To make this argument, we discuss why Marx assumed both labour and value creation to be inherently human, zeroing in on the sharp distinction he makes between humans and animals. We consider why he grounds this distinction in various capabilities like creativity and imagination, and how some AI projects, as of 2019, are trying to automate such capabilities. While the previous chapters have engaged in some necessary speculation, this chapter envisages a distant future that is more science fiction than science fact. Thus, before we delve into the specifics of Marx’s value theory and his arguments about human uniqueness, we first justify why we are devoting a chapter to a technology that has yet to, and might never, see the light of day.
ARTIFICIAL GENERAL INTELLIGENCE
No scientific or philosophical consensus exists on the definition of intelligence, but most perspectives agree that true intelligence must be to some degree flexible or general (Kaplan 2016; Lake et al. 2017: 9–19). Existing ML and GOFAI are distinguished from human intelligence by their narrowness and inflexibility. Research is, however, underway to produce AI which can be generally applied – AGI. The term AGI was first introduced by Mark Avrum Gubrud (1997) to describe ‘AI systems that rival or surpass the human brain in complexity and speed, that can acquire, manipulate and reason with general knowledge, and that are usable in essentially any phase of industrial or military operations where a human intelligence would otherwise be needed.’ The idea of AGI, however, actually dates back to the original goal of the 1956 Dartmouth workshop (Wang and Goertzel 2007: 6). But the goal of emulating human intelligence was quickly abandoned in favour of more manageable practical problems that could be solved by narrow AI, and until the early 2000s AGI was considered so unrealistic that people working on it were seen as crackpots (Pennachin and Goertzel 2007: 1; Wang and Goertzel 2007: 4). While there were research projects that were focused on the goal of building AGI, such as the Soar cognitive architecture that John Laird, Allen Newell and Paul Rosenbloom started in 1983 (Laird
perfect machines, inhuman labour
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