys, doctors, car mechanics, gardeners and hair stylists.
Most of the people who sell these goods and services are in turn employed, meaning that they too sell their labor and buy goods and services from other people with what they are paid. And round and round it goes.
The job loop worked incredibly well in combination with competitive markets for goods and services and with a properly functioning financial system. Entrepreneurs either used debt or equity to start new businesses, and employed people at wages that were often higher than older businesses, increasing their employees’ purchasing power and thereby fueling further innovation and growth. As far as expanding economic production and solving problems for which markets are well-suited, it was a virtuous cycle that resulted in unprecedented prosperity and innovation.
Some might point out that many people these days are self-employed, but that is irrelevant if they are selling their time. For instance, a graphic designer who works as an independent contractor is still paid for the labor they put into a project. It is only if they design something that is paid for over and over without them spending further time on it, such as a graphics template, that they have the opportunity to leave the job loop.
There are multiple problems with this virtuous cycle today. First, as we calculated at the outset of this section, it traps the vast majority of human attention. Second, when things contract, the effect of mutual reinforcement applies in the other direction. Take a small town, for example, in which local stores provide some of the employment. If a big superstore comes into town, total retail employment and wages will both fall. Fewer store employees have income, and those who do have less. If they start to spend less on haircuts and car repairs, the hair stylist and car mechanic earn less and can spend less themselves, and so on. Third, much of the consumption today is driven by vast sums of money spent on advertising, as well as by exposure to social media, inducing people into positional spending on wants (e.g., a bigger car than their neighbor). These higher expenditure levels, in turn, lock people into jobs which they hate but cannot afford to leave, which explains a great deal of the frustration among relatively highly-paid professionals, such as lawyers and bankers.
Put differently, what was once a virtuous loop has become a vicious loop that holds much of human attention trapped. Much of The World After Capital is about breaking free of this vicious version of the job loop. That is an urgent problem as the job loop has been becoming more vicious for some time now due to a change in the relationship between labor and capital.
To understand what is happening to the job loop, we need to look at a change in the economy that has become known as “the Great Decoupling” (Bernstein & Raman, 2015). In the decades after Worl War II, as the US economy grew, the share of Gross Domestic Product (GDP) going to labor grew at the same rate. However, starting in the mid-1970s, GDP continued to grow while household income remained flat (Economic Policy Institute, n.d.).
Source: Federal Reserve Bank of St. Louis, 2021a
Over this time of stagnant incomes, and particularly from the mid-1980s onward, US GDP growth was increasingly financed by consumers going into debt, until we reached the limit of how much debt households could support. The first event that really drove that point home was the collapse of the US housing bubble. There is some evidence that we are hitting another such point right now, as a result of the COVID-19 crisis, which has led to dramatic increases in unemployment.
Source: Federal Reserve Bank of St. Louis, 2021b; 2021c
Similar changes have occurred in other developed economies. This decoupling may be partly accounted for by changing demographics, but the primary driver appears to be technology. As technological innovation accelerates, there will be further pressure on the job loop. Particularly worrisome is the fact that jobs in developing countries are highly exposed to automation (The Economist, 2016). As a result, these countries may either skip the “golden age of the job loop” entirely or have a much diminished version.
So, while we want to free up the attention trapped in the job loop, we need to figure out how to do so gradually, rather than through a rapid collapse. But is such a collapse even possible?
With the job loop still dominant, people have to sell their labor to earn a living. Until recently, most economists believed that when human labor is replaced by technology in one economic activity, it finds work in another part. These economists refer to a fear of technological unemployment or underemployment as the “lump of labor fallacy.“
The argument is that automating some part of the economy frees up labor to work on something else—entrepreneurs might use this newly available labor to deliver innovative new products and services, for example. There is no fixed “lump” of labor; rather there are potentially an infinite number of things to work on. After all, this is what has happened historically. Why should this time be different?
To understand how things could be different, we might consider the role horses have played in the American economy. As recently as 1915, 25 million horses worked in agriculture and transportation; by 1960, that number had declined to 3 million, and then we stopped keeping track entirely as horses became irrelevant (Kilby, 2007). This decline happened because we figured out how to build tractors, cars and tanks. There were just no uses left for which horses were superior to a mechanical substitute. The economist Wassily Leontief (1952) pointed out that the same thing could happen to humans in his article “Machines and Man”.
Humans obviously have a broader range of skills than horses, which is why we have so far always found new employment. So what has changed? Basically, we’ve figured out how to have computers do lots of things that until recently we thought only humans could do, such as driving a car. Digital technology gives us universal computation at zero marginal cost. Suddenly, the idea that we humans might have fewer uses doesn’t seem quite so inconceivable.
Those who claim that this is committing the lump of labor fallacy argue that we haven’t considered a new set of human activities that will employ people, but that line of thinking might also be flawed. Just because we have found new employment in the past doesn’t mean we will in the future. I call this belief the “magic employment fallacy.”
We can be incredibly creative when it comes to thinking of new things to spend our time on, but the operative question for people selling their labor is whether they can get paid enough to afford solutions to their needs, such as food, shelter and clothing. The only thing that matters for this question is whether a machine or another human is capable of doing whatever we think of more cheaply.
This turns out to be the central problem with the magic employment fallacy. Nothing in economic theory says what the ‘market-clearing price’ for labor—the wage level at which there is neither unemployment nor a labor shortage—ought to be. It might be well below what people need to cover their needs, which could present a near-term existential threat to many people. We thus appear to face a dilemma. On the one hand, we want to free up human attention for uses that the job loop doesn’t provide for. On the other hand, we want to avoid a rapid collapse of the job loop. In order to understand how we can accomplish both, we need to consider the relationship between the cost of labor and innovation.
Some people argue that unions made labor expensive, resulting in unaffordable products and services. But in reality, increased labor costs in fact propelled us to become more efficient: entrepreneurs overcame the challenge of more expensive labor by building better machines that required fewer humans. In countries such as India, the abundance of cheap labor meant that for a long time there was little incentive to invest in machines, since it was cheaper to have people do the work by hand.
Globally, we face the risk of being stuck in a low innovation trap precisely as a result of a fear that automation will make labor cheap. For example, we might end up with many more years of people driving trucks across the country, long after a machine could do the same job more safely (Wong, 2016). What is the incentive to automate a job if you can get someone to do it for minimum wage?
Some people object to automation innovations on the grounds that work is an integral part of people’s identity. If you have been a truck driver for many years, for instance, who will you be if you lose your job? At first, this might sound like a completely legitimate question. But it is worth recalling that the idea that purpose primarily has to do with one’s profession, instead of belonging to a religion or to a community, is an Industrial Age phenomenon.
If we want to free up attention via automation, we need to come up with new answers to these concerns. That will be the subject of Part Four, but before getting there we will first consider why capitalism by itself can’t solve these problems.
We have seen that attention is scarce relative to the great problems and opportunities facing us, making proper allocation of available attention the crucial challenge for humanity. As we will see later, digital technology can help meet this challenge. But in the recent past the primary effect of digital technology has been to misallocate attention.
The Internet is exponentially increasing the amount of available content. Most of the recorded content produced by humanity has been produced in the last few years, a natural result of fast exponential growth in the creation of data (Marr, 2019). As a result, it is easy to be overwhelmed. Our limited attention is easily absorbed by the increasing amount of content tailored to piquing our curiosity and capturing our attention. Humans are inadequately adapted to the information environment we now live in. Checking email, Twitter, Instagram, and watching yet another YouTube clip or Snapchat story provide ‘information hits’ that trigger the parts of our brain that evolved to be stimulated by novelty, social connection, sexual attractiveness, animal cuteness, and so on. For hundreds of thousands of years, when you saw a cat (or a sexy person) there was an actual cat (or sexy person) somewhere nearby. Now the Internet can provide you with an effectively unlimited stream of cat (or sexy person) pictures. In 2019, the average person spent nearly two and a half hours on social media every day, part of a staggering 10 and a half hours spent on some sort of media consumption, or more than 60 percent of all waking hours (Kemp, 2020; "The Nielsen Total Audience Report," 2020).
Importantly, the dominant companies that we use to access this information, such as Google, Facebook and Twitter, generate most of their revenues by capturing and reselling our attention. That’s the essence of advertising, which is their business model. Advertisers literally buy our attention. Today, in order to grow, these companies invest in algorithms designed to present highly targeted, captivating content, thereby capturing more of our attention. News sites like Buzzfeed and the Huffington Post do the same.
It is much easier to capture attention by appealing to the parts of our brain that find kittens cute, people sexy, and react with outrage to perceived offenses rather than asking us to read a long-form essay or work through an argument by independently weighing evidence. The companies responsible for these systems lack financial incentives to persuade you to close your computer, put down your smartphone and spend more time with family and friends, read a book, or go outdoors and enjoy, or even clean up, the environment. The financial markets closely track metrics such as number of users and time spent on a platform, which are predictors of future growth in advertising revenue. In other words, the markets that drive the predominant way we use digital technology to allocate attention reflect the financial interests of investors and advertisers, which are often orthogonal or even antagonistic to individual and community interests. As we will see later (see the section on “Missing Prices” below) the problem runs even deeper, as it is actually impossible to construct proper markets for attention.
Capitalism has been so successful that even theoretically communist countries like China have embraced it. But it cannot solve the scarcity of attention without significant changes in regulation, because of three important limitations. First, prices will always be missing for things that we should be paying attention to. Second, capitalism has limited means for dealing with the concentration in wealth and market power arising from digital technologies. Third, capitalism acts to preserve the interests of capital over knowledge. We need to make changes now, precisely because capitalism has been so successful—the problems that are left are the ones it cannot solve.
Capitalism won’t help us allocate attention because it relies on prices that are determined in markets. Prices are powerful because they efficiently aggregate information about consumer preferences and producer capabilities, but not everything can be priced. And increasingly, the things that cannot be priced are becoming more important than those that can: for example, the benefits of space exploration, the cost of the climate crisis, or an individual’s sense of purpose.
The lack of prices for many things is not just a question of a missing market that can be created through regulation. The first foundational issue is the zero marginal cost of copies and distribution in the digital realm. From a social perspective, we should make all the world’s knowledge, including services such as medical diagnoses, available for free at the margin. But this means that as long as we rely on the price mechanism, we will under-produce digital resources. Just as the Industrial Age has been full of negative externalities such as pollution, resulting in overproduction, the Knowledge Age is full of positive externalities, such as learning, which implies underproduction. If we rely on the market mechanism, we will not pay nearly enough attention to the creation of free educational resources.
The second foundational issue is uncertainty. Because prices aggregate information, they fail when no such information exists. When events are either incredibly rare or have never occurred, we have no information on their frequency or severity, and the price mechanism cannot work when forecast error is infinite. For instance, large asteroid impacts on Earth occur millions of years apart, and hence no price can help us allocate attention to detecting them and building systems to deflect them. As a result, we pay a trivial amount of attention to such problems relative to the potential damage they would cause.
The third foundational issue is new knowledge. The further removed such knowledge is from creating a product or service that can be sold, the less use the price mechanism is. Consider early aviation pioneers, for example. They pursued flight because they were fascinated by solving a challenge rather than because there was an obvious market for air travel. Or take the early days of quantum computing: actual machines were still decades away, so at that time the price mechanism would not have allocated attention to the discipline. Much of this knowledge therefore needs to be produced by allocating attention through other mechanisms, such as government funded research, academic institutions, and prizes.
The fourth foundational issue is that in order for markets and prices to exist, there have to be multiple buyers (demand) and sellers (supply). There is no demand and supply for you to spend time with your children or to figure out your purpose in life. Capitalism cannot help us allocate attention to anything that is deeply personal.
A way of summarizing all of these examples is to think of the world as divided into an economic sphere (where prices exist) and a non-economic one. Market-based allocation of attention can only succeed in the former and, to the extent that there are insufficient counterweights, will do so at the detriment of attention allocated to the non-economic sphere. This is the high earning parent, who doesn’t spend enough time with their children, or the legions of science PhDs optimizing ad algorithms instead of working on the climate crisis.
When it comes to the distribution of income and wealth, many different outcomes are possible, and what actually happens depends both on the underlying production function and government regulation. Consider a manual production function that was common before industrialization. If you were a cobbler making shoes by hand, for instance, there was a limit to the number of shoes you could produce.
Then along came industrialization and economies of scale. If you made more cars, say, you could make them more cheaply. That is why, over time, there were relatively few car manufacturers around the world and the owners of the surviving ones had large fortunes. Still, these manufacturing businesses stayed fairly competitive with each other even as they grew large, which limited their market power and thereby the amount of wealth that they generated. Many service businesses have relatively small economies of scale, which has allowed a great many of them to exist, and markets such as nail salons and restaurants have remained highly competitive. Finance is one clear exception to this among services. A few large banks, insurance companies and brokerage firms tend to dominate the finance industry, and that has accelerated in recent years, largely because financial services have already been heavily impacted by digital technology.
With digital technology we are seeing a shift to ever-higher market power and wealth concentration. When you plot the outcomes, such as companies by revenue, the resulting curves look like so-called ‘power laws’: the biggest firm is a lot bigger than the next biggest firm, which in turn is a lot bigger than the third largest, and so on. This pattern is pervasive throughout digital technology and the industries in which it plays a major role. For instance, the most watched video on YouTube has been watched billions of times, while the vast majority of videos have been watched just a few times. In e-commerce, Amazon is an order of magnitude larger than its biggest competitor, and several orders of magnitude larger than most e-commerce companies. The same goes for apps: the leading ones have hundreds of millions of users, but the vast majority have just a few.
Digital technologies are driving these power laws due to zero marginal cost, as explained earlier, as well as through network effects. Network effects occur when a service gets better for all participants as more people or companies join the service. For example, as Facebook grew, both new and early users had more people they could connect with. This means that once a company grows to a certain size it becomes harder and harder for new entrants to compete, as their initially smaller networks offer less benefit to participants. In the absence of some kind of regulation, the combination of zero marginal cost with network effects results in extremely lopsided outcomes. So far, we have seen one social network, Facebook, and one search company, Google, dominate all others.
This shift to power laws is driving a huge increase in wealth and income inequality, to levels that are even beyond the previous peak of the early 1900s. Inequality beyond a certain level is socially corrosive, as the wealthy start to live in a world that is disconnected from the problems faced by large parts of the population.
Beyond the social implications of such inequality, the largest digital companies also wield undue political and market power. When Amazon acquired a relatively small online pharmacy, signaling its intent to compete in that market, there was a dramatic drop in the market capitalization of pharmacy chains. Historically, market power produced inefficient allocations due to excessive rents as prices were kept artificially high. In digital markets, in contrast, powerful companies have often pushed prices down or even made things free. While this appears positive at first, the harm to customers comes via reduced innovation, as companies and investors stop trying to bring better alternative products to market (consider, for example, the lack of innovation in Internet search).
Joseph Schumpeter coined the term “creative destruction” to describe the way in which entrepreneurs create new products, technologies, methods, and ultimately economic structures to replace old ones (Kopp, 2021). Indeed, if you look at the dominant companies today, such as Google, Amazon and Facebook, they are all relatively new having displaced in importance those of the Industrial Age. However, such ‘Schumpeterian' innovation will be more difficult going forward, if not downright impossible. During the Industrial Age, machines served a specific purpose, which meant that when a new product or manufacturing technology became available, the installed base of machines became essentially worthless. Today, general-purpose computers can easily implement a new product, add a feature or adopt a new algorithm. Furthermore, production functions with information as a key input have a property known as ‘supermodularity’: the more information you have, the higher the marginal benefit of additional information (Wenger, 2012). This gives the incumbent companies tremendous sustained power—they gain more marginal value from a new product or service than a new entrant does.
Toward the end of the Agrarian Age, when land was scarce, political elites came from the landowning classes, and their influence wasn’t truly diminished until after the Second World War. Now, although we have reached the end of the time of capital scarcity, political elites largely represent the interests of capital holders. In some countries, such as China, senior political leaders and their families own large parts of industry outright. In other countries such as the United States, politicians are heavily influenced by the owners of capital because of the need to raise funds, the impact on policy of lobbyists, ’think tanks’ and foundations backed by capital, the skewing of public debate through capital-owned media (e.g. FOX), as well as global ’regulatory competition’ allowing capital owners to play governments off against one another in order to limit wealth redistribution through taxation. Consider just lobbying: over a five-year period, the 200 most politically active companies spent nearly $6 billion to influence policy (Allison & Harkins, 2014). A clever study from 2019 showed how this kind of lobbying directly impacts the language of laws subsequently drafted by lawmakers (O’Dell & Penzenstadler, 2019).
The net effect of all of this are policies that are favorable to owners of capital, such as low rates of capital gains tax. Low corporate tax rates, with loopholes that allow corporations to accumulate profits in countries where taxes are low, are also favorable to owners of capital. This is why in many countries we have some of the lowest effective tax rates for corporations and wealthy individuals and families in history (‘effective’ means what is paid after exemptions and other ways of reducing or avoiding tax payments).
In addition to preserving and creating financial benefits for the owners of capital, corporations have also attacked the creation and sharing of knowledge. They have lobbied heavily to lengthen terms of copyright and to strengthen copyright protection. And scientific publishers have made access to knowledge so expensive that libraries and universities struggle to afford the subscriptions (Sample, 2018; Buranyi, 2018).
A key limitation of capitalism thus is that without meaningful change, it will keep us trapped in the Industrial Age by keeping governments and the political process focused on capital. As long as that is the case, we will continue to over-allocate attention to work and consumption, and under-allocate it to areas such as the individual need for meaning and the collective need for the growth of knowledge. Parts Four and Five of The World After Capital will examine how we can get out of the Industrial Age, but first we will take a closer look at the power of knowledge and the promise of the digital knowledge loop.
Have you watched television recently? Stored food in a refrigerator? Accessed the Internet? Played games on your smartphone? Driven a car? These are all things that billions of people around the world do every day. And while they are produced by different companies using a wide range of technologies, none of them would be possible without the existence of knowledge.
Knowledge, as I have earlier defined it, is the information that humanity has recorded in a medium and improved over time. As a reminder, there are two crucial parts to this definition. The first is “recorded in a medium,” which allows information to be shared across time and space. The second is “improved over time,” which separates knowledge from information. Improvement is the result of the operation of the critical process, which allows for existing knowledge to be criticized and alternatives to be proposed. Through this process knowledge becomes better at helping us humans meet our needs.
I began this section with examples of everyday technologies that would not exist without knowledge. An even stronger illustration of the power of knowledge is that without it, many of us would not even be here today. As we saw in our discussion of population, Malthus was right about population growth but wrong about its consequences because he did not foresee the development of technological progress powered by improved knowledge.
Let’s look at a specific example of how this process unfolded. Humans breathe air, but for a long time we did not know what it consisted of. Oxygen and nitrogen, the two primary components of air, were not identified as elements until the late eighteenth century.
Separately, although manure had been used in agricultural practice for millennia, it was not properly studied until the early nineteenth century. By the late 19th century, scientists had finally discovered the microbes that convert nitrogen into a form that plants can use. That led to the understanding that ammonia, which consists of nitrogen and hydrogen, is a powerful fertilizer. Scientific progress eventually resulted in the Haber process for nitrogen fixation which allows for the mass production of fertilizer. Invented in the early twentieth century, it became crucial to raising agricultural yields globally, thus averting the dire consequences Malthus had envisaged. Today, about half of the nitrogen in humans bodies has been touched by the Haber process on its way into the plants and animals that we eat .
My simplified history of the discovery of nitrogen fixation doesn’t capture the many false starts along the way. It seems strange to us now, but at one point a leading theory as to why some materials burn was that they all contain a substance called ‘phlogiston,’ which was thought to be released during combustion or ‘dephlogistication.’ Without the improvement of knowledge over time, we might have remained stuck on that theory, failing to find oxygen and nitrogen and thus to increase agricultural yields, and thereby potentially exposing humanity to a Malthusian crisis.
This is just one example of a knowledge breakthrough that allowed humanity to overcome a seemingly insurmountable barrier to progress. When thinking about the power of knowledge, we must remember that both our individual lifetimes and the history of modern science to-date are trivially short in the timescale of humanity, which in turn is minuscule compared to that of the universe. When considering longer timeframes, we should regard all speculative technological advances that don’t contravene the laws of physics as possible and eventually achievable. This line of thinking about the power of knowledge is inspired by a theoretical foundation for science recently developed by the physicists David Deutsch and Chiara Marletto called constructor theory (“Constructor Theory,” 2020).
Consider for a moment what knowledge might allow us to do in the more or less distant future. We might rid ourselves of our dependence on fossil fuels, cure any disease, and travel to other planets in our solar system (organizations like SpaceX and NASA are already working toward this goal) (NASA, 2018). Eventually, we might even travel to the stars. You might think interstellar travel is impossible, but it isn’t. Extremely difficult? Yes. Requiring technology that doesn’t exist yet? Yes. But impossible? No. It is definitely not imminent, but we can count on it to becoming possible with the further accretion of knowledge.
We are the only species on Earth that has created knowledge—not just science, but also art. Art allows us to express our hopes and fears, and culture has helped to motivate the large-scale coordination and mobilization of human effort. We might think of the technical component of knowledge as underpinning the ‘how’ of our lives, and the artistic component the ‘why’. If you’ve ever doubted the power of art, just think of the many times throughout history when dictators and authoritarian regimes have banned or destroyed works of art.
Knowledge has already made possible something extraordinary: by means of the innovations of the Industrial Age we can, in principle, meet everyone’s needs. But we must generate additional knowledge to solve the problems we have introduced along the way, such as the climate crisis. New knowledge does not spring forth fully formed out of a vacuum. Instead it emerges through what I call the ‘knowledge loop’, in which someone learns something and creates something new, which is then shared and in turn serves as the basis for more learning.
The knowledge loop has been around since humans first developed written language, some five thousand years ago. Before that, humans were able to use spoken language, but that limits learning and sharing in terms of both time and space. Since the invention of written language, breakthroughs have accelerated and access to the knowledge loop has broadened. Those include moveable type (around one thousand years ago), the printing press (around five hundred years ago) and more recently the telegraph, radio and television. Now we are in the middle of another fundamental breakthrough: digital technology, which connects all of humanity to the knowledge loop at zero marginal cost, and also allows machines themselves to participate in it.
It is easy to underestimate the potential of digital technology to further accelerate and broaden access to the knowledge loop. To many people, it seems as if these innovations have so far under-delivered. The technology investor Peter Thiel once famously complained that “We wanted flying cars, instead we got 140 characters.” In fact, we have made great progress on flying cars since then, in no small part because digital technologies have already helped accelerate the knowledge loop.
The zero marginal cost and universality of digital technologies are already accelerating learning, creating and sharing, giving rise to a digital knowledge loop. And as can be seen in the example of YouTube, it holds both amazing promise and great peril.
YouTube has experienced astounding growth since its launch in 2005. People around the world now upload over 100 hours of video content to the platform every minute. To illustrate just how much content that is, if you were to spend 100 years watching YouTube 24 hours a day, you would be unable to watch all the videos uploaded in a single week. YouTube contains amazing educational content on topics as diverse as gardening and pure mathematics. Many of those videos illustrate the promise of the digital knowledge loop, but the peril is also clear: YouTube also contains videos that peddle conspiracies, spread misinformation and even incite hate. Promoting such videos may, perversely, be in YouTube’s interest, as these capture more attention, which can then be resold to advertisers, thus growing YouTube’s revenues and profits.
Both the promise and the peril are made possible by the same characteristics of the platform: all of the videos are available for free to anyone in the world, and they become available globally the second they are published. Anybody can publish a video, and all you need to access them is an Internet connection and a smartphone. As a result, two to three billion people, almost half of the world’s population, has access to YouTube and can participate in the digital knowledge loop.
These characteristics are found in other systems that similarly show the promise and peril of the digital knowledge loop. Wikipedia, the collectively produced online encyclopedia, is another good example. At its most promising, someone might read an entry and learn the method Pythagoras used to approximate pi, then create an animation that illustrates this method, publishing it on Wikipedia, thus making it easier for other people to learn. Wikipedia entries result from collaboration and an ongoing revision process. You can also examine both the history of the page and the conversations about it, thanks to a piece of software known as a ‘wiki’ that keeps track of the history of edits to a page (“Wiki,” n.d.). When the process works, it raises the quality of entries over time. But when there is a coordinated effort at manipulation, Wikipedia can spread misinformation instantly and globally.
Wikipedia illustrates another important aspect of the digital knowledge loop: it allows individuals to participate in extremely small ways. If you wish, you can contribute to Wikipedia by fixing a single typo. If ten thousand people fixed one typo every day, that would be 3.65 million typos a year. If we assume that it takes two minutes to discover and fix a typo, it would take nearly fifty people working full-time for a year (2,500 hours) to fix that many typos.
The example of a Wikipedia spelling correction shows the power of small contributions that add up within the digital knowledge loop. Their peril can be seen on social networks such as Twitter and Facebook, where the small contributions are likes and retweets or reposts to one’s friends or followers. While these tiny actions can amplify high-quality content, they can also spread mistakes, rumors and propaganda: indeed, research carried out at MIT in 2018 found that fake news stories spread faster and more widely than true ones (Vosoughi et al., 2018) (see “Freedom to Learn”, below). These information cascades can have significant consequences, ranging from jokes going viral to the outcomes of elections being affected. They have even contributed to major outbreaks of violence, as in the well-known case of the brutal persecution of the Rohingya in Myanmar (BBC News, 2018).
Some platforms make it possible for people to contribute passively to the digital knowledge loop. Waze is a GPS navigation app. It tracks users that seem to be in a car, and the speed at which they are moving. It then passes that information back to its servers, and algorithms figure out where traffic is moving smoothly and where drivers will encounter traffic jams. Waze then proposes alternative routes, taking the traffic into account. If you follow a different route proposed by Waze, you automatically contribute your speed on that detour, a further example of passive contribution.
To see the peril of passive contribution, consider Google’s autocomplete for search queries, which are derived from what people frequently search for. As a result, they often reflect existing biases, further amplifying them: often, instead of typing out their whole query, users select one of the autocompleted options presented to them. Another example of dangerous passive contribution are suggested ’follows’ on networks such as Twitter. These often present accounts of people similar to the ones someone is already connected with, thus deepening connections among people who think alike while cutting them off from other groups, a phenomenon giving rise to a kind of “Cyber-Balkans” (Van Alstyne & Brynjolfsson, 2005).
The promise of the digital knowledge loop is broad access to a rapidly improving body of knowledge. The peril is that it will lead to a post-truth society that is constantly in conflict. Both of these possibilities are enabled by the same characteristics of digital technologies. Here once again, we can see that technology by itself does not determine the future.
To achieve the promise of the digital knowledge loop and sidestep its perils will require human societies to go through a massive transition, on a par with the two previous ones, from the Forager Age to the Agrarian Age and from the Agrarian Age to the Industrial Age. We now need to leave the Industrial Age behind and enter the next one, which I am calling the Knowledge Age. We have based our economies around the job loop, which traps a lot of our attention. We have constructed our laws governing access to information and computation as if they were industrial products. We have adopted a range of beliefs that keep us tied to jobs and consumption, and we are utterly overwhelmed by the new information environment. All of that has to change.
The transition will be difficult, however, because the Industrial Age is a system with many interlocking parts, and systems are highly resistant to change. As we saw earlier, simply harnessing digital technology to the existing system results in a hugely uneven distribution of power, income and wealth. Even worse, it tilts the digital knowledge loop away from its promise and toward its perils.
The human species is facing problems that we can only overcome if we use digital technology to alleviate rather than worsen attention scarcity. We must reap the promise and limit the perils of digital technology for the knowledge loop. In order to successfully negotiate the transition into the Knowledge Age, we need to make dramatic changes in both collective regulation and self-regulation. This is what we will explore in Part Four.
Attention is to time as velocity is to speed. If I tell you that I’m driving at a speed of 55 miles per hour, that does not tell you anything about where I’m going, because you don’t know what direction I’m heading in. Velocity is speed plus direction. Similarly, if I tell you that I spent two hours with my family yesterday (time), that does not tell you anything about what our minds were directed at—we could have been having an engaging conversation, or we could have been immersed in our phones. Attention is time plus intentionality.
The amount of human attention in the world is finite. We have 24 hours in the day, some of which we need to spend paying attention to eating, sleeping and meeting our other needs. The attention during the remaining hours of most people in the world is taken up by having to earn an income and by consuming goods and services, leaving relatively little time for attention to be freely allocated. A hard limit on available attention also exists for humanity as a whole—as I argued earlier, we are headed for peak population, at which point we will no longer be increasing the total amount of potentially available attention by adding more people.
Crucially, we cannot go back in time and change our past attention, either as individuals or collectively. A student who walks into an exam unprepared cannot revisit the preceding weeks and study more. A world that enters a pandemic unprepared is not able to go back in time and do more research on coronaviruses.
First, let’s consider attention at the individual level. The need for meaning is no longer being met because most people are failing to give enough attention to the crucial questions of purpose at a time of great transition.
In recent times, all over the world, people had become used to constructing meaning around their jobs and beliefs, but both are undermined by digital technologies. Many jobs have come under pressure from automation or outsourcing. Meanwhile, ideas, images, and information are no longer contained by geographic boundaries, and people are increasingly exposed to opinions and behaviors that diverge from their core beliefs. In combination, these challenges are leading to a crisis of identity and meaning. This crisis can take many different forms, including teenage depression, adult suicide—in the US, particularly among middle-aged white men —and fatal drug overdoses (Rodrick, 2019; American Foundation for Suicide Prevention, 2019). Between 2006 and 2019, these problems increased by 99 percent, 26 percent and 43 percent respectively.
Source: CDC, 2020; National Center for Health Statistics, 2019; Substance Abuse and Mental Health Services Administration, 2020
The situation is not dissimilar to the one that first occurred when people left the countryside and moved to big cities during the transition to the Industrial Age, having to give up identities that had been constructed around land and crafts (a process that has continued to play itself out throughout the world as industrialization spread). They were uprooted from their extended families and confronted with people from other regions who held different beliefs. Then too there was a marked increase in mental illness, drug abuse and suicide.
The Industrial Age had little use for an individual sense of meaning—it is difficult to combine the pursuit of a strong sense of personal purpose with the repetitive operation of an industrial machine day in, day out. Early in the Industrial Age, religion continued to provide a source of meaning for most people, as a collective purpose. As the Industrial Age progressed, however, church attendance decreased, while jobs and consumption increasingly came to be seen as sources of meaning. Some of this change can be traced back to the rise of the ‘Protestant work ethic‘, which provided justification for wealth accumulation from rising professions (such as lawyers and doctors) and the managerial class. Some of it is the result of the massive growth in commercial advertising, which cleverly tied consumption to such aspirations as freedom (e.g., the infamous Camel cowboy cigarette ads) and happiness. We have come so far on that path that people now speak of “retail therapy,” the idea that you can make yourself feel better by shopping.
As with such earlier transitions, it is not surprising that with the current digital dislocation we are yet again seeing a rise in populist leaders with simplistic messages, such as Donald Trump in the United States and Viktor Orbán in Hungary. A recent study found that the average share of the vote for populist parties throughout Europe is more than double what it was in the 1960s (Inglehart & Norris, 2016). People who lose their sense of meaning when their purpose and beliefs are challenged want to be told that things will be okay and that the answers are simple. “Make America Great Again” is one such message. These backward-looking movements promise an easy return to a glorious past. Similarly, we are once again seeing a growth in church attendance as well as in various spiritual movements, all of which promise to quickly restore individuals’ access to meaning. The alternative of creating new meaning through an individual search for purpose and the independent examination and formation of beliefs requires considerable attention. Attention which people cannot muster for reasons that we will examine in detail later in the book.
This individual scarcity of attention to purpose is not confined to any one demographic. People who work multiple jobs to pay rent and feed their families are definitely impacted, but so are many people in high-paying jobs, who are often working more hours than ever and have increased their personal expenses to the point where they cannot afford to quit. One might posit that this is the result of a lack of education, but I often meet young people who have graduated from elite schools and want to work for a technology startup or get into venture capital. Most of them are looking for advice about how to apply to a specific position. After discussing that for some time, I usually ask them a more open question: “What do you want from this position?” That often elicits more interesting answers—they might talk about learning a new skill, or applying one that they have recently learned. Sometimes people answer with a desire to contribute to some cause. When I ask them “What is your purpose?”, shockingly few have paid enough attention to this question to have an answer. It is often as if they had been presented with this question for the first time and suddenly realize that “make a lot of money” is not actually a purpose that can provide meaning in life.
Humanity is also not devoting nearly enough attention to our collective need for more knowledge to address the threats we are facing and seize the opportunities ahead of us.
In terms of the threats we face, we are not working nearly hard enough on reducing the levels of carbon dioxide and other greenhouse gases in the atmosphere. Or on monitoring asteroids that could strike the Earth, and coming up with ways of deflecting them. Or on containing the current coronavirus outbreak and future pandemics (an early draft of The World After Capital, written before 2020, said “containing the next avian flu” here).
Climate change, “death from above” and pandemics are three examples of species-level threats that are facing humans. As I wrote earlier, we are only able to sustain the current global human population due to technological progress. Each of these risk categories has the potential to fundamentally disrupt our ability to meet individual needs. For example, the climate crisis could result in large-scale global crop failures, which could mean we would no longer be able meet everyone’s needs for calories and nutrients. This is not a hypothetical concern: it has led to the downfall of prior human civilizations, such as the Rapa Nui on Easter Island and the Mayans, whose societies collapsed due to relatively small changes in their local climate, possibly induced in some measure by their own actions (White, 2019; Simon, 2020; Seligson, 2019). Now we are facing a climate crisis on a truly global scale, and we should be using a significant proportion of all human attention to fight this threat.
On the opportunity side, far too little human attention is spent on things such as environmental cleanup, educational resources and basic research. The list here is nearly endless, and includes unlocking quantum computing and advancing machine intelligence. The latter is particularly intriguing because it could help produce more knowledge faster, thus potentially helping to reduce the scarcity of attention.
None of this means that everyone has to become a scientist or engineer—there are many other ways to allocate attention to address these threats and opportunities. For instance, learning about the climate crisis, sharing that knowledge with others and becoming politically active are all ways of allocating attention that can directly or indirectly create more knowledge. So is creating art that inspires others, whether it is to directly take an action, or by connecting us to our shared humanity as a source of meaning. This is why when I talk about not creating enough knowledge, I am not limiting it to scientific knowledge but including all knowledge, as defined earlier.
Attention scarcity is difficult to alleviate, and I therefore propose it as a possible explanation for the Fermi paradox. The physicist Enrico Fermi famously asked why we have not yet detected any signs of intelligent life elsewhere in our universe, despite knowing that there are plenty of planets that could harbor such life. Many different explanations have been advanced, including that we are the first and hence only intelligent species, or that more advanced intelligent species stay “dark” for fear of being attacked by even more advanced species (the premise of Cixin Liu’s sci-fi trilogy The Three-Body Problem). Alternatively, perhaps all civilizations develop until they have sufficient capital but then suffer from attention scarcity, so they are quickly wiped out by a pandemic or a meteor strike. If civilizations that can build radios don’t persist for very long, the timing of signs of their existence may be very unlikely to coincide with ours.
Why is our scarce attention so poorly allocated that we have created a potential extinction-level event in the form of a climate crisis? One reason is that we currently use the market mechanism to allocate attention. The next sections explain how this mechanism is sucking huge amounts of attention into a few systems such as Facebook, while also keeping much of it trapped in Industrial Age activities. Finally, we will consider why markets fundamentally cannot allocate attention, which points to crucial limits of capitalism.