Radical Hegemon
by Jennie Rose Halperin
In a widely-shared 2021 interview, science fiction writer Ted Chiang connected capitalist realism with the growing fear of artificial intelligence.
“Most fears about A.I. are best understood as fears about capitalism,” Chiang said, “that is, the unexamined assumption [of] the inevitability of technological change and technologically-induced unemployment. We take it as an assumption that [capitalism] will always exist and that we will never escape it.” He went on to situate the source of these fears not in capitalism per se but in its practitioners, contrasting the exploitative environment capitalists have built for U.S. workers with worker-friendly, Scandinavian-style childcare and healthcare; policy interventions like these, he supposed, would make it possible to “separate an evaluation of the merits and drawbacks of technology from the framework of capitalism.”
In the five years since that interview, it’s become clear that the potential of new technologies has only grown more constrained by the entanglement of technology and capital, particularly when considered in the context of academic research.
The boundary between industry and research in computer science has been permeable since before the days of ARPANET; by the time AI rolled around, the line was fully blurred. Many of the core training datasets for frontier AI companies like Books3, Diversity in Faces, and Common Crawl originated as legitimate academic or nonprofit datasets, which were later exploited by industry to build their commercial products.
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