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Jacobin
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Venture capital is designed to demand large returns in the short term. This makes VC firms unlikely to support the sort of research that produces technological breakthroughs, which requires generous financing over long periods of time. Science operates on a different timetable than capitalism.
Bill Gates' fund is a 20-year one, as opposed to the more usual 10-year one, but that's not enough
[...] A sharper tone prevails in the New York Times and on Fox News, in statehouses and on Capitol Hill. Criticisms once confined to scholarly circles, or to more oppositional outlets like The Baffler and Valleywag, have become conventional, even banal. One could be uncharitable about the heavy Kool-Aid drinkers who abruptly sobered up — there is no shortage of annoying figures among the late converts to tech critique — but the techlash has been a very good thing. We are at last having a more honest conversation about the internet. The long 1990s are over. The old gods are finally dead.
Who are the new gods? This is what makes our moment so interesting: the conventional wisdom is cracking up but its replacement hasn’t quite consolidated. As James Bridle says, something is wrong on the internet — and something is wrong with the way we have thought about the internet — but there is not yet a widely accepted set of answers to the all-important questions of why these things are wrong, or how to make them right.
Different camps are now competing to provide those answers. They are competing to tell a new story about the internet, one that can explain the origins of our present crisis and offer a roadmap for moving past it. Some talk about monopoly and antitrust. Others emphasize privacy and consent. Shoshana Zuboff proposes the term “surveillance capitalism” to describe the new kinds of for-profit monitoring and manipulation that the internet and associated technologies have made possible.
These analyses have important differences. But they tend to share a liberal understanding of capitalism as a basically beneficent system, if one that occasionally needs state intervention to mitigate its excesses. They also tend to equate capitalism with markets. Sometimes these markets become too consolidated and need to be made more competitive (the antitrust view); sometimes market actors violate the terms of fair exchange and need to be restrained (Zuboff’s view). But two articles of faith always remain. The first is that capitalism is more or less compatible with people’s desire for dignity and self-determination (or can be made so with proper regulation). The second is that capitalism is more or less the same thing as markets.
What if neither belief is true? This is the starting point for building a better story about the internet.
There have always been markets. Capitalism, by contrast, is relatively new. Its laws of motion first emerged in Europe in the fifteenth and sixteenth centuries, and reached escape velocity with industrialization in the eighteenth and nineteenth.
If capitalism didn’t invent markets, however, it did make markets much more important. The historian Robert Brenner observes that capitalism is defined above all by market dependence. Pre-capitalist peasants can trade and barter, but they don’t depend on the market for life’s necessities: they grow their own food. In capitalist societies, on the other hand, the market mediates your access to the means of subsistence. You must buy what you need to survive, and to have the money to do so, you must sell your labor power for a wage.
Market dependence doesn’t exist for its own sake. It serves an important function: to facilitate accumulation. Accumulation is the aim of any capitalist arrangement: to take a sum of value and make more value out of it. While markets are certainly central to capitalism, they aren’t what makes it tick. Accumulation is. To put it in a more Marxist idiom, capital is value in motion. As it moves, it expands. Capitalism, then, is a way to organize human societies for the purpose of making capital move.
There are a few different methods for making capital move. The principal one is for capitalists to purchase people’s labor power, use it to create new value in the form of commodities, and then realize that value as profit by selling those commodities. A portion of the proceeds are reinvested into expanding production, so even more commodities can be made at lower cost, thus enabling our capitalist to compete effectively with the other capitalists selling the same commodities.
This may seem entirely obvious, but it’s actually a very distinctive way of doing things. In other modes of social organization, the point of production is to directly fulfill people’s needs: think of subsistence farmers, growing food for their families to eat. Or the point is to make the rulers rich: think of the slaves of ancient Rome, doing the dirty work so that imperial elites could lead lives of luxury.
What makes capitalism so unusual is that production (and accumulation) isn’t for anything exactly, aside from making it possible to produce (and accumulate) more. This obsession gives capitalism its extraordinary dynamism, and its revolutionary force. It utterly transforms how humans live and, above all, how they produce. Capitalism forces people to produce together, in increasingly complex combinations of labor. Production is no longer solitary, but social.
Yet there was a contradiction lurking here. If no one worker could claim sole credit for a product, the owner of the factory could still claim sole ownership of everything the workers made together. Wealth was being created socially, on a new model — but still owned privately, on the old model.
The contradiction became even sharper when zooming out to consider the wider economy. As many workers as it took to run a Manchester mill, it took even more workers to make that work possible, from the machinists who manufactured and maintained the power looms and the other machines to the slaves in the American South who picked the cotton that kept those machines fed. The collective labor inside the mill was sustained by many concentric circles of collective labor outside of it.
The pre-capitalist economy looked like a cluster of islands — an archipelago. It involved a collection of small producers relatively isolated from one another and producing mostly for personal use. (Marx memorably compared the French peasantry to a sack of potatoes.) By contrast, the capitalist economy looked like a network. The network of capital concentrated masses of people into larger nodes of production and linked them through countless threads of interdependence. Yet the wealth that this network generated didn’t flow to the many workers who collectively created that wealth. It flowed to the few who owned the network: the capitalists.
Before capitalism, when production happened on a more personal basis, such an arrangement might’ve made sense. If the economy was a cluster of islands, it followed that each island would own what it made. But capitalism, by revolutionizing production, introduced a contradiction: wealth was now made as a network, but still owned as an archipelago. Capitalists like Engels’ father became rich. The workers of Manchester earned starvation wages, and lived in cholera-infested slums.
yooo
It’s hard to imagine a more extreme form of the contradiction on display at Manchester than a social network of more than two billion people ruled by a single billionaire. The network of capital has become denser, and more literal, than Engels could’ve possibly imagined, while its control has become concentrated in even fewer hands.
To observe that Facebook has relatively few workers is not to suggest that the work they perform is not important. Without content moderators, data center technicians, site reliability engineers, and others, Facebook’s product would become unusable and its business would collapse. But their collective labor, like that of the workers within Engels’ father’s factory, depends on many concentric circles of collective labor outside of it. And, for Facebook and the other firms that fall under the umbrella of tech, the share of value supplied by these external layers is especially vast.
One source is the workers who invented the software, hardware, protocols, and programming languages that laid the basis for today’s tech industry. These were developed over the course of several decades, starting with the creation of the first modern electronic computers in the 1940s, and relied heavily, often exclusively, on US military funding. Another source is the workers who, in the present day, continue to make and maintain the stuff on which tech profits depend. While this work takes many forms, most of it is menial or dangerous. It includes manufacturing smartphones, mining rare earth elements, and labeling training data for machine learning models.
[...]
The upshot is a world where the creation of wealth becomes more collective than ever before. In the nineteenth century, Engels reflected on how capitalism transformed production “from a series of individual into a series of social acts.” The total enclosure of our world by computing means that those social acts can now happen at the scale of entire societies. The industrial factory has become what Terranova and others, building on a term from Italian autonomism, call the “social factory.” The new Manchester is everywhere.
useful summary of the "free labor" debates debate
[...] these divisions were constantly being reinforced, since they served a valuable purpose: they helped make exploitation seem justified, even natural.
Thus it was natural for the Irish to be paid less and live in appalling slums. It was natural for women to be paid less while also performing the unpaid work of raising children — children who went into the mills as young as five. It was natural to enslave human beings of African origin and put them to work harvesting the cotton that those mills turned into textiles. It was natural to dispossess and exterminate the Indigenous people who had formerly inhabited the land that became those cotton fields.
Capitalism doesn’t invent human difference, of course. Humans look different; they speak different languages; they come from different communities and cultures. But capitalism makes these differences make more of a difference to people’s lives. Differences become more differential. They become differences of capacity and value — differences in how much a human being is worth, or if they’re even considered human at all.
The political scientist Cedric J. Robinson argued that this difference-making has been a core feature of capitalism from the beginning — he called it racial capitalism for this reason. Feudal Europe was highly racialized, Robinson said. As Europeans conquered and colonized one another, they came up with ideas about racial difference in order to justify why, for instance, Slavs should be slaves. (In fact, Slavs were so frequently enslaved in the Middle Ages that they supplied the source of the word “slave,” in English and several other European languages.)
If racial thinking saturated the societies where capitalism first emerged, capitalism subsequently picked up these concepts and extended them. It generated deeper and more varied ideas about racial difference in order to justify the new relationships of domination that the imperative of accumulation demanded — particularly as Europeans began carving up Asia, Africa, and the Americas. “The tendency of European civilization through capitalism,” Robinson wrote, “was thus not to homogenize but to differentiate — to exaggerate regional, subcultural, and dialectical differences into ‘racial’ ones.”
Robinson’s insight helps clarify another crucial aspect of how tech operates. If tech intensifies capitalism’s contradiction between wealth being collectively produced and privately owned, it also intensifies capitalism’s tendency to slice people into different groups and assign them different capacities and values. Indeed, the two operations are closely related. “Capital can only be capital when it is accumulating,” says the theorist Jodi Melamed, “and it can only accumulate by producing and moving through relations of severe inequality among human groups.” The network for making wealth, in other words, relies on the engine for making difference.
That engine is now made of software. Differentiation happens at an algorithmic level. The abundant data that flows from mass digitization, combined with the ability of machine learning algorithms to find patterns in that data, has given capitalism vastly more powerful tools for segmenting and sorting humanity.
Way back in 1993, the media scholar Oscar H. Gandy, Jr. offered an extremely prescient view of how this works. He called it “the panoptic sort,” in a book of the same name. “The panoptic sort is a difference machine that sorts individuals into categories and classes on the basis of routine measurements,” he wrote. “It is a discriminatory technology that allocates options and opportunities on the basis of those measures and the administrative models that they inform.”
The role of these systems is not just to reproduce inequalities, but to naturalize them. Capitalist difference-making has always required a substantial amount of ideological labor to sustain it. For hundreds of years, philosophers and priests and scientists and statesmen have had to keep saying, over and over, that some people really are less human than others — that some people deserve to have their land taken, or their freedom, or their bodies ruled over or used up, or their lives or labor devalued. These ideas do not sprout and spread spontaneously. They must be very deliberately transmitted over time and space, across generations and continents. They must be taught in schools and churches, embodied in laws and practices, enforced in the home and on the street.
It takes a lot of work. Machine learning systems help automate that work. They leverage the supposed authority and neutrality of computers to make the differences generated by capitalism look like differences generated by nature. Because a computer is saying that Black people commit more crime or that women can’t be software engineers, it must be true. To paraphrase one right-wing commentator, algorithms are just math, and math can’t be racist. Thus machine learning comes to automate not only the production of inequality but its rationalization.