I found Lyotard’s treatment of the relationships between science, technology, money, power to be particularly salient but at times problematic. Lyotard’s basic sketch of the production of late-capitalist scientific knowledge as an “equation between wealth, efficiency, and truth” (45) is certainly justified by a quick look at the bankrolls of major scientific research centers inside and outside of the academy. Dominant metanarratives of science portray science as a disinterested pursuit of truth, which, within these narratives, is self-legitimating based on notions of the human spirit’s “fundamental desire” to increase knowledge and expose this “truth.” The large-scale infusion of private corporations into scientific research and development apparatuses dismantles this narrative handily and, in so doing, raises the question of the relationship between the financial ability to conduct science, the knowledges produced by for-profit research efforts, and the augmentation of consolidation of power through control of the dominant means of scientific advancement. Based on Lyotard’s vision, a feedback loop is created:
moneyàscientific apparatus/research fundingàknowledgeàpoweràmoneyà
ad infinitum.
My question is whether or not this continuous consolidation of power, knowledge, money, and scientific research allows room for intervention or subversion? Will we continue to see the consolidation of knowledge production in the hands of the wealthy and powerful, or can we locate sites at which science resists this one-way flow, subverts dominant regimes of power, or simply proceeds “in the name of science?”
I was also fascinated by Lyotard’s discussion of the mechanical automatization of teaching, which brought me back to Weiner’s oft-misinterpreted visions of the automatization of society. I am skeptical of Lyotard’s argument that “pedagogy would not necessarily suffer” in the replacement of professors by machines. It is true that such a system would teach new skills (new languages, better manipulation of language games), and the mercantilization of knowledge certainly elevates the value of efficiency above that of truth. However, much larger questions are raised by Lyotard’s automatization scheme: who will teach the computers that will then teach humans, and by what pedagogy will these computer-teachers operate? Do computers allow for the efficiency of knowledge exchange that human teaching can offer (for instance, 1 professor teaching 500 students)? Will people accept and, most importantly, pay for this?
A few pages later, Lyotard seems to partially deconstruct his argument regarding the obsolescence of the professor and the possibility of teaching by machine. Addressing interdisciplinary studies as a site of cross-currents of disparate knowledge devoid of metanarrative, Lyotard underscores the centrality of brainstorming and teamwork in the understanding of these new forms of knowledge. These operations, uniquely human and incapable of machine replacement, probably represent the biggest new trend in academia and, as a consequence, necessitate the allocation of more professors, students, and resources. Here, the professor doesn’t serve merely to “transmit established knowledge;” (53) he or she is a facilitator of new connections and a steward of increased teamwork. Replacing the interdisciplinary professor with a machine would create the exact type of rigid framework of knowledge that interdisciplinary studies seeks to undermine and problematize, thus rendering it inneficient, wasteful, and backward.
Lastly, and briefly, I found Lyotard’s ultimatim to “give the public free access to the memory and data banks” to be at once prescient and reassuring. In a time in which net neutrality and access to information is constantly being threatened by the intrusion of governments, corporations, groups, and individuals, Lyotard’s early call for openness and free access rings more true and important than ever.
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