An earlier post considered Dave Elder-Vass’s very interesting treatment of the contemporary digital economy. In Profit and Gift in the Digital Economy Elder-Vass argues that the vast economic significance of companies like Google, FaceBook, and Amazon in today's economy is difficult to assimilate within the conceptual framework of Marx’s foundational ideas about capitalism, constructed as they were around manufacturing, labor, and ownership of capital, and that we need some new conceptual tools in order to make sense of the economic system we now confront. (Elder-Vass responded to my earlier post here.)
A new book by Nick Srnicek looks at this problem from a different point of view. In Platform Capitalism Srnicek proposes to understand the realities of our current “digital economy” according to traditional ideas about capitalism and profit. Here is a preliminary statement of his approach:
The simple wager of the book is that we can learn a lot about major tech companies by taking them to be economic actors within a capitalist mode of production. This means abstracting from them as cultural actors defined by the values of the Californian ideology, or as political actors seeking to wield power. By contrast, these actors are compelled to seek out profits in order to fend off competition. This places strict limits on what constitutes possible and predictable expectations of what is likely to occur. Most notably, capitalism demands that firms constantly seek out new avenues for profit, new markets, new commodities, and new means of exploitation. For some, this focus on capital rather than labour may suggest a vulgar econo-mism; but, in a world where the labour movement has been significantly weakened, giving capital a priority of agency seems only to reflect reality. (Kindle Locations 156-162)In other words, there is not a major break from General Motors, with its assembly lines, corporate management, and vehicles, to IBM, with its products, software, and innovations, to Google, with its purely abstract and information-intensive products. All are similar in their basic corporate navigation systems: make decisions today that will support or increase profits tomorrow. In fact, each of these companies falls within the orbit of the new digital economy, according to Srnicek:
As a preliminary definition, we can say that the digital economy refers to those businesses that increasingly rely upon information technology, data, and the internet for their business models. This is an area that cuts across traditional sectors – including manufacturing, services, transportation, mining, and telecommunications – and is in fact becoming essential to much of the economy today. (Kindle Locations 175-177).What has changed, according to the economic history constructed by Srnicek, is that the creation and control of data has suddenly become a vast and dynamic source of potential profit, and capitalist firms have adapted quickly to capture these profits.
The restructuring associated with the rise of information-intensive economic activity has greatly changed the nature of work:
Simultaneously, the generalised deindustrialisation of the high-income economies means that the product of work becomes immaterial: cultural content, knowledge, affects, and services. This includes media content like YouTube and blogs, as well as broader contributions in the form of creating websites, participating in online forums, and producing software. (Kindle Locations 556-559)But equally it takes the form of specialized data-intensive work within traditional companies: design experts, marketing analysis of “big data” on consumer trends, the use of large simulations to guide business decision-making, the use of automatically generated data from vehicles to guide future engineering changes.
In order to capture the profit opportunities associated with the availability of big data, something else was needed: an organizational basis for aggregating and monetizing the data that exist around us. This is the innovation that comes in for Srnicek's greatest focus of attention: the platform.
This chapter argues that the new business model that eventually emerged is a powerful new type of firm: the platform. Often arising out of internal needs to handle data, platforms became an efficient way to monopolise, extract, analyse, and use the increasingly large amounts of data that were being recorded. Now this model has come to expand across the economy, as numerous companies incorporate platforms: powerful technology companies (Google, Facebook, and Amazon), dynamic start-ups (Uber, Airbnb), industrial leaders (GE, Siemens), and agricultural powerhouses (John Deere, Monsanto), to name just a few. (Kindle Locations 602-607).
What are platforms? At the most general level, platforms are digital infrastructures that enable two or more groups to interact. They therefore position themselves as intermediaries that bring together different users: customers, advertisers, service providers, producers, suppliers, and even physical objects. More often than not, these platforms also come with a series of tools that enable their users to build their own products, services, and marketplaces. Microsoft’s Windows operating system enables software developers to create applications for it and sell them to consumers; Apple’s App Store and its associated ecosystem (XCode and the iOS SDK) enable developers to build and sell new apps to users; Google’s search engine provides a platform for advertisers and content providers to target people searching for information; and Uber’s taxi app enables drivers and passengers to exchange rides for cash. (Kindle Locations 607-616)Srnicek distinguishes five large types of digital data platforms that have been built out as business models: advertising, cloud, industrial, product, and "lean" platforms (the latter exemplified by Uber).
Srnicek believes that firms organized around digital platforms are subject to several important dynamics and tendencies: "expansion of extraction, positioning as a gatekeeper, convergence of markets, and enclosure of ecosystems" (kl 1298). These tendencies are created by the imperative by the platform-based firm to generate profits. Profits depend upon monetizing data; and data has little value in small volume. So the most fundamental imperative is -- mass collection of data from individual consumers.
If data collection is a key task of platforms, analysis is the necessary correlate. The proliferation of data-generating devices creates a vast new repository of data, which requires increasingly large and sophisticated storage and analysis tools, further driving the centralisation of these platforms. (kl 1337-1339)So privacy threats emerging from the new digital economy are not a bug; they are an inherent feature of design.
This appears to lead us to Srnicek's most basic conclusion: the new digital economy is just like the old industrial economy in one important respect. Firms are wholly focused on generating profits, and they design intelligent strategies to permit themselves to appropriate ever-larger profits from the raw materials they process. In the case of the digital economy the raw material is data, and the profits come from centralizing and monopolizing access to data, and deploying data to generate profits for other firms (who in turn pay for access to the data). And revenues and profits have no correspondence to the size of the firm's workforce:
Tech companies are notoriously small. Google has around 60,000 direct employees, Facebook has 12,000, while WhatsApp had 55 employees when it was sold to Facebook for $ 19 billion and Instagram had 13 when it was purchased for $ 1 billion. By comparison, in 1962 the most significant companies employed far larger numbers of workers: AT& T had 564,000 employees, Exxon had 150,000 workers, and GM had 605,000 employees. Thus, when we discuss the digital economy, we should bear in mind that it is something broader than just the tech sector defined according to standard classifications. (Kindle Locations 169-174)Marx's theory of capitalism fundamentally originates in a theory of conflict of interest and a theory of exploitation. In Capital that conflict exists between capitalists and workers, and consumers are essentially ignored (except when Marx sometimes refers to the deleterious effects of competition on public health; link). But in Srnicek's reading of the contemporary digital economy (and Elder-Vass's as well) the focus shifts away from labor and towards the consumer. The primary conflict in the digital economy is between the platform firm that seeks to acquire our data and the consumers who want the digital services but who are poorly aware of the cost to their privacy. And here it is more difficult to make an argument about exploitation. Are consumers being exploited in this exchange? Or are they getting fair value through extensive and valuable digital services, for the surrender of their privacy in the form of data collection of clicks, purchases, travel, phone usage, and the countless other ways in which individual data winds up in the aggregation engines?
In an unexpected way, this analysis leads us back to a question that seems to belong in the nineteenth century: what after all is the source of value and wealth? And who has a valid claim on a share? What principles of justice should govern the distribution of the wealth of society? The labor theory of value had an answer to the question, but it is an answer that didn't have a lot of validity in 1850 and has none today. But in that case we need to address the question again. The soaring inequalities of income and wealth that capitalism has produced since 1980 suggest that our economy has lost its control mechanisms for equity; and perhaps this has something to do with the fact that a great deal of the money being generated in capitalism today comes from control of data rather than the adding of value to products through labor. Oddly enough, perhaps Marx's other big idea is relevant here: social ownership of the means of production. If there were a substantial slice of public-sector ownership of big data firms, including financial institutions, the resulting flow of income and wealth might be expected to begin to correct the hyper-inequalities our economy is currently generating.
Right!
ReplyDeleteBig Data aggregated from the public is a public asset that should be taxed. This is an idea that could be part of the easing of income inequality, as well as a path to the future where manual labor is not performed by humans for income.
@Jim Carlson
ReplyDeleteI think you did not understand the core of the argument above. Profit is still the life-blood in capitalis. The system is dominated by private capitalist companies which compete and struve to outperform each other. The profit has to be high enough in aggregate term not only for an individual capitalist. Taxation is one of the obstacles against achieving a high enough rate of profit. For that reason we have seen in the recent years not only an obscene level of inequality, but tax evasion on a gigantic scale (e.g. Panama Files). Some countries imposed 40% corporate tax decades ago and still doing it. Some others, like Britain are going towards 15 % (see the Conservative Party manifesto). So here the state of the economy locally and globally and the political party in government is a key. At the end of the day, capitalists invest if they are making enough profit. Otherwise, they hoard the money. A crisis follows. Then you need "a new economy", or destruction of capital and driving wages down to resume the cycle. In some other cases, you need a massive state investment to get out of the crisis.