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robertogreco : technocapitalism   1

Optimize What? • Commune
"Silicon Valley is full of the stupidest geniuses you’ll ever meet. The problem begins in the classrooms where computer science is taught."



"In higher education and research, the situation is similar, if further removed from the harsh realities of technocapitalism. Computer science in the academy is a minefield of contradictions: a Stanford undergraduate may attend class and learn how to extract information from users during the day, then later attend an evening meeting of the student organization CS+Social Good, where they will build a website for a local nonprofit. Meanwhile, a researcher who attended last year’s Conference on Economics and Computation would have sat through a talk on maximizing ad revenue, then perhaps participated the next morning in a new workshop on “mechanism design for social good.”

It is in this climate that we, too, must construct our vision for computer science and its applications. We might as well start from scratch: in a recent article for Tribune, Wendy Liu calls to “abolish Silicon Valley.” By this she means not the naive rejection of high technology, but the transformation of the industry into one funded, owned, and controlled by workers and the broader society—a people’s technology sector.

Silicon Valley, however, does not exist in an intellectual vacuum; it depends on a certain type of computer science discipline. Therefore, a people’s remake of the Valley will require a people’s computer science. Can we envision this? Today, computer science departments don’t just generate capitalist realism—they are themselves ruled by it. Only those research topics that carry implications for profit extraction or military applications are deemed worthy of investigation. There is no escaping the reach of this intellectual-cultural regime; even the most aloof theoreticians feel the need to justify their work by lining their paper introductions and grant proposals with spurious connections to the latest industry fads. Those who are more idealistic or indignant (or tenured) insist that the academy carve out space for “useless” research as well. However, this dichotomy between “industry applications” and “pure research” ignores the material reality that research funding comes largely from corporate behemoths and defense agencies, and that contemporary computer science is a political enterprise regardless of its wishful apolitical intentions.

In place of this suffocating ideological fog, what we must construct is a notion of communist realism in science: that only projects in direct or indirect service to people and planet will have any hope of being funded, of receiving the esteem of the research community, or even of being considered intellectually interesting. What would a communist computer science look like? Can we imagine researchers devising algorithms for participatory economic planning? Machine learning for estimating socially necessary labor time? Decentralized protocols for coordinating supply chains between communes?

Allin Cottrell and Paul Cockshott, two of the few contemporary academics who tackle problems of computational economics in non-market settings, had this to say in a 1993 paper:
Our investigations enable us to identify one component of the problem (with economic planning): the material conditions (computational technology) for effective socialist planning of a complex peacetime economy were not realized before, say, the mid-1980s. If we are right, the most notorious features of the Soviet economy (chronically incoherent plans, recurrent shortages and surpluses, lack of responsiveness to consumer demand), while in part the result of misguided policies, were to some degree inevitable consequences of the attempt to operate a system of central planning before its time. The irony is obvious: socialism was being rejected at the very moment when it was becoming a real possibility.


Politically, much has changed since these words were written. The takeaway for contemporary readers is not necessarily that we should devote ourselves to central planning once more; rather, it’s that our moment carries a unique mixture of ideological impasse and emancipatory potential, ironically both driven in large part by technological development. The cold science of computation seems to declare that social progress is over—there can only be technological progress. Yet if we manage to wrest control of technology from Silicon Valley and the Ivory Tower, the possibilities for postcapitalist society are seemingly endless. The twenty-first-century tech workers’ movement, a hopeful vehicle for delivering us towards such prospects, is nascent—but it is increasingly a force to be reckoned with, and, at the risk of getting carried away, we should start imagining the future we wish to inhabit. It’s time we began conceptualizing, and perhaps prototyping, computation and information in a workers’ world. It’s time to start conceiving of a new left-wing science."
engineering  problemsolving  capitalism  computers  politics  technology  jimmywu  2019  optimization  efficiency  allincottrell  paulcockshott  siliconvalley  techosolutionism  technocapitalism  computation  wendyliu  compsci  ideology 
april 2019 by robertogreco

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