The machine… is a mechanism that, after being set in motion, performs with its tools the same operations as the worker formerly did with similar tools. (Capital, Chapter 15, p. 495).
For Marx, a machine consisted of three parts. In modern terms, the power supply, the transmission mechanism, and the powered-tool itself. A few differences in detail - we mostly convert a power source (wind, sun, fossil fuels) to electricity in order to use it - should not prevent us from seeing the essential continuity between the machinery of Marx’s day and contemporary computerized machines. Indeed, robots fit this schema exactly, because we consider robots to be powered-tools rather than… well, whatever we think a computer is (I will return to this question in a moment).
In their recent book, Inhuman Power: Artificial Intelligence and the Future of Capitalism, Nick Dyer-Witheford, Atle Mikkola Kjøsen, and James Steinhoff draw a rigid distinction between robots and AI. Basing their understanding of robotics on Alan Winfield’s definition, Dyer-Witheford, Kjøsen, and Steinhoff argue that while “all robots have bodies”, “AI is software and, therefore, need not be embodied, though it requires computing hardware to run on” (10). It seems to me that this distinction is spurious: what is the difference between a robot “body” and the hardware that runs software? The rest of Winfield’s definition states that robots (but not computers) can sense and act on their environment, and that they can “autonomously carry out useful work”. However, consider a light-monitoring application in a so-called “smart home”. It can sense the light levels within the house, and it can turn on or off various lights to fit the parameters of the “useful work” it has been programmed to perform. Is this a robot or a computer?
I think the distinction between robots and computers stems from two things. In the first place, robots are seen as a continuation of earlier automation technologies while computers are seen as something radically new and different (Lovelace and Babbage’s engines notwithstanding). In the second place, robots were originally “hard-coded”, that is, their function was determined through the physical operation of parts, rather than by a separate, programmed control mechanism (software). (Early computers operated like this too, of course, but Turing’s theoretical papers consigned this fact to a historical curiosity, easily ignored). The fact that robots are now software-driven is ignored in maintaining a hard distinction between a computer and a robot. In fact, there is pretty much no difference: a robot can be understood as a computer with a particular set of peripherals. The distinction between robot and computer is historically determined, but does not hold up in contemporary terms.
But what about software. Despite their caveat that software “requires computing hardware to run”, Dyer-Witheford, Kjøsen, and Steinhoff claim that “software… need not be embodied”. If robots are embodied, and there is no real distinction between robots and computers, then the idea that software need not be embodied collapses. As the adage goes, “the cloud is just someone else’s computer”.
I think that the mistake made here stems, again, from the early days of the computer. For Turing, in his 1938 paper on the Entscheidungsproblem in which he defines the Turing machine, the computer is a virtual machine whose purpose is computation. For Norbert Wiener, on the other hand, the computer is a control mechanism for the performance of work. In The Human Use of Human Beings: Cybernetics and Society, Wiener writes that:
The development of these computing machines has been very rapid since the war. For a large range of computational work, they have shown themselves much faster and more accurate than the human computer. Their speed has long since reached such a level that any intermediate human intervention in their work is out of the question. Thus they offer the same need to replace human capacities by machine capacities as those which we found in the anti-aircraft computer. (151)
Wiener does not draw a distinction between the “virtual” machine performing computations and the material effects of computer labour in the real world. Computer scientists, it would appear, side with Turing, math, software, virtuality, and disembodied computation; engineers, like Wiener, side with work, hardware, materiality, and robots. The robot-computer distinction is a cultural one as well as a historical one. These distinctions, then, do not arise empirically, but are a priori ones brought to the study of or work with technology by the people involved.
In terms of software in general and AI in particular, the dominant discourse is that of disembodied computation leading to “thought”, “reasoning”, and “understanding”. We take the arguments of AI researchers at face value that these anthropomorphized terms are accurate descriptions of what AI software does. There are the usual caveats that a computer does not “think”, “reason”, or “understand” in the same way as human beings, but nonetheless what they are doing can and must be considered in these anthropomorphic terms. The hard-and-fast distinction between robots/hardware and AI/software above is explicitly stated by Margaret Boden in her classic AI text Artificial Intelligence and Natural Man:
One thing, however, is certain: artificial intelligence is not the study of computers. Computers are metallic macchines of intrinsic interest to electronic engineers but not, as such, to many others. […] It would be more accurate to say that artificial intellifence is the study of computer programs. (3)
It must pain AI researchers to have to care about such things as FLOPs and Moore’s Law, which must appear as a “revenge of the flesh” to those who wish they could concern themselves purely with mathematics, statistics, and computation.
This brings us around, then, to the question of software. We could approach the question purely from a Turing-AI perspective and say that software is the “mind” of the machine, no matter how simplified (indeed, one of Boden’s recent works is titled “mind as machine”). Or we could understand software as the extension of Marx’s three-part conception of the machine to encompass a fourth part: the control of the machine itself. This would fit with Wiener’s more cybernetic perspective - and indeed, the word “cybernetics” comes from the Greek word for “steersman”. So software is never disembodied, but always “steers”, governs, or controls hardware - hardware which is the condition for the software’s operation. (There is probably an argument to be made that the software/hardware dualism simply reproduces Cartesian dualism in mechanical form; we are arguing here for a monist perspective). Software, then, is the automation of the labour of the worker who controls a machine.
As we know from the history of technology, before a task can be automated, it must be broken down into its simplest parts. The simplest parts of a decision-making governor is predicate logic, the logic on which all computation and software are built. The IF-THEN-ELSE branches and FOR loops of computer programming are the crudest representation of human decision making, and the simplest version of it necessary for controlling computers/robots. The list of steps into which a problem or task is decomposed is the algorithm; there is nothing mysterious or nefarious about algorithms (though they do, of course, encode human values, biases, and prejudices).
As the work we require of our machines becomes more sophisticated, so too do the control mechanisms. We find that the logical and object structures encoded in traditional programs are no longer fast enough, parallelizable enough, or efficient enough to do the “useful work” we ask of them, and so we develop new techniques (AI) which are really no different from the old techniques, except that they are faster, more parallelizable, and more efficient. In no sense do AI technologies “think”, “reason”, or “understand” - not even by metaphor or analogy. At best, they automate a small piece of work (perception, classifying, etc.) that had, until now, been the work of a human being. This places this process squarely within what Marx calls the subsumption of labour under capital.
So why call them AI? Why create a panic around something that is basically simply the next phase of the automation of human labour by capital? To understand that, we can return to Marx’s chapter on technology:
Machinery does not just act as a superior competitor to the worker, always on the point of making him superfluous. It is a power inimical to him, and capital proclaims this fact loudly and deliberately, as well as making use of it. It is the more powerful weapon for suppressing strikes, those periodic revolts of the working class against the autocracy of capital. (562)
Capital does not just replace human labour with the dead labour of machines, it “proclaims this fact loudly and deliberately”. There is a discursive requirement to make sure workers think their jobs are at risk due to technological advance (whether that be robotics or AI), in order to keep them scared, docile, and subservient. The same discursive requirement applies to race, as well, with anti-immigrant feeling spurred up in part by fears of “immigrants coming to take your jobs”. However, in the case of technology - as opposed to immigration - just because capital whips up such fear for its own purposes does not make it false. It is true that technological advance will necessitate job loss, more precarity, proletarianization and immiseration. In the case of immigrants, it suits the capitalist’s purposes to lie; in the case of technology, it suits their purpose to tell the truth - but the purpose remains the same.
Boden, Margaret. Artificial Intelligence and Natural Man (New York: Basic Books, 1977).
Dyer-Witheford, Nick, Atle Mikkola Kjøsen and James Steinhoff. Inhuman Power: Artificial Intelligence and the Future of Capitalism (London: Pluto Press, 2019).
Marx, Karl. Capital, Volume 1 (London: Penguin Books, 1976).
Wiener, Norbert. The Human Use of Human Beings: Cybernetics and Society (Boston: Da Capo,  1954).