‘A dangerous proposition’: How AI is warping the social fabric and the ways we collectively imagine the future
lots of discussion around artificial intelligence (AI) focuses on grand ideas like the rise of the imaginary artificial general intelligence (AGI) and superintendence. Speculation is swirling around the possibility that technology will weaken the job market, or even eliminate it. Death or evolution of human creativity. We have not focused as much attention on the many subtle but highly consequential ways in which AI is reshaping the social fabric of our society, and how we collectively imagine the future.
This is the argument of sociologists and AI researchers mona sloanassistant professor of data science and media studies at the University of Virginia, puts at the center of her new book, “Prediction: How AI is restructuring social life” (University of California Press, 2026). Whether we consider email filtering, prediction markets, or social media platforms, AI systems are embedded at the core of how we interact with the digital world. In fact, AI is so ubiquitously integrated into everyday interfaces that it has given rise to a new type of “predictive reasoning” that makes assumptions about who we are and how we might behave.
In this piece, Sloane compares the AI technology we use today to the oracles of ancient Greece, presenting it as an omnipotent presence that has moved to organize society through the prism of predictive models. This in turn affects the way we learn, live, love and even imagine the future.
We live in a world of oracles. These predictions give us constant predictions that shape our social lives – how we socialize, love, work, get access to resources. As in ancient Greece, prophecies play a major role in our society. We consider our oracles to be so powerful that their predictive power rules over the fate of entire economies and even geopolitical constellations. Where the oracle is, there is the center of the world.
But unlike ancient Greece, our prophets are not high priests giving divine prophecies. They are artificial intelligence (AI) systems embedded in the infrastructure of everyday life. Today, it is almost impossible to escape the grip of AI predictions. I voluntarily and involuntarily use AI on an ongoing basis: by using email providers that build predictive AI properties for spam filters, by conducting online banking and enrolling in AI-automated fraud detection, or by using generative AI to support administrative tasks. It has become part of how I experience the world.
It can be a relief when it helps me do things I’m afraid of or am bad at, like creating a spreadsheet template I desperately need, helping streamline language drafted by different writers for a report, or producing a specific image for a presentation. Often, I must hold the AI carefully, examine its output, and correct it. And sometimes, with deep frustration, I give up and start completing my work manually.
The ubiquity of AI prediction may make it easier to think of these systems as inevitable, semi-natural phenomena to which we are subject rather than part. But they are quantitative concepts that arise from social agreements about how we should capture and interpret the world around us.
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“Quantitative concepts are not given by nature: they arise from our practice of applying numbers to natural phenomena,” logician and professor of philosophy of science Rudolf Carnap wrote in 1966. He said that numbers can be useful because they act as a kind of language, allowing information to travel more easily across contexts. They also make mathematical predictions possible.
For him, it was first and foremost useful for the engineering of modern life: a quantitative language allows the expression of quantitative laws, which in turn, especially in the field of physics, facilitates the routine generation of mathematical predictions. Being able to predict how energy, compounds and materials will behave in certain configurations is why humans were able to create airplanes, cars, and telephones. For Carnap, predictions like this were simply helpful.
AI’s predictive capabilities are changing the way we think about the future.
(Image credit: Yana Iskayeva via Getty Images)
Today, almost 60 years later, this practical approach to mathematical prediction has been turned upside down by AI. Prediction is no longer just a useful tool in physics or engineering. Promises of AI’s superhuman power have turned prediction into an argument for the structure of social life. This is a dangerous proposition. This implies that AI is always necessary or inevitable and distracts from the social forces shaping ideas around this technology in the first place.
AI systems are not natural phenomena that happen to us. They are the collective expression of society. Thus, they are not merely a propaganda or hoax fabricated and implemented by the global technological elite. They signal broader changes in the way we envision and enact our society. Many critical discussions of AI characterize this phenomenon primarily as one of increased surveillance and capitalist extraction. But this is a short-sighted diagnosis. The most powerful impact of AI is the subtle but widespread recalibration toward predictability as a guiding principle for organizing society. In this book, I call this phenomenon the prediction paradigm.
AI is something we do as part of how we go about our lives and participate in society – it is social infrastructure, influencing how we relate to each other and how we act in public and in private. Like all infrastructures, AI allows resources and ideas to flow in some directions, but not others. AI uses data from our collective past to predict our individual future. And because AI works in the future, it reinforces a linear time arrangement that hardens our societal commitment to causality: the past always predicts the future. The problem of AI is not the rise of intelligent machines, but the extraordinary social importance attributed to this linearity, which glamorizes the future and leaves little room for discussion about what (other) futures might be possible or what we might want.
Prediction: How AI is Restructuring Social Life: 1 (Co-opting AI)
In predictedMona Sloane provides a practical framework for understanding these changes around prediction, classification, and linearity, proposing that we think about AI as a social system that we co-produce. Based on over a decade of empirical research and real-world examples, this book invites us to see AI for what it is: deeply social, deeply political, and open to change.
