By Gordon Hull
“Factory work exhausts the nervous system to the uttermost; at the same time, it does away with the many-sided play of the muscles, and confiscates every atom of freedom, both in bodily and in intellectual activity” (Marx, Capital I [Penguin Ed.], 548).
A recent piece by Josh Dzieza in the Verge about the working conditions of those subject to discipline by AI in the workplace is wrenching. It tells the story of Amazon workers and call center employees and others whose work lives have become an exhausting monotony of ever-intensifying robot-like demands. The “AI boss” becomes ever more demanding, filling every moment at work with the requirement to be more productive and with absurd metrics for deciding when its demands are met. Amazon workers report that they are basically ground down by the unsustainability of the pace of productivity; they are either fired or forced to quit, often with injuries. Call center employees are subject to Orwellian monitoring by a machine that purports (often laughably inaccurately) to monitor and tweak their affect when speaking to customers. Folks working from home find it impossible to go to the bathroom, because they are forced to sit in front of their computer all the time, which takes frequent pictures of them and reports on their productivity, as measured by lines of code or keystrokes per unit time.
All of this optimized misery reminds us of something important: AI systems are being deployed under capitalism. A worker subject to an “AI Boss” is not some sort of new-fangled social form; they are fundamentally a worker subject to capitalist exploitation. What AI has done is enable capitalism to be more intensively exploitative. The stories in the article echo the stories Marx reports in Capital in his discussion of machinery, as does a lot of the logic. This suggests that two popular narratives about AI need to be displaced. First, it may be that AI will someday swoop in and take away everyone’s jobs. As Dzieza notes, this narrative deflects attention from the pressing reality of deteriorating workplace conditions under AI supervision. Second, Marx’s work on machines and technology is frequently read (as by the autonomists) through the Grundrisse “Fragment on Machines,” and in a way that emphasizes affective labor and cognitive capital. The reality of AI today serves as an important reminder that the treatment in Capital is still very important. Let me explain.
Marx proposes that there are three immediate effects of the introduction of machinery. First, there is an increased subsumption of society under capital as women and children are employed in jobs that formerly required more “muscular power” (517, Penguin ed.). Labor laws get in the way of some of this in the case of AI, but it is worth pointing out that there is a lot of work to be done on the feminization of labor around AI, as well as the workforce structures around things like call centers, particularly outside of the U.S.
Second, it prolongs the working day, because not only can machines work all the time, they depreciate over time, so using them less than 24/7 is a waste. Marx writes:
“The instrument of labour now becomes an industrial form of perpetual motion. It would go on producing forever, if it did not come up against certain natural limits in the shape of the weak bodies and the strong wills of its human assistants” (526)
Aside from noting that these AI-based management systems are basically designed to break down the strong wills of the people who work for them, it is worth pointing out that they produce a de facto extension of the working day in at least two ways. On the one hand, they leave workers utterly exhausted. Workers in the Dzieza article point to falling asleep in their cars after shifts, and not having energy to do more than sleep when they get home: the entire day becomes either labor or recovery from it. He quotes a Minnesota worker:
“The concept of a 40-hour work week was you work eight hours, you sleep eight hours, and you have eight hours for whatever you want to do,” he said. “But [what] if you come home from work and you just go straight to sleep and you sleep for 16 hours, or the day after your work week, the whole day you feel hungover, you can’t focus on things, you just feel like shit, you lose time outside of work because of the aftereffects of work and the stressful, strenuous conditions?”
On the other hand, AI systems perfect just-in-time scheduling, where workers shifts are no longer predictable or consistent. Instead, they have to be ready at a moment’s notice to arrive at work or end a shift early, whenever the scheduling apparatus decides that more or fewer workers will be needed. This problem has been brewing for years and the AI bosses only intensify it, but the effect is that a worker can never leave work, because they are always on call. This is devastating for families in particular. As Marx puts the point in the analogous case of factory machines, “the most powerful instrument for reducing labor-time suffers a dialectical inversion and becomes the most unfailing means for turning the whole lifetime of the worker and his family into labor-time at capital’s disposal for its own valorization” (532).
There is an even more insidious extension of the working day at play in the case of AI systems. Under factory production, the day is divided into times of work and non-work. The surveillance capacity of these systems, when combined with their machine learning algorithms, allow them to fully disaggregate the working day into ever smaller moments, identifying moments where employees are “not working” and then forcing them either to work during those moments, or lose pay. Consider the experience of a worker named Rony, who worked at home under the supervision of a system named WorkSmart:
“WorkSmart did, in fact, transform Rony’s day into solid blocks of productivity because if it ever determined he wasn’t working hard enough, he didn’t get paid. The software tracked his keystrokes, mouse clicks, and the applications he was running, all to rate his productivity. He was also required to give the program access to his webcam. Every 10 minutes, the program would take three photos at random to ensure he was at his desk. If Rony wasn’t there when WorkSmart took a photo, or if it determined his work fell below a certain threshold of productivity, he wouldn’t get paid for that 10-minute interval …. Rony soon realized that though he was working from home, his old office job had offered more freedom. There, he could step out for lunch or take a break between tasks. With Crossover, even using the bathroom in his own home required speed and strategy: he started watching for the green light of his webcam to blink before dashing down the hall to the bathroom, hoping he could finish in time before WorkSmart snapped another picture. The metrics he was held to were extraordinarily demanding: about 35,000 lines of code per week. He eventually figured out he was expected to make somewhere around 150 keystrokes every 10 minutes, so if he paused to think and stopped typing, a 10-minute chunk of his time card would be marked “idle.” Each week, if he didn’t work 40 hours the program deemed productive, he could be fired, so he estimated he worked an extra 10 hours a week without pay to make up the time that the software invalidated.”
This extension of the workday is then part of why workers can do nothing but sleep afterwards.
The final immediate effect Marx identifies is the intensification of labor; it is this part which is most evident in the Dzieza article. The process Marx outlines is fully dialectical: the extension of the working day at some point reaches a limit in that there are only so many hours a person can work during the day, either because of natural limits or because workers succeed in getting legislation passed to limit the length of the day. At that point, the process becomes one of intensive exploitation, trying to make each second more productive (534). In tandem with eliminating time spent “not working,” the system seeks to make each second generate more surplus value. Dzieza recounts numerous examples of how Amazon relentlessly pushes workers to handle more and more packages, often at direct cost to their health. Again, this is a tendency inherent to capitalism and not unique to AI. Marx spends several pages documenting examples of how both the speed of machines is increased and individual workers are given more machines to operate. Dzieza recalls the history of Taylorism and Fordism; to this record one should add the experiences of workers at meat packing facilities who are forced to work at extremely dangerous speeds by the machinery that moves animals by them.
Marx suggests this process works in tandem with the shortening of the working day; as workers succeed in shortening their workday, capital responds by intensifying the hours left. As Marx puts it:
“Capital’s tendency, as soon as a prolongation of the hours of labor is one for all forbidden, is to compensate for this by systematically raising the intensity of labor, and converting every improvement in machinery into a more perfect means for soaking up labor-power. There cannot be the slightest doubt that this process must soon lead once again to a critical point at which a further reduction in the hours of labor will be inevitable” (542)
The emerging experience with AI shows both the historical specificity of Marx’s argument and the ongoing evidence of the relevance of dialectical thinking; the discovery of so much time spent “not working” while on the clock opens a fresh period of colonization of the work day and the concrete negation of the abstract opposition between the length of the work day and its intensity. These processes can be combined into a singular axiomatic that simultaneously increases both the intensive and extensive quantity of work. The only thing that remains constant is that the worker bears the cost of the process while not being paid for it.
I’ll say more about Marx’s synthetic comments about factories, and what this implies for Marx on technology, next time.
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