The story of global industry in the 21st century could be told through the perspective of three firms: Google, Facebook and Amazon. Google acts as the gatekeeper to the vast reservoir of human knowledge, Facebook as the default (for better or worse) public square, and Amazon as a retail behemoth, which is slowly cannibalizing the industry, gorging both competitors and sellers alike. These actors make up three of the 10 most valuable firms in the world, and each of their particular powers is often compared to that of sovereign governments; Facebook and Google act as de facto Ministries of Information, wielding immense power over who and what is worthy of public display, while Amazon has effectively gained the power to assert regulatory control over the e-commerce industry. Being that these three firms — along with other tech “disruptors” such as Uber and AirBnb — have market valuations in the billions, an Econ 101-educated extraterrestrial observing our world from afar would be surprised to learn what is perhaps the most “disruptive” aspect of our new platform overlords: that they make little to no profit on their front-end use.  

When the influential, early 20th-century economist Joseph Schumpeter — a right wing libertarian nethertheless working off Karl Marx’s theories of early capitalist economies — described capitalism’s ceaseless, glutinous need to tear down existing modes of capital accumulation for new forms as a system of “creative destruction,” one wonders if he could’ve possibly predicted this development. What many tech firms have done is almost break the physics of economics. Instead of earlier modes of business practices, where a company would provide a product at a market price for consumption by its users, for which it would make its profit, the front-end services many tech companies provide is entirely separate from its commercial use: the mass extraction of user data for sale to third-parties and private use to fine-tune their AI suggestion algorithms.

For example, while Google and Facebook offer their services for free, they make their profit by extracting data from their users for sale to advertisers, market research companies, shadowy political data firms and more. Our interests, desires, jealousies, insecurities and fears are mined and sacrificed at the ever-expanding altar of data accumulation. Similarly, Amazon and Uber — while indeed charging for their front end use — often operate at losses on those uses and rather focus on other aspects for their commercial purpose; Uber’s ride-sharing service is notoriously unprofitable and, in true Silicon Valley fashion, has stayed alive by way of stock speculation and venture capital, which has buoyed its survival.  Rather, Uber’s extraction of city transportation information and logistics is the platform’s main source of profit. Amazon, a slightly different case, uses its highly profitable cloud-computing business to host other companies’ data on their servers, such as Netflix, even though they are technically competitors in terms of streaming services. 

The development of such methods of extraction and accumulation represents a massive shift in the global economy, and has occurred thanks to favorable shifts in the preferences of investors and the enforcement of antitrust. Investors, for example, tend to value growth more than profitability when it comes to tech startups; it doesn’t matter if firms such as Amazon and Uber can’t technically compete according to the merits of competitive markets if their massive network effects will eventually allow them to take over the market itself. Similarly, Google, Facebook and Amazon have benefited from a massive relaxation in antitrust law since the conservative revolution in the field during the 1980s. As antitrust law switched to a narrow focus of consumer price and a dubious definition of “efficiency,” the three giants of the digital economy have been effectively shielded from being defined as a “monopoly,” despite their abilities to dictate the terms of the markets they dominate, which, in the case of Amazon, have ripple effects throughout multiple sectors of the economy, including the power to hold down wages

Such developments are critical to the rise of Platform Capitalism, or what PR-soaked Silicon Valley acolytes would call the “sharing economy.” The logic of platform capitalism works like this: A heavily leveraged tech startup such as Uber or Airbnb provides a platform to connect people to each other — Uber connects riders to drivers; Airbnb, prospective short-term tenants to renters, and so on — and sets the governance structure for how they can interact. Aside from the numerous problems that arise from particular business practices, such as Uber’s pernicious redefinition of the employee under the guise of “being your own boss” and AirBnb’s contributions to rising rents in the cities in which it operates, the practice of the platform provides ample ground for the harvesting of data from its consumers. The fruits of such extraction are withheld from the cities in which they operate under a panoply of intellectual property protections and unequal bargaining power. 

If any of this sounds relatively banal, it shouldn’t. The slow death of traditional notions of profitability and the rise of the data economy represents a rupture in the very foundation of our society; data provides a capital stream whose value is almost completely untethered from the labor (our activities on said platforms) required to manufacture and use it. This allows for almost infinite speculative activity for shareholders and investors, who are not known to shy away from new avenues of exploitation, and the subsequent returns on our activities are concentrated within their hands. The way this data is harvested — and the specific uses for which they are harvested — is purposely opaque, and is increasingly being used for oppressive purposes. 

The story of the data economy is, in a sense, the story of capitalism as a whole; with its constant need for new avenues of extraction, the creation of data for profit mirrors both commodities and capital: commodities in that data could be seen as a  “natural resource” such as oil, and capital in that it must be constantly being created and circulated, and that this circulation, as Marx stated of capital 150 years ago, is an end in and of itself. The practice of data extraction must insert its logic everywhere; when Facebook or Google make inroads into India and the Global South under the sunny pretense of “connecting” impoverished people to the internet, what they’re really doing is penetrating new markets, ones in which the intellectual activity of its citizens has not yet been subsumed and commodified as data. As the academic Jathan Sadowski noted in his recent paper, “When data is capital: Datafication, accumulation, and extraction,” such practices act as a form of data colonialism, wherein tech firms lock populations into their platforms and extract data according to their own internal rules, with little to no input from governments or citizens. 

As long as the extraction of data remains outside the purview of legislators and democracy, it will be used to further contribute to the power imbalance already too prevalent in our society. This is perhaps most evident in targeted advertisement sales and the datafication of employment. In an excellent recent paper by Sam Adler-Bell and Michelle Miller of The Century Foundation, a progressive think tank, the implications of increasing datafication untethered from regulation are made apparent. A 2015 study from Carnegie Mellon University found that Google was more likely to show ads for high-paying jobs to men than women; predatory for-profit colleges had been shown to cater their ads to low-income students, and people who are “scored” as financially desperate are increasingly shown ads for payday loan services and a vast array of other targeted ads in which more affluent users are not. Additionally, with Facebook, a recently patented technology helps credit lenders reject people for loans based on their income and social media activity. These methods, which, coupled with the profit motive apparent in the ceaseless accumulation of user data, do not appear to be slowing down any time soon, and could lead to the emergence of redlining in the digital sphere. Such developments are what legal scholar Frank Pasquale deems “The Scored Society,” in which unevenly accessed and distributed data could further determine our social worthiness — of jobs, career and educational opportunities, loans and whatever else the logic of profit-generating data accumulation inserts itself into. Such sentiments should seem obvious: financial and technological innovations inevitably mirror the economic conditions and practices in which they arise. As long as our political economy becomes increasingly secretive, privatised and atomized under the totalizing logic of “efficiency” and consumer convenience, the technological innovations that emerge in it will benefit an increasingly small group, monopolizing progress.

The pernicious uses of personal data — developed and fine-tuned by our aforementioned tech giants — are increasingly making their way into the workplace as well. Data is now being used to mine and extract value from individual workers, obtaining information about consumer habits, health conditions, socio-economic status and even browser activity. Such developments have massive implications for hiring, on-the-job monitoring and even exiting a job. For example, an increasingly concentrated and amply funded workplace data industry is able to determine who and who does not get hired according to a vague and possibly unfair set of criteria. Job applicants with default browsers have been found to stay at a job for shorter periods of time than those with, say, Google Chrome. This may lead to a workplace data company such as Cornerstone scoring them lower for employment opportunities for this arbitrary reason. Shadowy third-party firms conduct credit scores on potential applicants according to methods that are far from transparent, and workers are left with no recourse to dispute such claims. As long as such methods of data-use are not subject to civil rights laws, such problems will continue. On-the-job performance tracking is implemented with no input or understanding of the rules from workers. Such methods have their most obvious effects in the gig economy such as Uber and Instacart, which supplement the traditional notion of a manager for data-driven algorithms. Adler-Bell and Miller describe such problems below:

“Without any straightforward rules or understanding to explain to workers how the algorithms pay them, workers must engage in a costly trial-and-error process to understand how their behaviors affect their scores, and thus their take home pay. Last year, workers for Instacart, the same-day grocery delivery service, were taken by surprise when the company suddenly added a ‘service fee”’ that customers mistook for an automatically included tip, causing a sudden drop in wages. And these same Instacart couriers have to start out with no clear information up front about the most lucrative time periods to be available for shifts—they have to learn it, at their own economic risk, over time.” 

In a perfect free market, this wouldn’t be as much of a problem. But as Marshall Steinbaum of The Roosevelt Institute has shown, increasing market concentration, in which tech firms and other companies own an increasingly consolidated share of markets, drastically reduce worker power and choice. Once again, innovations mirror the societies in which they arise, and currently, the tremendous productive powers of data are only being felt by one side of the worker-employer relationship, with no downward distribution. 

The process of data accumulation is not dangerous in the abstract. Rather, the question of who benefits from such an innovation deserves further examination. The very process of data extraction is only made possible by the consumers and workers it utilizes. Contrary to typical neo-feudal definitions of “innovation” and “capitalist vision,” the tech behemoths have merely derived their data-fortunes from the intellectual activity of citizens, and have previously benefited from loopholes in laws and already-existing developments in technology, all of which were the product of human labor. This is without even  mentioning the role that rent-seeking — merely the owning of productive, value creating agents — plays in all this (this is the very essence of the aforementioned platform capitalism). It is thus worth asking exactly how data can be harvested in accordance with the public interest. The modern city may hold the answer. 

European cities such as Barcelona and Amsterdam have joined project DECODE, an initiative meant to reclaim a semblance of the “data commons,” i.e providing open-source software that is open to possible avenues of innovation for anyone to contribute to. The socialization of data by way of platform cooperatives and the like essentially turn the data that is generated in cities into a meta-utility. Providing open access to crucial information such as infrastructure, air quality, health and local business information could help municipalities develop innovative technologies with the public good at the forefront, rather than simply the profit motive. 

Perhaps the most dangerous component of the data economy is the extent to which access to data is withheld from the public by tech firms by way of intellectual property protections, which economists Dean Baker and Joseph Stiglitz have argued actively hurts innovation by shielding competitors and the public from entry into innovative endeavors. The socialization of data — with adequate funding from governments and proper privacy protections for citizens — could help buck this trend. This, along with proper regulation to ensure that firms act in accordance with the public interest, is the key to ensuring data extraction does not merely act as another complicit agent on the way to a second gilded age.

When evaluating the potential society-rupturing effects of new innovations and technological progress, one must always ask themselves the questions: “Innovation for who? Progress for who?” Silicon Valley billionaires and power-justifying Davos-Conference lackeys like Steven Pinker may evangelize about how wealth and progress isn’t “zero-sum,” but the above examples of power-imbalances within workplaces and access to data in general show that this worldview is necessarily incoherent. This is especially so in a world where the wealth of billionaires has grown 12 percent while the world’s poorest have seen theirs decrease by 11 percent, all while wages and standards of living continue to stagnate and decline throughout the West — this argument fails even according to its own superficial foundations. While the vast expansion of the productive powers of data, AI and platform behemoths provide superficial benefits to consumers in the form of convenience, it is up to us to ensure that the value extracted from users is not used in turn to contribute to an asymmetrical society, in which the mass faces increasing uncertainty while the few monopolize progress. 

We shouldn’t let them.


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