In Nick Land’s essay Meltdown, the third sentence reads:
“As markets learn to manufacture intelligence, politics modernizes, upgrades paranoia, and tries to get a grip.”
This is a central theme in Land’s work: markets = intelligence. The locus classicus for this idea is Friedrich Hayek’s 1945 essay, The Use of Knowledge in Society, which argues that markets function as decentralized information processors, aggregating the dispersed knowledge of market participants. A market is an abstract aggregator of partial, local information, which means markets are literally intelligent more intelligent than we are for technically specifiable reasons. Every transaction is an analysis of local conditions—desires, needs, and perceived worth—compared against myriad other potential transactions. The price, in whatever currency, acts as a universal denominator, allowing for global comparability.
Ludwig von Mises further developed this concept from a different angle in his 1920 essay, Economic Calculation in the Socialist Commonwealth. Rational economic calculation is impossible without market prices. This is often referred to as the “calculation argument,” where Mises endeavors to prove the infeasibility of computing socialist economic planning policies, a line of thought Hayek builds upon. Without market prices you have nothing to even compute. Even if you had a hypothetical communist computer designed for centralized calculation, and it worked, it would immediately be outpaced because individuals would go trade on the information it outputs. Markets are living in time at all times, constantly updating, especially in our era of digitalized global markets.
The historical emergence of stock markets, such as the Amsterdam Stock Exchange with the Dutch East India Company (VOC) around 1602 illustrates the concept. It’s one of the earliest examples of equity shares of a company trading on an open public market. VOC stock prices fluctuated daily based on rumors, news from distant trading posts like Java, reports on Spanish fleet movements, or diplomatic efforts. The share price itself became a form of news. Stockbrokers would employ couriers in races to get information faster, and some even kept telescopes on the cape to spot returning ships first—this was “alpha.” The stock price itself was first interpreted as news. This early market activity demonstrated that splitting a company into tradable shares wasn’t just a financial operation but a profound and dramatic new type of social intelligence generation.
As markets evolve and “manufacture intelligence,” effectively telling us what to do (from daily purchases to career choices), politics attempts to adapt. This often involves reacting to the challenges posed by these decentralized intelligences, which can be perceived as threatening and destabilizing to established powers because they represent information markets outside of their control. James C. Scott’s Seeing Like a State examines how modern governments try to impose grids of intelligibility on their populations and resources, creating standardized systems (like forestry programs or Soviet collectivization). This political modernism can be seen as reactive, an attempt to keep up with the runaway train of markets and intelligence, always threatening uncontrollable chaos.
Richard Hofstadter’s 1964 essay, The Paranoid Style in American Politics, explores how political movements can become consumed by conspiratorial thinking in response to perceived threats. Land suggests that this kind of political modernism is downstream of technological and market-driven synthetic intelligence. As this intelligence escapes its box, politics becomes a paranoiac attempt to create control, to retain power, to manage it, always a few steps behind, structurally doomed to never quite get up to speed but always trying to “get a grip.” This effort to control an increasingly dynamic system often leads to doomed and probably evil, desperate measures.
The dynamic is evident in contemporary debates around Artificial Intelligence (AI). As AI systems, like OpenAI’s new o3 model, become more sophisticated and capable of surprisingly complete, objective, and accurate computations of increasingly complicated sets of data, there is a growing call for regulatory oversight. Figures like Eliezer Yudkowsky advocate for international organizations to lock down AI models, while others like Geoffrey Hinton express concerns about job displacement, suggesting global socialism as a response. However, such paranoid measures centralize power and increase systemic risk. Peter Thiel has warned against forces presenting themselves as representatives of safety gaining too much global power. This echoes Land’s warning about the state’s attempt to domesticate emergent intelligences.
In his essay Machinic Desire, Land describes “Politically Organized Defensive Systems” (PODS), which are “modelled upon the polis, hierarchically delegated authority through public institutions, family, and self seeking metaphorical sustenance in the corpuscular fortifications of organisms and cells.” He writes:
“The global human security allergy to cyber-revolution consolidates itself in the new world order or consummate macropod… The macropod has one law: the outside must pass by way of the inside.”
This is the state’s tendency to absorb and control external innovations. The “macropod” represents the “human security system” which insists that any outside innovation or emergent intelligence, once it becomes significant enough, must bend the knee and be integrated or domesticated. This is seen in the AI safety discussion: When intelligence manufacturing reaches a certain level, the call to control it intensifies, potentially leading to a “one world government” if one believes it’s necessary to control escalating intelligence.
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Markets Learn to Manufacture Intelligence and Politics Modernizes