by
Nick Srnicek
archive/mc433
Franklin Foer,
Christian Fuchs,
Wolfgang Streeck,
Frank Pasquale,
Evgeny Morozov,
George Ritzer,
Nick Srnicek,
Nancy Fraser,
Arjun Appadurai,
Yann Moulier-Boutang
tech and justice essay quotes
[...] capitalism has turned to data as one way to maintain economic growth and vitality in the face of a sluggish production sector. [...]
think about this in the context of Immanuel Wallerstein's World-Systems theory & running out of markets to expand to
but this is just an easy temporary fix, akin to deleting a few stale keys in redis when you run out of memory (or actually that's not a good analogy--think of a better one)
[...] At one end, tax evasion and cash hoarding have left US companies--particularly tech companies--with a vast amount of money to invest. This glut of corporate savings has--both directly and indirectly--combined with a loose monetary policy to strengthen the pursuit of riskier investments for the sake of a decent return. And at the other end, tax evasion is, by definition, a drain on government revenues and therefore has exacerbated austerity. The vast amount of tax money that goes missing in tax havens must be made up elsewhere. The result in further limitations on fiscal stimulus and a greater need for unorthodox monetary policies. Tax evasion, austerity, and extraordinary monetary policies are all mutually reinforcing.
one could argue that this tax evasion/avoidance isn't really that serious since the amount of tax to be paid is arbitrary anyway, and if it's all legal, then why does it matter? the response to that is less moral (for which the answer is obvious: corporations benefit from government infrastructure and thus should attempt to pay the set tax rate in good faith) and more about long-term efficiency ... a corporation operating in a state that has lower tax revenues will 1) have shittier infrastructure and 2) put the average person through more hardship, meaning that not only are they less likely to be able to afford to buy products, they are (hopefully) more likely to rise up and demand change, potentially at a disastrous cost for the corporation
[...] 'once we understand this [tendency], it becomes clear that demanding privacy from surveillance capitalists or lobbying for an end to commercial surveillance on the Internet is like asking Henry Ford to make each Model T by hand'. Calls for privacy miss how the suppression of privacy is at the heart of this business model. [...]
on companies like Google collecting all sorts of privacy-infringing data on users
quoting Shoshana Zuboff in http://www.faz.net/aktuell/feuilleton/debatten/the-digital-debate/shoshana-zuboff-secrets-of-surveillance-capitalism-14103616.html
[...] markets do not simply dissolve status distinctions; rather, they instrumentalize them, bending pre-existing patterns of cultural value to capitalist purposes. For example, racial hierarchies that long predated capitalism were not abolished with the dismantling of New World slavery or even of Jim Crow, but reconfigured to suit a market society. No longer explicitly codified in law, and no longer socially legitimate, racist norms have been wired into the infrastructure of capitalist labor markets. Thus, the net result of marketization is the modernization, not supersession, of status subordination.
The distinction between affirmation and transformation can be applied, first of all, to the perspective of distributive justice. In this perspective, the paradigmatic example of an affirmative strategy is the liberal welfare state, which aims to redress maldistribution through income transfers. Relying heavily on public assistance, this approach seeks to increase the consumption share of the disadvantaged, while leaving intact the underlying economic structure. In contrast, the classic example of a transformative strategy is socialism. Here the aim is to redress unjust distribution at the root--by transforming the framework that generates it. Far from simply altering the end-state distribution of consumption shares, this approach would change the division of labor, the forms of ownership, and other deep structures of the economic system.
she says later that affirmative strategies can actually promote misrecognition (e.g., liberal welfare state programs that mark the poor as "needy")
[...] Since the massification of computing they have in some small ways also been able to construct themselves in relation to other forms of life. (In the sense that Ludwig Wittgenstein means when he says, "To imagine a language is to imagine a form of life.") This self-sufficiency of software, in such a context, allows (in much the same way as it allows a programmer to think he or she is working on the formulation of a particularly interesting and chewy algorithm when working at another scale, perhaps more determining, on an insurance program to more finely exclude the poor from public services) a certain distance from social or cultural norms. Things can be done in software that don't require much dependence on other factors. [...]
[...] technology can embody valid knowledge and constitute a set of reliable, seemingly neutral tools or points of leverage over nature and at the same time constitute an instance of prevailing, hegemonic social rationality and so be implicated in social power. [...]
on Andrew Feenberg's critical theory, developed to address the mistaken (in his opinion) assumption that technology is predominantly being used to oppress workers simply because capitalism is "scientific"
More benignly, perhaps, these companies influence the choices we make ourselves. Recommendation engines at Amazon and YouTube affect an automated familiarity, gently suggesting offerings they think we’ll like. But don’t discount the significance of that “perhaps.” The economic, political, and cultural agendas behind their suggestions are hard to unravel. As middlemen, they specialize in shifting alliances, sometimes advancing the interests of customers, sometimes suppliers: all to orchestrate an online world that maximizes their own profits.
So why does this all matter? It matters because authority is increasingly expressed algorithmically. Decisions that used to be based on human reflection are now made automatically. [...]
[...] In their race for the most profitable methods of mapping social reality, the data scientists of Silicon Valley and Wall Street tend to treat recommendations as purely technical problems. The values and prerogatives that the encoded rules enact are hidden within black boxes.
[...] Marketers plot to tout beauty products at moments of the day that women feel least attractive. There’s little to stop them from compiling digital dossiers of the vulnerabilities of each of us. In the hall of mirrors of online marketing, discrimination can easily masquerade as innovation.
using data to overcome more of our natural defenses against advertising