Caffentzis argued that the apparent job-destroying powers of AI had to be considered in light of its antithesis, the expansion of the service sector and global sweatshops; one had to think ‘Africa’ and ‘automata’ together. He draws on the ninth chapter of Volume 3 of Capital, ‘Formation of a General Rate of Profit (Average Rate of Profit) and Transformation of Commodity Values into Prices of Production’ (1991: 254–73). Here Marx suggested that while the profit extracted by capital as a whole depends on the overall amount of surplus-value extracted within its entire system, there is no direct correspondence between any individual capitalist’s profit and the amount of socially necessary labour they employ. Value is a social phenomenon and any and all value produced goes into a social pool after the commodities have been exchanged. But capitalists also appropriate surplus-value from this pool in the form of profit; an individual capitalist will appropriate more profit if their capital, relative to other capitals, is of a larger size, has a higher organic composition, and a higher average profit rate (Marx 1991: 241–73; Caffentzis 2013: 132–4). Thus highly automated businesses syphon-off the surplus-value generated by labour-intensive capital. Caffentzis called this ‘the law of the increasing dispersion of organic composition’, by which ‘every increase in the introduction of science and technology ... in one branch of industry ... will lead to an equivalent increase in the introduction of low organic composition production in [an]other’ (2008: 65). Caffentzis’s account of capital’s contradictory movements towards high-technology (automata) and low-wage-labour (Africa) suggests reflection on how its current AI-fever is induced not only by technological breakthroughs, but by increasing frustrations in finding cheap labour.
AI NOVUM
Before and during the writing of this book, in addition to assimilating materials about Marxist theory and the science, economics and sociology of AI, we read and watched a great deal of AI science fiction (henceforward, AI-SF), including not just the classic films – 2001, Blade Runner, Terminator – that are inevitable points of reference for all AI discussion, but a wave of more recent writings and productions that accompanied the emergence of ML. Some will regard this as evidence of impaired judgement. Harry Collins (2018: 5–13) renames AI as ‘Artifictional Intelligence’ because, he argues, SF has encouraged a widespread overestimate of AI capabilities: depictions of the purported superhuman singularity encourage ‘the surrender’ – human abdication to stupid computer programs. Similarly, Mike Cook (2018), an AI researcher, designates AI-SF, alongside excessive respect for scientists and the over-selling of AI, as one of a set of cultural factors contributing to a ‘basic lack of understanding’ about what ML can and cannot do.
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inhuman power