What happens when a society begins to see itself as a machine? Adam Curtis’s documentary trilogy All Watched Over by Machines of Loving Grace explores this question through the rise of cybernetic thinking in politics, ecology, and genetics, suggesting that mechanical metaphors have constrained human possibility even as they’ve promised liberation. While Curtis effectively demonstrates how mechanical thinking has shaped modern institutions, his rigid human/machine distinction obscures more nuanced ways of understanding our relationship with technology.
These questions feel urgent today as artificial intelligence reshapes work, relationships, and governance. Silicon Valley executives promote “accelerationist” visions of technological progress while critics warn against reducing humans to data points. Curtis’s documentary, though made in 2011, offers crucial insights for navigating these contemporary debates.
Yet Curtis’s critique, while illuminating, relies on a problematic assumption: that humans and machines represent fundamentally different categories. This binary thinking may be just as limiting as the mechanical metaphors Curtis critiques.
The Randian Machine
In the first part of the documentary, Curtis investigates the way that Ayn Rand’s idea of objectivism has reframed the way we see ourselves in the world. Through what we might today call “theory-fiction,” Ayn Rand articulated a utopian vision of a world without altruism. She believed herself to be a strict rationalist, and she was surrounded by a group of followers who thought themselves the same. In the end, they thought, all that we have is ourselves: there is no God, there is no social reality, there is nothing except the self.
One member of Rand’s “collective” was Alan Greenspan, who was appointed chairman of the United States Federal Reserve in 1987. Greenspan’s chairmanship coincided with the surge of information technology as a way to manage markets, and he believed that new systems would lead to an enormous growth of productivity.
He convinced the Clinton administration to abandon the traditional regulatory state but, as we know, Clinton’s deregulation shifted significant power to financial markets. This contributed to economic instability in Asia and expanded financial capital’s global reach.
At the same time, Silicon Valley was becoming a powerhouse in its own right, and numerous up-and-coming tech moguls took Rand’s ideas seriously. In the process, what Richard Barbrook and Andy Cameron call “the Californian Ideology” came into existence, combining Randian individualism (in all its political, economic, social, and cultural forms) with a belief that technology was capable of transforming global society into a veritable utopia.
American–and more broadly, Western–elites came to see the economy as a mechanical system that they could fine-tune, but would largely grow on its own.
It appears that the trend that Curtis has identified here has not abated, and in fact might be accelerating. We continue to see humans drawing upon technological models for our own society. Silicon Valley executives have embraced their own form of accelerationism, which has diverged quite significantly from that developed by the CCRU and its descendants.
Ecosystems as Feedback Loops
Curtis’s second episode reveals how this mechanical thinking extended beyond economics into our understanding of natural and social systems. While the episode is ostensibly about ecological systems, Curtis gives just as much weight to social systems.
Curtis begins with the story of Arthur Tansley, the English botanist who developed the concept of the “ecosystem.” In the early twentieth century, he was troubled by a dream that he shot his wife. Trying to make sense of it, he moved to Vienna for a year to be analyzed by Sigmund Freud, who taught him that the brain is an electrical system. The idea of the brain as a network stayed with Tansley, who then began to think about the natural environment in the same way. The Odum brothers, both of whom were ecologists, synthesized Tansley’s ecosystem with Norbert Wiener’s cybernetics and argued that feedback cycles regulate the natural environment towards equilibrium. Eugene Odum’s Fundamentals of Ecology popularized the idea, and the idea that nature was always in equilibrium became a principal assumption for anyone thinking about the natural world.
In the late 1960s, Wiener’s ideas about cybernetic systems really took off. Hippie communes relied on principles of cybernetics by framing their experiments as self-regulating systems where each individual was a “node.” When there was disequilibrium, the system would modify itself so it fell back into a stable level. Take the famous Synanon community in California. Founded on cybernetic principles of self-regulation, it began as a drug rehabilitation program but gradually became authoritarian as human dynamics overwhelmed systematic design.
Jay Forrester and the Club of Rome relied on cybernetics when they wrote The Limits to Growth, an alarming text that showed global human society would collapse in the 21st century. Forrester urged states to engage in a policy of proto-“degrowth,” but his suggestions were ignored by everyone–from states to environmental protesters.
Ecological researchers in the 1970s built models of ecosystems based on exacting data because they wanted to understand how the environment’s feedback cycles work. However, ecological research in the 1970s revealed significant problems with equilibrium models. Many ecosystems showed little evidence of self-regulation, calling into question whether closed, cybernetic models accurately described natural systems. Nevertheless, the idea that the environment regulates itself is still widely held. This equilibrium thinking persists in contemporary climate discourse, where Earth is often portrayed as a self-regulating system that will ultimately recover from human disruption–an assumption worth questioning.
The Gene’s Eye View
The final episode pushes this mechanical thinking to its logical extreme, asking whether humans themselves are simply biological machines. At the core of the story is Bill Hamilton’s genetic research. All of his research was consumed with one question: Why do humans and other creatures give their lives for others? Unlike Ayn Rand, who seemed to see altruism as a human pathology, he recognized that it was baked into our very being. Hamilton’s innovation was his ability to see the world from the perspective of the gene. From this vantage point, humans are merely exoskeletons designed to protect the gene as it propagates itself.
Chemist George Price discovered Hamilton’s research papers, which had been largely ignored by the scientific establishment, and he found that Hamilton’s equations for how genes operate were almost identical to those used by machines. In effect, he showed that self-replicating machines long preceded John von Neumann’s research: Everything alive–including humans–was a self-replicating machine. Price went on to show that the gene’s need to replicate could explain murder and rape, genocide and suicide. Price’s framework suggested that even destructive human behaviors might serve genetic imperatives.
Richard Dawkins went on to popularize Price’s research, convincing millions of us that our genetics are intrinsically selfish, and this egotism could express itself from a range of behaviors: from cruelty to total altruism. Price’s equations predicted that parents should favor children who share more of their genes. Yet adoptive families demonstrate profound love that serves no genetic purpose: a complexity his mechanical model couldn’t capture.
Throughout the episode, Curtis brings our attention to the Rwandan genocide and the collapse of the Congo, which–under Price’s understanding–could be explained through this selfish gene. In addition to colonial racism, Curtis argues that Western consumption patterns, rooted in the same mechanical thinking that devalues human agency, fueled demand for conflict minerals. He also examines the research of Dian Fossey, who had spent time investigating gorillas and learning about how similar they are to humans.
When Mechanical Theories Meet Human Complexity
Each case study reveals the same pattern: mechanical theories collide with human complexity in ways that both support and complicate Curtis’s argument. While these examples seem to validate Curtis’s distinction between humans and machines, they actually point toward a more complex relationship between systematic thinking and human agency.
Ayn Rand, for example, believed herself utterly rationalist all the time. Yet, she gave into a very human desire for love and affection. She began an affair with Nathaniel Branden, who was married to Barbara–both of them members of Rand’s collective. She framed the affair as something rational, as though it would be impossible for any other course of action to make sense.
While many communes struggled with the gap between cybernetic theory and human dynamics, their experiments offered valuable lessons about the complexities of self-organizing communities–lessons that inform contemporary discussions about decentralized systems. While they were built on principles of free association, individualism, equality, and altruism, the feedback loops put in place to maintain the system fell apart. Cybernetics gave way and the communes fell into classical political dynamics: bullying, hazing, hoarding power, and so on.
George Price came to believe that his discoveries were given to him by God himself–an idea that was completely at odds with his earlier views. Moreover, he devoted himself to helping the homeless, and he killed himself in a way that ensured that his genetics would not benefit.
Beyond the Human/Machine Binary
Curtis’s analysis reveals important limitations in mechanical thinking, yet his proposed human/machine binary overlooks the very fact that it is a binary at all. There is no clear distinction between these two categories. Rather than finding this troubling, we might see it as an invitation to think more carefully about what kinds of machines we want to be, and what distinctly human capacities we want to cultivate alongside our mechanical aspects.
Darwin’s evolutionary theory challenged traditional hierarchical views of life and showed that the rest of Earth’s life are our kin. At this point, nobody but the most trenchant fundamentalist would deny that. But, where does life end and non-life begin?
This binary thinking becomes problematic when we examine the boundaries Curtis assumes are clear-cut. Consider viruses: they lack their own DNA, instead carrying foreign genetic material and hijacking host cells for reproduction. Are viruses alive or are they biological machines? The question reveals how artificial our categories can be. Similarly, when we examine human behavior–our capacity for both systematic reasoning and emotional contradiction–we find complex systems that defy simple classification. We are neither purely rational actors nor chaotic beings immune to patterns. We are something more interesting: systems capable of reflecting on our own systematic nature.
As AI becomes more prevalent, Curtis’s documentary remains relevant not as a warning against all technological thinking, but as a reminder that our metaphors shape our possibilities. Understanding ourselves as complex systems–neither purely mechanical nor exempt from systematic analysis–might help us navigate technological change more thoughtfully.