Why is it that Google, a company once known for its distinctive “Do no evil” guideline, is now facing the same charges of “surveillance capitalism” as Facebook, a company that never made such claims? Why is it now subject to the same kind of antitrust complaints once faced by Microsoft, the “evil empire” of the previous generation of computing? Why is it that Amazon, which has positioned itself as “the most customer-centric company on the planet,” now lards its search results with advertisements, placing them ahead of the customer-centric results chosen by the company’s organic search algorithms, which prioritize a combination of low price, high customer ratings, and other similar factors? The answer can be found in the theory of economic rents, and in particular, in the kinds of rents that are collected by companies during different stages of the technology business cycle. There are many types of rents and an extensive economics literature discussing them, but for purposes of this article, they can be lumped into two broad categories—“rising tide rents” that benefit society as a whole, such as those that encourage innovation and the development of new markets, and “robber baron rents” that disproportionately benefit those with power.
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What Is Economic Rent? Not to be confused with the ordinary sense of rent as a charge for temporary use of property, economic rents are the income above a competitive market rate that is collected because of asymmetries in ownership, information, or power. Economists Mariana Mazzucato and Josh Ryan-Collins write, “If the reward accruing to an actor is larger than their contribution to value creation, then the difference may be defined as rent. This can be due to the ownership of a scarce asset, the creation of monopolistic conditions that enable rising returns in a specific sector, or policy decisions that favour directly or indirectly a specific group of interest.” For example, consider drug pricing. Patents—exclusive, government-granted rights intended to encourage innovation—protect pharmaceutical companies from competition and allow them to charge high prices. Once the patents expire, there is competition from so-called “generic drugs,” and the price comes down. That difference in price (and its impact on pharmaceutical company profits) shows the extent of the rent. In 20th century neoliberal economics, rents have typically been seen as a temporary aberration that is eventually competed away. They are a price that we pay for a rising tide of innovation. But as Mazzucato points out, to the classical economists—Smith, Ricardo, and Mill—who lived in a world of inherited power and privilege, rents were a pernicious and persistent consequence (and source) of inequality. At the dawn of economic theory, agriculture was still the chief source of value creation, and much of that value created by the labor of serfs and tenant farmers was appropriated by those who owned the land. When the local baron sent his troops to collect what he considered his share of the harvest, it was impossible to say no. In an unjust society, neither effort nor investment nor innovation but rents rooted in power asymmetries determine who gets what and why. But not all rents represent abuse of power. As noted by economist Joseph Schumpeter, innovation—whether protected by patents, trade secrets, or just by moving faster and more capably than the competition—provides an opportunity to receive a disproportionate share of profits until the innovation is spread more widely. During the expansive period of a new technology cycle, market leaders emerge because they solve new problems and create new value not only for consumers but also for a rich ecosystem of suppliers, intermediaries, and even competitors. Even though the market leaders tend to receive a disproportionate share of the profits as they lay waste to incumbents and dominate the emerging market, value creation is a rising tide that lifts all boats. But this kind of virtuous rising tide rent, which benefits everyone, doesn’t last. Once the growth of the new market slows, the now-powerful innovators can no longer rely on new user adoption and collective innovation from a vibrant ecosystem to maintain their extraordinary level of profit. In the dying stages of the old cycle, the companies on top of the heap turn to extractive techniques, using their market power to try to maintain their now-customary level of profits in the face of macroeconomic factors and competition that ought to be eating them away. They start to collect robber baron rents. That’s exactly what Google, Amazon, and Meta are doing today. Then the cycle begins again with a new class of competitors, who are forced to explore new, disruptive technologies that reset the entire market. Enter OpenAI, Anthropic, and their ilk.
Attention is all you need What is the source of big tech market power? What is the limited resource that they control and monopolize? It’s not our data. It’s not the price of the services we purchase from them—they give those away for free. It’s our attention. Back in 1971, in a talk called “Designing Organizations for an Information-rich World,” political scientist Herbert Simon noted that the cost of information is not just money spent to acquire it but the time it takes to consume it. “In an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it.” In the discussion following the talk, Simon noted that in the future, information would be so abundant that we would need machines to help us manage our attention. And that has indeed been the secret to success in the information age. Google was founded with the promise of finding the right web page out of billions, giving you just what you want and then sending you on your way. Amazon aimed to help customers find the best quality and price for any one of millions of products. Even social media started with the promise of information triage: for each person, a unique feed of updates from only the friends they had chosen to follow. These are all astonishing tools for making our limited capacity for attention more efficient. In the early idealistic days of internet expansion, the leading companies earned outsized profits by solving the attention allocation problem. As the internet grew, the amount of information available to consumers became so vast that it outran traditional human means of curation and selection. Attention allocation was outsourced to the machines. Algorithms for search, recommendations, social media feeds, entertainment, and news became the foundation of an enormous new economy. The internet giants succeeded by doing what they are now too often reviled for: extracting signal from massive amounts of data. Google not only crawled and indexed virtually every page on the web, it looked at how sites linked to each other, tracked which of the ten top links it showed were clicked on the most, which ones led people to come back and try another and which sent them away satisfied. It used location data and past searches to make answers more relevant and personalized. Amazon too used everything from price, user reviews, popularity, and your individual purchase history to bring to the top the products they believed best matched their customers’ needs. In my 2005 essay “What is Web 2.0?,” I made the case that the companies that had survived the dotcom bust had all in one way or another become experts at “harnessing collective intelligence.” Perhaps a more direct way to say this in the context of economic value creation is that companies such as Amazon, Google, and Facebook had developed a set of remarkable advances in networked and data-enabled market coordination. But over time, something went very wrong. Instead of continuing to deploy their attention optimization algorithms for their users’ and suppliers’ benefit, the tech giants began to use them to favor themselves. It first became obvious with social media: recommended posts and amplification of addictive, divisive content in order to keep users scrolling, creating additional surface area for advertising. Google began to place more and more advertising ahead of “organic” search results, turning advertising from a complementary stream of…
