Back in 1974, Harry Braverman published his magnum opus, Labor and Monopoly Capital, a work that became a landmark of twentieth-century Marxist analysis. Indeed, I would say that it is one of the best pieces of American Marxist writing. Braverman's central claim was stark: modern capitalism systematically separates conception from execution. Management plans. Workers carry out. Over time, skill and knowledge are pulled away from labor and concentrated in management. Braverman contended that this process was not accidental. It was structural. Capital, driven by competition, seeks control over the labor process. And control requires reducing dependence on workers' tacit knowledge. Braverman drew on what is often called the Babbage principle, associated with the nineteenth-century engineer, mathematician and economist, Charles Babbage. The principle is simple: break complex work into discrete tasks and assign each task to the cheapest labor capable of performing it. Instead of employing one highly skilled worker to complete an entire process, management decomposes the work. Skilled components are minimized. Routine components are assigned to lower-paid workers. Costs fall. Control increases. For Braverman, this logic defined industrial capitalism. But what happens when we shift from factory labor to artificial intelligence, which after all, was not a factor in industrial production during Braverman's lifetime? AI as the Ultimate Task Fragmenter AI is often presented in both the professional literature and the popular media as a radical rupture with the past. Yet from the standpoint of the Babbage principle, it looks more like a powerful continuation. https://www.academia.edu/164729636/AI_the_Babbage_Principle_and_the_New_Economics_of_Control ( https://www.academia.edu/164729636/AI_the_Babbage_Principle_and_the_New_Economics_of_Control )
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