Embrace refusal, not acceleration: Even if AI has a role in an emancipatory future, only our moment of refusal can break open the future which has been foreclosed by the commodifying monoculture of AI-capitalism.

Others writing in the Marxist tradition see autonomism or accelerationism as viable responses to AI-capitalism. Why, in your view, are these insufficient?

Left accelerationism sees in the development of AI a promising tool for socialism, freeing people from wage labor and enhancing possibilities for economic planning. And certain lines of autonomist Marxism manifest a similar enthusiasm, based on the belief that AI development will rest on and empower the distributed techno-scientific knowledge of a still-human — even if cyborg — general intellect. These positions retain the high-modernist confidence in the ultimately progressive direction of capitalist technological development that is part of Marxism. I don’t dismiss the possibility of emancipatory uses of AI. But what is being accelerated right now, in the current trajectory of AI, is capital’s command over, and capacity to dispense with, the worker, and what is expanded is not the autonomy of labor from capital, but capital’s autonomization from the human.

These are not questions of an abstract futurism. Leaving aside the question of a long-term crisis of work, we today see the dominant applications of AI intensifying processes in play since capital began its cybernetic offensive against organized labor decades ago. These include the increasing precarity of work in a gig economy, implicated in the very making of AI itself, as well as in the deployment of machine learning by companies such as Uber or Amazon; the polarization of the workforce between an elite techno-managerial strata, charged with job automation, and a racialized and feminized service sector, whose labor is still largely too cheap to automate; the offloading onto individuals of costs for the training and upgrading of skills through which they will supposedly sustain the impacts of the fourth industrial revolution; intensifications of workplace monitoring; the linkage of this surveillance with algorithmically precision-targeted and bot-enabled vital propaganda campaigns from well-funded reactionary interests; and the incorporation of AI into a Big Data security apparatus for the disciplining of the poor, from welfare screening to preemptive policing. This mix of precarity, polarization, panopticism, propaganda, and policing constitutes — to use a phrase from David Noble, the late, great radical historian of digital technology — the “present tense” politics of capitalism’s AI project.

Do you see a path forward?

The political answer is not acceleration but refusal. And this is indeed what is has begun to manifest, in a variety of social rebellions. This includes the strikes of gig economy labor, the protests of Silicon Valley tech workers, anti-surveillance movements, urban protests against the smart city, defections from social media sites, algorithmic-bias busting, and “techlash” against the oligopolistic concentration of digital powers. This is the new composition of class against AI-capital. Such refusals will always be tarred with the label of Luddism, but in our view, this designation is simply irrelevant. The issue is now not the prevention of a nascent techno-capitalism, but a swerve away from its potentially disastrous terminus. This moment of refusal is necessary to break open the foreclosure of the future by AI-capital, to win the space for real collective governance and direction of AI. Inhuman Power was published only last year, but since then we have seen important developments confirming its perspective: renewed warnings by the influential AI scientist Stuart Russell about the existential threats posed by AI; the proposal by legal scholar Frank Pasquale that “accountability” of new digital systems include outright banning or restricted licensing; and the stirring Manifest-No of feminist data scientists calling for withdrawal from disciplinary, discriminatory, and invasive machine learning development. These calls come from positions different from ours, but they do share a recognition that the new developments in machine learning demand a response to ensure a future where, even as the nature of the human may undergo profound changes, these transformations are not dictated by the commodifying monoculture of AI-capitalism. If we want a picture of what such a response entails, we need search no further than the images coming from the streets of Hong Kong and Santiago, where protestors against penury and inequality use lasers to disable the facial recognition technologies and drones deployed by police. This is what the struggle against inhuman power looks like today.