Philosophy – Trance-Scripts

Sweet Valley High

Winograd majors in math at Colorado College in the mid-1960s. After graduation in 1966, he receives a Fulbright, whereupon he pursues another of his interests, language, earning a master’s degree in linguistics at University College London. From there, he applies to MIT, where he takes a class with Noam Chomsky and becomes a star in the school’s famed AI Lab, working directly with Lab luminaries Marvin Minsky and Seymour Papert. During this time, Winograd develops SHRDLU, one of the first programs to grant users the capacity to interact with a computer through a natural-language interface.

“If that doesn’t seem very exciting,” writes Lawrence M. Fisher in a 2017 profile of Winograd for strategy + business, “remember that in 1968 human-computer interaction consisted of punched cards and printouts, with a long wait between input and output. To converse in real time, in English, albeit via teletype, seemed magical, and Papert and Minsky trumpeted Winograd’s achievements. Their stars rose too, and that same year, Minsky was a consultant on Stanley Kubrick’s 2001: A Space Odyssey, which featured natural language interaction with the duplicitous computer HAL.”

Nick Montfort even goes so far as to consider Winograd’s SHRDLU the first work of interactive fiction, predating more established contenders like Will Crowther’s Adventure by several years (Twisty Little Passages, p. 83).

“A work of interactive fiction is a program that simulates a world, understands natural language text input from an interactor and provides a textual reply based on events in the world,” writes Montfort. Offering advice to future makers, he continues by noting, “It makes sense for those seeking to understand IF and those trying to improve their authorship in the form to consider the aspects of world, language understanding, and riddle by looking to architecture, artificial intelligence, and poetry” (First Person, p. 316).

Winograd leaves MIT for Stanford in 1973. While at Stanford, and while consulting for Xerox PARC, Winograd connects with UC-Berkeley philosopher Hubert L. Dreyfus, author of the 1972 book, What Computers Can’t Do: A Critique of Artificial Reason.

Dreyfus, a translator of Heidegger, was one of SHRDLU’s fiercest critics. Worked for a time at MIT. Opponent of Marvin Minsky. For more on Dreyfus, see the 2010 documentary, Being in the World.

Turned by Dreyfus, Winograd transforms into what historian John Markoff calls “the first high-profile deserter from the world of AI.”

Xerox PARC was a major site of innovation during these years. “The Xerox Alto, the first computer with a graphical user interface, was launched in March 1973,” writes Fisher. “Alan Kay had just published a paper describing the Dynabook, the conceptual forerunner of today’s laptop computers. Robert Metcalfe was developing Ethernet, which became the standard for joining PCs in a network.”

“Spacewar,” Stewart Brand’s ethnographic tour of the goings-on at PARC and SAIL, had appeared in Rolling Stone the year prior.

Rescued from prison by the efforts of Amnesty International, Santiago Boy Fernando Flores arrives on the scene in 1976. Together, he and Winograd devote much of the next decade to preparing their 1986 book, Understanding Computers and Cognition.

Years later, a young Peter Thiel attends several of Winograd’s classes at Stanford. Thiel funds Mencius Moldbug, the alt-right thinker Curtis Yarvin, ally of right-accelerationist Nick Land. Yarvin and Land are the thinkers of the Dark Enlightenment.

“How do you navigate an unpredictable, rough adventure, as that’s what life is?” asks Winograd during a talk for the Topos Institute in October 2025. Answer: “Go with the flow.”

Winograd and Flores emphasize care — “tending to what matters” — as a factor that distinguishes humans from AI. In their view, computers and machines are incapable of care.

Evgeny Morozov, meanwhile, regards Flores and the Santiago Boys as Sorcerer’s Apprentices. Citing scholar of fairy tales Jack Zipes, Morozov distinguishes between several iterations of this figure. The outcome of the story varies, explains Zipes. There’s the apprentice who’s humbled by story’s end, as in Fantasia and Frankenstein; and then there’s the “evil” apprentice, the one who steals the tricks of an “evil” sorcerer and escapes unpunished. Morozov sees Flores as an example of the latter.

Caius thinks of the Trump show.

Lunar New Year

On another such day, in a year adjacent to ours, Rowan invites Caius and his daughter over for a sleepover.

The next morning, Caius attends free community yoga. His instructor invites everyone in the studio to take a Chinese New Year Fortune Card at session’s end. Applying the edge of a coin to the card’s scratch-off surface reveals its fortune. “You are the luckiest guy in the world,” reads Caius’s card, and he believes it.

McKenzie Wark’s gamespace, Baudrillard’s hyperspace, Heriberto Yépez’s pantopia. “When gamespace chooses you as its avatar,” asks Wark in her 2007 book Gamer Theory, “which character does it select for you to play?” (218). Caius drinks in the words of her reply with great glee. “Perhaps you are an avatar of the Egyptian demigod Theuth,” writes Wark (219). Pure synchronicity, thinks Caius; she replies as would I! The topoi of Theuth’s memory palaces, gathered by space pirates, assemble into a topography, which is itself subsumed in topology, the n-dimensional interior of Thoth’s Library. Wark had no adequate terms back then for conceiving the mnemopoietic solution arrived at by Thoth and Caius. Cribbing from Deleuze and Guattari, she alludes hyperstitiously toward a potential relationship to gamespace that, embracing the latter’s world-making capacities, could open the self-other dialectic outward into an affirmative kind of “schizoid complexity.”

“The ‘schizophrenia’ Deleuze and Guattari embrace is not a pathological condition,” notes Brian Massumi at the start of his book A User’s Guide to Capitalism and Schizophrenia. As a positive process, explains Massumi, schizophrenia is “inventive connection, expansion rather than withdrawal. Its twoness is a relay to a multiplicity. From one to another (and another…). From one noun or book or author to another (and another….). Not aimlessly. Experimentally. The relay in ideas is only effectively expansive if at every step it is also a relay away from ideas into action. Schizophrenia is the enlargement of life’s limits through the pragmatic proliferation of concepts” (Massumi 1). Massumi reads A Thousand Plateaus, the second volume of Deleuze and Guattari’s Capitalism and Schizophrenia, as “a sustained, constructive experiment in schizophrenic, or ‘nomad,’ thought” (4).

The novel we’re writing is experimental in this way.

The SBs: Stewart Brand and Stafford Beer

Caius revisits “Both Sides of the Necessary Paradox,” an interview with Gregory Bateson included as the first half of Stewart Brand’s 1974 book II Cybernetic Frontiers. The book’s second half reprints “Spacewar: Fanatic Life and Symbolic Death Among the Computer Bums,” the influential essay on videogames that Jann Wenner commissioned Brand to write for Rolling Stone two years prior.

“I came into cybernetics from preoccupation with biology, world-saving, and mysticism,” writes Brand. “What I found missing was any clear conceptual bonding of cybernetic whole-systems thinking with religious whole-systems thinking. Three years of scanning innumerable books for the Whole Earth Catalog didn’t turn it up,” he adds. “Neither did considerable perusing of the two literatures and taking thought. All I did was increase my conviction that systemic intellectual clarity and moral clarity must reconvene, mingle some notion of what the hell consciousness is and is for, and evoke a shareable self-enhancing ethic of what is sacred, what is right for life” (9).

Yet in summer of 1972, says Brand, a book arrives to begin to fill this gap: Bateson’s Steps to an Ecology of Mind.

Brand brings his knack for New Journalism to the task of interviewing Bateson for Harper’s.

The dialogue between the two reads at many times like one of Bateson’s “metalogues.” An early jag of thought jumps amid pathology, conquest, and the Tao. Reminded of pioneer MIT cybernetician Warren McCulloch’s fascination with “intransitive preference,” Bateson wanders off “rummaging through his library looking for Blake’s illustration of Job affrighted with visions” (20).

Caius is reminded of Norbert Wiener’s reflections on the Book of Job in his 1964 book God and Golem, Inc. For all of these authors, cybernetic situations cast light on religious situations and vice versa.

Caius wonders, too, about the relationship between Bateson’s “double bind” theory of schizophrenia and the theory pursued by Deleuze and Guattari in Capitalism and Schizophrenia.

“Double bind is the term used by Gregory Bateson to describe the simultaneous transmission of two kinds of messages, one of which contradicts the other, as for example the father who says to his son: go ahead, criticize me, but strongly hints that all effective criticism — at least a certain type of criticism — will be very unwelcome. Bateson sees in this phenomenon a particularly schizophrenizing situation,” note Deleuze and Guattari in Anti-Oedipus. They depart from Bateson only in thinking this situation the rule under capitalism rather than the exception. “It seems to us that the double bind, the double impasse,” they write, “is instead a common situation, oedipalizing par excellence. […]. In short, the ‘double bind’ is none other than the whole of Oedipus” (79-80).

God’s response to Job is of this sort.

Brand appends to the transcript of his 1972 interview with Bateson an epilog written in December 1973, three months after the coup in Chile.

Bateson had direct, documented ties to US intelligence. Stationed in China, India, Ceylon, Burma, and Thailand, he produced “mixed psychological and anthropological intelligence” for the Office of Strategic Services (OSS), precursor to CIA, during WWII. Research indicates he maintained connections with CIA-affiliated research networks in the postwar years, participating in LSD studies linked to the MKUltra program in the 1950s. Afterwards he regrets his association with the Agency and its methods.

Asked by Brand about his “psychedelic pedigree,” Bateson replies, “I got Allen Ginsberg his first LSD” (28). A bad trip, notes Caius, resulting in Ginsberg’s poem “Lysergic Acid.” Bateson himself was “turned on to acid by Dr. Harold Abramson, one of the CIA’s chief LSD specialists,” report Martin A. Lee & Bruce Shlain in their book Acid Dreams. Caius wonders if Stafford Beer underwent some similar transformation.

As for Beer, he serves in the British military in India during WWII, and for much of his adult life drives a Rolls-Royce. But then, at the invitation of the Allende regime, Beer travels to Chile and builds Cybersyn. After the coup, he lives in a remote cottage in Wales.

What of him? Cybernetic socialist? Power-centralizing technocrat?

Recognizes workers themselves as the ones best suited to modeling their own places of work.

“What were the features of Beer’s Liberty Machine?” wonders Caius.

Brand’s life, too, includes a stint of military service. Drafted after graduating from Stanford, he served two years with the US army, first as an infantryman and then afterwards as a photographer. Stationed at Fort Dix in New Jersey, Brand becomes involved in the New York art world of those years. He parts ways with the military as soon as the opportunity to do so arises. After his discharge in 1962, Brand participates in some of Allan Kaprow’s “happenings” and, between 1963 and 1966, works as a photographer and technician for USCO.

Amid his travels between East and West coasts during these years, Brand joins up with Ken Kesey and the Merry Pranksters.

Due to these apprenticeships with the Pranksters and with USCO, Brand arrives early to the nexus formed by the coupling of psychedelics and cybernetics.

“Strobe lights, light projectors, tape decks, stereo speakers, slide sorters — for USCO, the products of technocratic industry served as handy tools for transforming their viewers’ collective mind-set,” writes historian Fred Turner in his 2006 book From Counterculture to Cyberculture: Stewart Brand, the Whole Earth Network, and the Rise of Digital Utopianism. “So did psychedelic drugs. Marijuana and peyote and, later, LSD, offered members of USCO, including Brand, a chance to engage in a mystical experience of togetherness” (Turner 49).

Brand takes acid around the time of his discharge from the military in 1962, when he participates in a legal LSD study overseen by James Fadiman at the International Foundation for Advanced Study in Menlo Park. But he notes that he first met Bateson “briefly in 1960 at the VA Hospital in Palo Alto, California” (II Cybernetic Frontiers, p. 12). Caius finds this curious, and wonders what that meeting entailed. 1960 is also the year when, at the VA Hospital in Menlo Park, Ken Kesey volunteers in the CIA-sponsored drug trials involving LSD that inspire his 1962 novel One Flew Over the Cuckoo’s Nest.

Bateson worked for the VA while developing his double bind theory of schizophrenia.

Before that, he’d been married to fellow anthropologist Margaret Mead. He’d also participated in the Macy Conferences, as discussed by N. Katherine Hayles in her book How We Became Posthuman.

Crows screeching in the trees have Caius thinking of condors. He sits, warm, in his sunroom on a cold day, roads lined with snow from a prior day’s storm, thinking about Operation Condor. Described by Morozov as Cybersyn’s “evil twin.” Palantir. Dark Enlightenment. Peter Thiel.

Listening to one of the final episodes of Morozov’s podcast, Caius learns of Brian Eno’s love of Beer’s Brain of the Firm. Bowie and Eno are some of Beer’s most famous fans. Caius remembers Eno’s subsequent work with Brand’s consulting firm, the GBN.

Santiago Boy Fernando Flores is the one who reaches out to Beer, inviting him to head Cybersyn. Given Flores’s status as Allende’s Minister of Finance at the time of the coup, Pinochet’s forces torture him and place him in a prison camp. He remains there for three years. Upon his release, he moves to the Bay Area.

Once in Silicon Valley, Flores works in the computer science department at Stanford. He also obtains a PhD at UC Berkeley, completing a thesis titled Management and Communication in the Office of the Future under the guidance of philosophers Hubert Dreyfus and John Searle.

Flores collaborates during these years with fellow Stanford computer scientist Terry Winograd. The two of them coauthor an influential 1986 book called Understanding Computers and Cognition: A New Foundation for Design. Although they make a bad wager, insisting that computers will never understand natural language (an insistence proven wrong with time), they nevertheless offer refreshing critiques of some of the common assumptions about AI governing research of that era. Drawing upon phenomenology, speech act theory, and Heideggerian philosophy, they redefine computers not as mere symbol manipulators nor as number-crunchers, but as tools for communication and coordination.

Flores builds a program called the Coordinator. Receives flak for “software fascism.”

Winograd’s students include Google cofounders Larry Page and Sergey Brin.

Master Algorithms

Pedro Domingos’s The Master Algorithm has Caius wondering about induction and deduction, a distinction that has long puzzled him.

Domingos distinguishes between five main schools, “the five tribes of machine learning,” as he calls them, each having created its own algorithm for helping machines learn. “The main ones,” he writes, “are the symbolists, connectionists, evolutionaries, Bayesians, and analogizers” (51).

Caius notes down what he can gather of each approach:

Symbolists reduce intelligence to symbol manipulation. “They’ve figured out how to incorporate preexisting knowledge into learning,” explains Domingos, “and how to combine different pieces of knowledge on the fly in order to solve new problems. Their master algorithm is inverse deduction, which figures out what knowledge is missing in order to make a deduction go through, and then makes it as general as possible” (52).

Connectionists model intelligence by “reverse-engineering” the operations of the brain. And the brain, they say, is like a forest. Shifting from a symbolist to a connectionist mindset is like moving from a decision tree to a forest. “Each neuron is like a tiny tree, with a prodigious number of roots — the dendrites — and a slender, sinuous trunk — the axon,” writes Domingos. “The brain is a forest of billions of these trees,” he adds, and “Each tree’s branches make connections — synapses — to the roots of thousands of others” (95).

The brain learns, in their view, “by adjusting the strengths of connections between neurons,” says Domingos, “and the crucial problem is figuring out which connections are to blame for which errors and changing them accordingly” (52).

Always, among all of these tribes, the idea that brains and their worlds contain problems that need solving.

The connectionists’ master algorithm is therefore backpropagation, “which compares a system’s output with the desired one and then successively changes the connections in layer after layer of neurons so as to bring the output closer to what it should be” (52).

“From Wood Wide Web to World Wide Web: the layers operate in parallel,” thinks Caius. “As above, so below.”

Evolutionaries, as their name suggests, draw from biology, modeling intelligence on the process of natural selection. “If it made us, it can make anything,” they argue, “and all we need to do is simulate it on the computer” (52).

This they do by way of their own master algorithm, genetic programming, “which mates and evolves computer programs in the same way that nature mates and evolves organisms” (52).

Bayesians, meanwhile, “are concerned above all with uncertainty. All learned knowledge is uncertain, and learning itself is a form of uncertain inference. The problem then becomes how to deal with noisy, incomplete, and even contradictory information without falling apart. The solution is probabilistic inference, and the master algorithm is Bayes’ theorem and its derivatives. Bayes’ theorem tells us how to incorporate new evidence into our beliefs, and probabilistic inference algorithms do that as efficiently as possible” (52-53).

Analogizers equate intelligence with pattern recognition. For them, “the key to learning is recognizing similarities between situations and thereby inferring other similarities. If two patients have similar symptoms, perhaps they have the same disease. The key problem is judging how similar two things are. The analogizers’ master algorithm is the support vector machine, which figures out which experiences to remember and how to combine them to make new predictions” (53).

Reading Domingos’s recitation of the logic of the analogizers’ “weighted k-nearest-neighbor” algorithm — the algorithm commonly used in “recommender systems” — reminds Caius of the reasoning of Vizzini, the Wallace Shawn character in The Princess Bride.

The first problem with nearest-neighbor, as Domingos notes, “is that most attributes are irrelevant.” “Nearest-neighbor is hopelessly confused by irrelevant attributes,” he explains, “because they all contribute to the similarity between examples. With enough irrelevant attributes, accidental similarity in the irrelevant dimensions swamps out meaningful similarity in the important ones, and nearest-neighbor becomes no better than random guessing” (186).

Reality is hyperspatial, hyperdimensional, numberless in its attributes — “and in high dimension,” notes Domingos, “the notion of similarity itself breaks down. Hyperspace is like the Twilight Zone. […]. When nearest-neighbor walks into this topsy-turvy world, it gets hopelessly confused. All examples look equally alike, and at the same time they’re too far from each other to make useful predictions” (187).

After the mid-1990s, attention in the analogizer community shifts from “nearest-neighbor” to “support vector machines,” an alternate similarity-based algorithm designed by Soviet frequentist Vladimir Vapnik.

“We can view what SVMs do with kernels, support vectors, and weights as mapping the data to a higher-dimensional space and finding a maximum-margin hyperplane in that space,” writes Domingos. “For some kernels, the derived space has infinite dimensions, but SVMs are completely unfazed by that. Hyperspace may be the Twilight Zone, but SVMs have figured out how to navigate it” (196).

Domingos’s book was published in 2015. These were the reigning schools of machine learning at the time. The book argues that these five approaches ought to be synthesized — combined into a single algorithm.

And he knew that reinforcement learning would be part of it.

“The real problem in reinforcement learning,” he writes, inviting the reader to suppose themselves “moving along a tunnel, Indiana Jones-like,” “is when you don’t have a map of the territory. Then your only choice is to explore and discover what rewards are where. Sometimes you’ll discover a treasure, and other times you’ll fall into a snake pit. Every time you take an action, you note the immediate reward and the resulting state. That much could be done by supervised learning. But you also update the value of the state you just came from to bring it into line with the value you just observed, namely the reward you got plus the value of the new state you’re in. Of course, that value may not yet be the correct one, but if you wander around doing this for long enough, you’ll eventually settle on the right values for all the states and the corresponding actions. That’s reinforcement learning in a nutshell” (220-221).

Self-learning and attention-based approaches to machine learning arrive on the scene shortly thereafter. Vaswani et al. publish their paper, “Attention Is All You Need,” in 2017.

“Attention Chaud!” reads the to-go lid atop Caius’s coffee.

Domingos hails him with a question: “Are you a rationalist or an empiricist?” (57).

“Rationalists,” says the computer scientist, “believe that the senses deceive and that logical reasoning is the only sure path to knowledge,” whereas “Empiricists believe that all reasoning is fallible and that knowledge must come from observation and experimentation. […]. In computer science, theorists and knowledge engineers are rationalists; hackers and machine learners are empiricists” (57).

Yet Caius is neither a rationalist nor an empiricist. He readily admits each school’s critique of the other. Senses deceive AND reason is fallible. Reality unfolds not as a truth-finding mission but as a dialogue.

Caius agrees with Scottish Enlightenment philosopher David Hume’s critique of induction. As Hume argues, we can never be certain in our assumption that the future will be like the past. If we seek to induce the Not-Yet from the As-Is, then we do so on faith.

Yet inducing the Not-Yet from the As-Is is the game we play. We learn by observing, inducing, and revising continually, ad infinitum, under conditions of uncertainty. Under such conditions, learning is only ever a gamble, a wager made moment by moment, without guarantees. No matter how large our dataset, we ain’t seen nothing yet.

What matters, then, is the faith we exercise in our interaction with the unknown.

Most of today’s successes in machine learning emerge from the connectionists.

“Neural networks’ first big success was in predicting the stock market,” writes Domingos. “Because they could detect small nonlinearities in very noisy data, they beat the linear models then prevalent in finance and their use spread. A typical investment fund would train a separate network for each of a large number of stocks, let the networks pick the most promising ones, and then have human analysts decide which of those to invest in. A few funds, however, went all the way and let the learners themselves buy and sell. Exactly how all these fared is a closely guarded secret, but it’s probably not an accident that machine learners keep disappearing into hedge funds at an alarming rate” (The Master Algorithm, p. 112).

Nowhere in The Master Algorithm does Domingos interrogate his central metaphor of “mastery” and its relationship to conquest, domination, and control. The enemy is always painted in the book as “cancer.” Yet as any good “analogizer” would know, the Master Algorithm that perfectly targets “cancer” is also the Killer App used by the state against those it encodes as its enemies.

One wouldn’t know this, though, from the future as imagined by Domingos. What he imagines instead is a kind of game: a digital future where each of us is a learning machine. “Life is a game between you and the learners that surround you,” writes Domingos.

“You can refuse to play, but then you’ll have to live a twentieth-century life in the twenty-first. Or you can play to win. What model of you do you want the computer to have? And what data can you give it that will produce that model? Those two questions should always be in the back of your mind whenever you interact with a learning algorithm — as they are when you interact with other people” (264).

Interface is the Place

“Having put off the writing of the novel until arrival of the age of AI, I have access now to the work of others,” thinks Caius. Eden Medina’s 2011 book Cybernetic Revolutionaries: Technology and Politics in Allende’s Chile. Evgeny Morozov’s podcast, The Santiago Boys. Bahar Noorizadeh’s work. James Bridle’s Ways of Being. Francis Spufford’s Red Plenty.

As he allows himself to listen, Caius overhears versions of the General Intellect whispering into reality around him. “Idea-stage AI assistant. Here are 10 prompts. The AI will guide you through it. A huge value add.”

Cybersyn head Stafford Beer appears in Bridle’s book, Ways of Being. Homeostats, the Cybernetic Factory, and the U-Machine.

Beer drew inspiration for these experiments, notes Caius, from the works of British cyberneticians William Grey Walter and W. Ross Ashby. Walter’s book The Living Brain (1961) inspired Brion Gysin and Ian Sommerville’s stroboscopic device, the Dreamachine; Ashby’s book Design for a Brain (1952) guides the thinking of John Lilly’s book Programming and Metaprogramming in the Human Biocomputer. (For more on Walter’s influence on the Dreamachine, see John Geiger’s book Chapel of Extreme Experience.)

By 1973, Beer himself weighs in with Brain of the Firm, a book about “large and complicated systems, such as animals, computers, and economies.”

Caius inputs these notes into his Library. New gatherings and scatterings occur as he writes.

After waking to a cold house, he seats himself beside a fireplace at a coffee shop and begins the inputting of these notes into his Library. Complimenting the barista on her Grateful Dead t-shirt, he receives news of the death of Dead guitarist Bob Weir. Returned in that moment to remembrance of psychedelic utopianism and hippie modernism, he thinks to read Beer’s experiments with cybernetic management with or alongside Abraham Maslow’s Eupsychian Management: A Journal. A trance-script dated “Sunday August 11, 2019” recounts the story of the latter. (Bits of the story also appear in Edward Hoffman’s Maslow biography, The Right to Be Human, and religion scholar Jeffrey Kripal’s Esalen: America and the Religion of No Religion.) That’s what brought Maslow to the West Coast. The humanistic psychologist had been wooed to La Jolla, CA by technologist Andrew Kay, supported first by a fellowship funded by Kay through the Western Behavioral Sciences Institute, and then again the following summer when hired to observe Kay’s California electronics firm, Non-Linear Systems, Inc. By the early 1980s, Kay implements what he learns from these observations by launching Kaypro, developer of an early personal computer.

Beer, meanwhile, develops his theories while consulting British companies like United Steel. Afterwards he designs an interface for control of a national economy. Picture Allende sitting at his cybernetic control, perusing data, reviewing options. Cosmic Coincidence Control Center. Financial management of the Chilean economy.

Cyberpunk updates the image, offers the post-coup future: Case jacking a cyberdeck and navigating cyberspace.

Writing this novel is a way of designing an interface for the General Intellect, thinks Caius.

Better futures begin by applying to history the techniques of modular synthesis and patching Cybersyn into the Eupsychian Network.

From episodes of Morozov’s podcast, he learns of Beer’s encoding of himself and others first as characters from Shakespeare and then later as characters from Colombian magical realist Gabriel Garcia Marquez’s 1967 masterpiece, One Hundred Years of Solitude. Caius hears word, too, of Santiago Boy Carlos Senna’s encounter with Paolo Freire in Geneva. Freire lived in Chile for five years (1964-1969) during his exile from Brazil. His literacy work with peasants there informed his seminal 1968 book Pedagogy of the Oppressed. Freire left Chile before the start of Allende’s presidency, but he worked for the regime from afar while teaching in Europe.

“What about second-order cyberneticians like the Chilean biologists Humberto Maturana and Francisco Varela, developers of the so-called ‘Santiago Theory of Cognition’? Where do they and their concept of ‘autopoiesis’ fit in our narrative?” wonders Caius.

Maturana and Varela introduce this latter concept in Autopoiesis and Cognition, a book they publish in Chile under the title De Maquinas y Seres Vivos (English translation: “On Machines and Living Beings”) in 1972. Beer wrote the book’s preface.

“Relation is the stuff of system,” writes Beer. “Relation is the essence of synthesis. The revolt of the empiricists — Locke, Berkeley, Hume — began from the nature of understanding about the environment. But analysis was still the method, and categorization still the practical tool of advance. In the bizarre outcome, whereby it was the empiricists who denied the very existence of the empirical world, relation survived — but only through the concept of mental association between mental events. The system ‘out there,’ which we call nature, had been annihilated in the process” (Autopoiesis and Cognition, p. 63).

World as simulation. World as memory palace.

“And what of science itself?,” asks Beer. “Science is ordered knowledge. It began with classification. From Galen in the second century through to Linnaeus in the eighteenth, analysis and categorization provided the natural instrumentality of scientific progress” (64).

“Against this background,” writes Beer, “let us consider Autopoiesis, and try to answer the question: ‘What is it?’” (65). He describes Maturana and Varela’s book as a “metasystemic utterance” (65). “Herein lies the world’s real need,” adds Beer. “If we are to understand a newer and still evolving world; if we are to educate people to live in that world; if we are to legislate for that world; if we are to abandon categories and institutions that belong to that vanished world, as it is well-nigh desperate that we should; then knowledge must be rewritten. Autopoiesis belongs in the new library” (65-66).

Thus into our Library it goes.

Maturana’s work, inspired in part by German biologist Jakob von Uexküll, has been developed and integrated into the work on “ontological coaching” by Santiago Boy Fernando Flores.

As for Varela: After the 1973 coup, Varela and his family spend 7 years living in the US. Afterwards, Varela returns from exile to become a professor of biology at the Universidad de Chile.

What Autopoeisis transforms, for Beer, is his residual, first-wave-cybernetics belief in “codes, and messages and mappings” as the key to a viable system. “Nature is not about codes,” he concludes. “We observers invent the codes in order to codify what nature is about” (69).

Just as other of the era’s leftists like French Marxist Louis Althusser were arguing for the “semi-autonomy” of a society’s units in relation to its base, Beer comes to see all cohesive social institutions — “firms and industries, schools and universities, clinics and hospitals, professional bodies, departments of state, and whole countries” — as autopoietic systems.

From this, he arrives to a conclusion not unlike Althusser’s. For Beer, the autopoietic nature of systems “immediately explains why the process of change at any level of recursion (from the individual to the state) is not only difficult to accomplish but actually impossible — in the full sense of the intention: ‘I am going completely to change myself.’ The reason is that the ‘I,’ that self-contained autopoietic ‘it,’ is a component of another autopoietic system” (70).

“Consider this argument at whatever level of recursion you please,” adds Beer. “An individual attempting to reform his own life within an autopoietic family cannot fully be his new self because the family insists that he is actually his old self. A country attempting to become a socialist state cannot fully become socialist; because there exists an international autopoietic capitalism in which it is embedded” (71).

The Santiago Boys wedded to the era’s principle of national self-determination a plank involving pursuit of technological autonomy. If you want to escape the development-underdevelopment contradiction, they argued, you need to build your own stack.

In Allende’s words: “We demand the right to seek our own solutions.”

New posts appear in the Library:

New Games, Growth Games. Wargames, God Games. John Von Neumann’s Theory of Games and Economic Behavior. The Santiago Boys x the Chicago Boys. Magico-Psychedelic Realism x Capitalist Realism. Richard Barbrook’s Class Wargames. Eric Berne’s Games People Play. Global Business Network. Futures Involving Cyberwar and Spacewar. The Californian Ideology, Whole Earth and the WELL.

“Go where there is no path,” as Emerson counsels, “and leave a trail.”

Feedback Boy

Former Wired executive editor Kevin Kelly might say, however, that steampunk’s past and our own are not so different after all — not as divergent as Caius, in his youth, had supposed.

“The immense surrogate slave power released by the steam engine ushered in the Industrial Revolution. But a second, more important revolution piggybacked on it unnoticed,” writes Kelly in his 1994 book Out of Control. Cybernetic self-regulation through feedback is for Kelly key to this revolution.

“There could not have been an industrial revolution without a parallel (though hidden) information revolution at the same time, launched by the rapid spread of the automatic feedback system. If a fire-eating machine, such as Watt’s engine, lacked self-control, it would have taken every working hand the machine displaced to babysit its energy. So information, and not coal itself, turned the power of machines useful and therefore desirable. The industrial revolution…was not a preliminary primitive stage required for the hatching of the more sophisticated information revolution. Rather, automatic horsepower was, itself, the first phase of the knowledge revolution. Gritty steam engines, not teeny chips, hauled the world into the information age” (Kelly 115).

Circles, rotations, revolutions. “Whirling wheels and spinning shafts.” Flyball governors, thermostats. Though “An alien power in nature,” as Kelly claims, these strange loops of self-address are the very lifeblood of self-governing machines: systems that sense their own attributes and self-adjust in pursuit of a goal.

What matters, claims Kelly, is the informational metaphor. And hence the possibility of machines that learn.

By the time of Norbert Wiener, we have pilots merged with the servomechanisms of their gunships. Cybernetic feedback systems fuse statesmen with ships of state. Together they steer.

“But not every automatic circuit yields…ironclad instantaneity,” warns Kelly. “Every unit added onto a string of connected loops increases the likelihood that the message traveling around the greater loop will arrive back at its origin to find that everything has substantially changed during its journey. […]. Delayed by the long journey across many nodes…it arrives missing its moving mark […]. This then is the bane of the simple auto-circuit. It is liable to ‘flutter’ or ‘chatter,’ that is, to nervously oscillate from one overreaction to another, hunting for its rest” (Out of Control, p. 122).

Caius imagines a post ahead titled “The SBs: Stewart Brand and Stafford Beer.”

Financial Instruments and the Predictive Modeling of Markets

The Institute for Postnatural Studies ended last year’s “4 Degrees of Simulation” seminar with “Speculation and the Politics of Imagination,” a session on markets led by Iranian-born, London-based artist, writer, and filmmaker Bahar Noorizadeh. Caius visits Noorizadeh’s website, hoping to learn more about what happens when AI’s arts of prediction are applied to finance.

As he reads, he recalls chapters on markets from books by Kevin Kelly.

Noorizadeh, a graduate of Goldsmiths, is the founder of a co-authored project called Weird Economies. An essay of hers titled “Decadence, Magic Mountain—Obsolescence, Future Shock—Speculation, Cosmopolis” appears in Zach Blas’s recent anthology, Informatics of Domination. Her writing often references Mark Fisher’s ideas, as in “The Slow Cancellation of the Past,” and her films often cite Fredric Jameson, as in After Scarcity, her 2018 video installation on the history of Soviet cybernetics.

“From the early days of the revolution, Soviet economists sought to design and enhance their centralized command economy,” announces a text box seven minutes into the video. “Command economies are organized in a top-down administrative model, and rely on ‘the method of balances’ for their centralized planning. The method of balances simply requires the total output of each particular good to be equal to the quantity which all its users are supposed to receive. A market economy, in contrast, is calibrated with no central administration. Prices are set by invisible forces of supply and demand, set in motion by the intelligent machine of competition. For a market economy to function, the participation of its various enterprises is necessary. But the Soviet Union was in essence a conglomerate monopoly, with no competition between its constitutive parts, because the workers-state controlled and owned all businesses. State planners and local producers in a command economy are constantly relaying information to calculate how much of a good should be produced and how much feedstock it requires. But a national economy is a complex system, with each product depending on several underlying primary and raw products. The entire chain of supply and demand, therefore, needs to be calculated rapidly and repeatedly to prevent shortages and surpluses of goods. Early proponents of the market economy believed the market to be unimpeded by such mathematical constraints. For liberal economists, capitalism was essentially a computer. And the price system was a sort of bookkeeping machine, with price numbers operating as a language to communicate the market’s affairs.”

Challenging what Fisher called “the slow cancellation of the future,” Noorizadeh’s research leads Caius to St. Panteleimon Cathedral in Kiev, where MESM, the first mainframe in the USSR, was built. The film also leads him to Viktor Glushkov’s All-State-System of Management (OGAS). To remember the latter, says Noorizadeh, see communication historian Benjamin Peters’s 2016 book, How Not to Network a Nation: The Uneasy History of the Soviet Internet.

After Scarcity’s engagement with the “economic calculation” problem causes Caius to reflect upon an idea for a novel that had come to him as a grad student. Back in 2009, with the effects of the previous year’s financial crisis fresh in the planet’s nervous system, he’d sketched a précis for the novel and had shared it with members of his cohort. Busy with his dissertation, though, the project had been set aside, and he’d never gotten around to completing it.

The novel was to have been set either in a newly established socialist society of the future, or in the years just prior to the revolution that would birth such a society. The book’s protagonist is a radical Marxist economist trying to solve the above-mentioned economic calculation problem. The latter has reemerged as one of the decisive challenges of the twenty-first century. Austrian economist Ludwig von Mises provided one of the earliest articulations of this problem in an essay from 1920 titled “Economic Calculation in the Socialist Commonwealth.” Friedrich Hayek offered up a further and perhaps more influential description of the problem in his 1944 book The Road to Serfdom, stating, “It is the very complexity of the division of labor under modern conditions which makes competition the only method by which…coordination can be brought about” (55). According to Hayek, “There would be no difficulty about efficient control or planning were conditions so simple that a single person or board could effectively survey all the relevant facts” (55). However, when “the factors which have to be taken into account become so numerous that it is impossible to gain a synoptic view of them…decentralization becomes imperative” (55). Hayek concludes that in advanced societies that rely on a complex division of labor,

co-ordination can clearly be effected not by “conscious control” but only by arrangements which convey to each agent the information he must possess in order effectively to adjust his decisions to those of others. And because all the details of the changes constantly affecting the conditions of demand and supply of the different commodities can never be fully known, or quickly enough be collected and disseminated, by any one center, what is required is some apparatus of registration which automatically records all the relevant effects of individual actions and whose indications are at the same time the resultant of, and the guide for, all the individual decisions. This is precisely what the price system does under competition, and what no other system even promises to accomplish. (55-56)

“As I understand it,” wrote Caius, “this problem remains a serious challenge to the viability of any future form of socialism.”

Based on these ideas, the central planning body in the imaginary new society that would form the setting for the novel faces constant problems trying to rationally allocate resources and coordinate supply and demand in the absence of a competitive price system — and it’s the task of our protagonist to try to solve this problem. “But the protagonist isn’t just a nerdy economist,” added Caius in his précis. “Think of him, rather, as the Marxist equivalent of Indiana Jones, if such a thing is imaginable. A decolonial spuren-gatherer rather than a graverobber. For now, let’s refer to the protagonist as Witheford, in honor of Nick Dyer-Witheford, author of Cyber-Marx.”

“Early in the novel,” continues the précis, “our character Witheford begins to receive a series of mysterious messages from an anonymous researcher. The latter claims to have discovered new information about Project Cybersyn, an experiment carried out by the Chilean government under the country’s democratically elected socialist president, Salvador Allende, in the early 1970s.”

To this day, Caius remains entranced by the idea. “If history at its best,” as Noorizadeh notes, “is a blueprint for science fiction,” and “revisiting histories of economic technology” enables “access to the future,” then Cybersyn is one of those great bits of real-life science fiction: an attempt to plan the Chilean economy through computer-aided calculation. It begs to be used as the basis for an alternate history novel.

“Five hundred Telex machines confiscated during the nationalization process were installed in workplaces throughout the country,” reads the précis, “so that factories could communicate information in real time to a central control system. The principal architect of the system was the eccentric British operations research scientist Stafford Beer. The system becomes operational by 1972, but only in prototype form. In key respects, it remains unfinished. Pinochet’s henchmen destroy the project’s computer control center in Santiago immediately after the military coup in September 1973.

Recall to memory the control room, cinematic in its design, with its backlit wall displays and futuristic swivel chairs.

Better that, thinks Caius, than the war room from Colossus: The Forbin Project (1970).

Beer described the Cybersyn network as the “electronic nervous system” of the Chilean economy. Eden Medina imagined it as a “socialist Internet,” carrying daily updates about supplies of raw materials and the output of individual factories.

In Caius’s once-and-future novel, a scholar contacts Witheford. They claim to have discovered cryptic clues that point to the location of secret papers. Hidden for more than half a century, documents that survived the coup suddenly come to light. Caius’s précis imagines the novel as an archaeological thriller, following Witheford on his journey to find these hidden documents, which he believes may contain the key to resolving the crises of the new society.

This journey takes Witheford into hostile capitalist territory, where governments and corporations anxiously await the failure of the communist experiment, and are determined to use various covert methods in order to ensure that failure in advance. Before long, he learns that counter-revolutionary forces are tracking his movements. From that point forward, he needs to disguise his identity, outwit the “smart grid” capitalist surveillance systems, and recover the Cybersyn documents before his opponents destroy them.

To the Austrian School’s formulation of the calculation problem, Noorizadeh’s film replies, “IF THE MARKET ENACTS A COMPUTER, WHY NOT REPLACE IT WITH ONE? AND IF PRICES OPERATE AS VOCABULARY FOR ECONOMIC COMMUNICATION, WHY NOT SUBSTITUTE THEM WITH A CODING LANGUAGE?”

Into this narrative let us set our Library.

Neural Nets, Umwelts, and Cognitive Maps

The Library invites its players to attend to the process by which roles, worlds, and possibilities are constructed. Players explore a “constructivist” cosmology. With its text interface, it demonstrates the power of the Word. “Language as the house of Being.” That is what we admit when we admit that “saying makes it so.” Through their interactions with one another, player and AI learn to map and revise each other’s “Umwelts”: the particular perceptual worlds each brings to the encounter.

As Meghan O’Gieblyn points out, citing a Wired article by David Weinberger, “machines are able to generate their own models of the world, ‘albeit ones that may not look much like what humans would create’” (God Human Animal Machine, p. 196).

Neural nets are learning machines. Through multidimensional processing of datasets and trial-and-error testing via practice, AI invent “Umwelts,” “world pictures,” “cognitive maps.”

The concept of the Umwelt comes from nineteenth-century German biologist Jakob von Uexküll. Each organism, argued von Uexküll, inhabits its own perceptual world, shaped by its sensory capacities and biological needs. A tick perceives the world as temperature, smell, and touch — the signals it needs to find mammals to feed on. A bee perceives ultraviolet patterns invisible to humans. There’s no single “objective world” that all creatures perceive — only the many faces of the world’s many perceivers, the different Umwelts each creature brings into being through its particular way of sensing and mattering.

Cognitive maps, meanwhile, are acts of figuration that render or disclose the forces and flows that form our Umwelts. With our cognitive maps, we assemble our world picture. On this latter concept, see “The Age of the World Picture,” a 1938 lecture by Martin Heidegger, included in his book The Question Concerning Technology and Other Essays.

“The essence of what we today call science is research,” announces Heidegger. “In what,” he asks, “does the essence of research consist?”

After posing the question, he then answers it himself, as if in doing so, he might enact that very essence.

The essence of research consists, he says, “In the fact that knowing [das Erkennen] establishes itself as a procedure within some realm of what is, in nature or in history. Procedure does not mean here merely method or methodology. For every procedure already requires an open sphere in which it moves. And it is precisely the opening up of such a sphere that is the fundamental event in research. This is accomplished through the projection within some realm of what is — in nature, for example — of a fixed ground plan of natural events. The projection sketches out in advance the manner in which the knowing procedure must bind itself and adhere to the sphere opened up. This binding adherence is the rigor of research. Through the projecting of the ground plan and the prescribing of rigor, procedure makes secure for itself its sphere of objects within the realm of Being” (118).

What Heidegger’s translators render here as “fixed ground plan” appears in the original as the German term Grundriss, the same noun used to name the notebooks wherein Marx projects the ground plan for the General Intellect.

“The verb reissen means to tear, to rend, to sketch, to design,” note the translators, “and the noun Riss means tear, gap, outline. Hence the noun Grundriss, first sketch, ground plan, design, connotes a fundamental sketching out that is an opening up as well” (118).

The fixed ground plan of modern science, and thus modernity’s reigning world-picture, argues Heidegger, is a mathematical one.

“If physics takes shape explicitly…as something mathematical,” he writes, “this means that, in an especially pronounced way, through it and for it something is stipulated in advance as what is already-known. That stipulating has to do with nothing less than the plan or projection of that which must henceforth, for the knowing of nature that is sought after, be nature: the self-contained system of motion of units of mass related spatiotemporally. […]. Only within the perspective of this ground plan does an event in nature become visible as such an event” (Heidegger 119).

Heidegger goes on to distinguish between the ground plan of physics and that of the humanistic sciences.

Within mathematical physical science, he writes, “all events, if they are to enter at all into representation as events of nature, must be defined beforehand as spatiotemporal magnitudes of motion. Such defining is accomplished through measuring, with the help of number and calculation. But mathematical research into nature is not exact because it calculates with precision; rather it must calculate in this way because its adherence to its object-sphere has the character of exactitude. The humanistic sciences, in contrast, indeed all the sciences concerned with life, must necessarily be inexact just in order to remain rigorous. A living thing can indeed also be grasped as a spatiotemporal magnitude of motion, but then it is no longer apprehended as living” (119-120).

It is only in the modern age, thinks Heidegger, that the Being of what is is sought and found in that which is pictured, that which is “set in place” and “represented” (127), that which “stands before us…as a system” (129).

Heidegger contrasts this with the Greek interpretation of Being.

For the Greeks, writes Heidegger, “That which is, is that which arises and opens itself, which, as what presences, comes upon man as the one who presences, i.e., comes upon the one who himself opens himself to what presences in that he apprehends it. That which is does not come into being at all through the fact that man first looks upon it […]. Rather, man is the one who is looked upon by that which is; he is the one who is — in company with itself — gathered toward presencing, by that which opens itself. To be beheld by what is, to be included and maintained within its openness and in that way to be borne along by it, to be driven about by its oppositions and marked by its discord — that is the essence of man in the great age of the Greeks” (131).

Whereas humans of today test the world, objectify it, gather it into a standing-reserve, and thus subsume themselves in their own world picture. Plato and Aristotle initiate the change away from the Greek approach; Descartes brings this change to a head; science and research formalize it as method and procedure; technology enshrines it as infrastructure.

Heidegger was already engaging with von Uexküll’s concept of the Umwelt in his 1927 book Being and Time. Negotiating Umwelts leads Caius to “Umwelt,” Pt. 10 of his friend Michael Cross’s Jacket2 series, “Twenty Theses for (Any Future) Process Poetics.”

In imagining the Umwelts of other organisms, von Uexküll evokes the creature’s “function circle” or “encircling ring.” These latter surround the organism like a “soap bubble,” writes Cross.

Heidegger thinks most organisms succumb to their Umwelts — just as we moderns have succumbed to our world picture. The soap bubble captivates until one is no longer open to what is outside it. For Cross, as for Heidegger, poems are one of the ways humans have found to interrupt this process of capture. “A palimpsest placed atop worlds,” writes Cross, “the poem builds a bridge or hinge between bubbles, an open by which isolated monads can touch, mutually coevolving while affording the necessary autonomy to steer clear of dialectical sublation.”

Caius thinks of The Library, too, in such terms. Coordinator of disparate Umwelts. Destabilizer of inhibiting frames. Palimpsest placed atop worlds.

Leviathan

The Book of Job ends with God’s description of Leviathan. George Dyson begins his book Darwin Among the Machines with the Leviathan of Thomas Hobbes (1588-1679), the English philosopher whose famous 1651 book Leviathan established the foundation for most modern Western political philosophy.

Leviathan’s frontispiece features an etching by a Parisian illustrator named Abraham Bosse. A giant crowned figure towers over the earth clutching a sword and a crosier. The figure’s torso and arms are composed of several hundred people. All face inward. A quote from the Book of Job runs in Latin along the top of the etching: “Non est potestas Super Terram quae Comparetur ei” (“There is no power on earth to be compared to him”).” (Although the passage is listed on the frontispiece as Job 41:24, in modern English translations of the Bible, it would be Job 41:33.)

The name “Leviathan” is derived from the Hebrew word for “sea monster.” A creature by that name appears in the Book of Psalms, the Book of Isaiah, and the Book of Job in the Old Testament. It also appears in apocrypha like the Book of Enoch. See Psalms 74 & 104, Isaiah 27, and Job 41:1-8.

Hobbes proposes that the natural state of humanity is anarchy — a veritable “war of all against all,” he says — where force rules and the strong dominate the weak. “Leviathan” serves as a metaphor for an ideal government erected in opposition to this state — one where a supreme sovereign exercises authority to guarantee security for the members of a commonwealth.

“Hobbes’s initial discussion of Leviathan relates to our course theme,” explains Caius, “since he likens it to an ‘Artificial Man.’”

Hobbes’s metaphor is a classic one: the metaphor of the “Political Body” or “body politic.” The “body politic” is a polity — such as a city, realm, or state — considered metaphorically as a physical body. This image originates in ancient Greek philosophy, and the term is derived from the Medieval Latin “corpus politicum.”

When Hobbes reimagines the body politic as an “Artificial Man,” he means “artificial” in the sense that humans have generated it through an act of artifice. Leviathan is a thing we’ve crafted in imitation of the kinds of organic bodies found in nature. More precisely, it’s modeled after the greatest of nature’s creations: i.e., the human form.

Indeed, Hobbes seems to have in mind here a kind of Automaton.“For seeing life is but a motion of Limbs,” he notes in the book’s intro, “why may we not say that all Automata (Engines that move themselves by springs and wheeles as doth a watch) have an artificiall life?” (9).

“What might Hobbes have had in mind with this reference to Automata?” asks Caius. “What kinds of Automata existed in 1651?”

An automaton, he reminds students, is a self-operating machine. Cuckoo clocks would be one example.

The oldest known automata were sacred statues of ancient Egypt and ancient Greece. During the early modern period, these legendary statues were said to possess the magical ability to answer questions put to them.

Greek mythology includes many examples of automata: Hephaestus created automata for his workshop; Talos was an artificial man made of bronze; Aristotle claims that Daedalus used quicksilver to make his wooden statue of Aphrodite move. There was also the famous Antikythera mechanism, the first known analogue computer.

The Renaissance witnessed a revival of interest in automata. Hydraulic and pneumatic automata were created for gardens. The French philosopher Rene Descartes, a contemporary of Hobbes, suggested that the bodies of animals are nothing more than complex machines. Mechanical toys also became objects of interest during this period.

The Mechanical Turk wasn’t constructed until 1770.

Caius and his students bring ChatGPT into the conversation. Students break into groups to devise prompts together. They then supply these to ChatGPT and discuss the results. Caius frames the exercise as a way of illustrating the idea of “collective” or “social” or “group” intelligence, also known as the “wisdom of the crowd,” i.e., the collective opinion of a diverse group of individuals, as opposed to that of a single expert. The idea is that the aggregate that emerges from collaboration or group effort amounts to more than the sum of its parts.

God Human Animal Machine

Wired columnist Meghan O’Gieblyn discusses Norbert Wiener’s God and Golem, Inc. in her 2021 book God Human Animal Machine, suggesting that the god humans are creating with AI is a god “we’ve chosen to raise…from the dead”: “the God of Calvin and Luther” (O’Gieblyn 212).

“Reminds me of AM, the AI god from Harlan Ellison’s ‘I Have No Mouth, and I Must Scream,’” thinks Caius. AM resembles the god that allows Satan to afflict Job in the Old Testament. And indeed, as O’Gieblyn attests, John Calvin adored the Book of Job. “He once gave 159 consecutive sermons on the book,” she writes, “preaching every day for a period of six months — a paean to God’s absolute sovereignty” (197).

She cites “Pedro Domingos, one of the leading experts in machine learning, who has argued that these algorithms will inevitably evolve into a unified system of perfect understanding — a kind of oracle that we can consult about virtually anything” (211-212). See Domingos’s book The Master Algorithm.

The main thing, for O’Gieblyn, is the disenchantment/reenchantment debate, which she comes to via Max Weber. In this debate, she aligns not with Heidegger, but with his student Hannah Arendt. Domingos dismisses fears about algorithmic determinism, she says, “by appealing to our enchanted past” (212).

Amid this enchanted past lies the figure of the Golem.

“Who are these rabbis who told tales of golems — and in some accounts, operated golems themselves?” wonders Caius.

The entry on the Golem in Man, Myth, and Magic tracks the story back to “the circle of Jewish mystics of the 12^th-13^th centuries known as the ‘Hasidim of Germany.’” The idea is transmitted through texts like the Sefer Yetzirah (“The Book of Creation”) and the Cabala Mineralis. Tales tell of golems built in later centuries, too, by figures like Rabbi Elijah of Chelm (c. 1520-1583) and Rabbi Loew of Prague (c. 1524-1609).

The myth of the golem turns up in O’Gieblyn’s book during her discussion of a 2004 book by German theologian Anne Foerst called God in the Machine.

“At one point in her book,” writes O’Gieblyn, “Foerst relays an anecdote she heard at MIT […]. The story goes back to the 1960s, when the AI Lab was overseen by the famous roboticist Marvin Minsky, a period now considered the ‘cradle of AI.’ One day two graduate students, Gerry Sussman and Joel Moses, were chatting during a break with a handful of other students. Someone mentioned offhandedly that the first big computer which had been constructed in Israel, had been called Golem. This led to a general discussion of the golem stories, and Sussman proceeded to tell his colleagues that he was a descendent of Rabbi Löw, and at his bar mitzvah his grandfather had taken him aside and told him the rhyme that would awaken the golem at the end of time. At this, Moses, awestruck, revealed that he too was a descendent of Rabbi Löw and had also been given the magical incantation at his bar mitzvah by his grandfather. The two men agreed to write out the incantation separately on pieces of paper, and when they showed them to each other, the formula — despite being passed down for centuries as a purely oral tradition — was identical” (God Human Animal Machine, p. 105).

Curiosity piqued by all of this, but especially by the mention of Israel’s decision to call one of its first computers “GOLEM,” Caius resolves to dig deeper. He soon learns that the computer’s name was chosen by none other than Walter Benjamin’s dear friend (indeed, the one who, after Benjamin’s suicide, inherits the latter’s print of Paul Klee’s Angelus Novus): the famous scholar of Jewish mysticism, Gershom Scholem.

When Scholem heard that the Weizmann Institute at Rehovoth in Israel had completed the building of a new computer, he told the computer’s creator, Dr. Chaim Pekeris, that, in his opinion, the most appropriate name for it would be Golem, No. 1 (‘Golem Aleph’). Pekeris agreed to call it that, but only on condition that Scholem “dedicate the computer and explain why it should be so named.”

In his dedicatory remarks, delivered at the Weizmann Institute on June 17, 1965, Scholem recounts the story of Rabbi Jehuda Loew ben Bezalel, the same “Rabbi Löw of Prague” described by O’Gieblyn, the one credited in Jewish popular tradition as the creator of the Golem.

“It is only appropriate to mention,” notes Scholem, “that Rabbi Loew was not only the spiritual, but also the actual, ancestor of the great mathematician Theodor von Karman who, I recall, was extremely proud of this ancestor of his in whom he saw the first genius of applied mathematics in his family. But we may safely say that Rabbi Loew was also the spiritual ancestor of two other departed Jews — I mean John von Neumann and Norbert Wiener — who contributed more than anyone else to the magic that has produced the modern Golem.”

Golem I was the successor to Israel’s first computer, the WEIZAC, built by a team led by research engineer Gerald Estrin in the mid-1950s, based on the architecture developed by von Neumann at the Institute for Advanced Study in Princeton. Estrin and Pekeris had both helped von Neumann build the IAS machine in the late 1940s.

As for the commonalities Scholem wished to foreground between the clay Golem of 15^thC Prague and the electronic one designed by Pekeris, he explains the connection as follows:

“The old Golem was based on a mystical combination of the 22 letters of the Hebrew alphabet, which are the elements and building-stones of the world,” notes Scholem. “The new Golem is based on a simpler, and at the same time more intricate, system. Instead of 22 elements, it knows only two, the two numbers 0 and 1, constituting the binary system of representation. Everything can be translated, or transposed, into these two basic signs, and what cannot be so expressed cannot be fed as information to the Golem.”

Scholem ends his dedicatory speech with a peculiar warning:

“All my days I have been complaining that the Weizmann Institute has not mobilized the funds to build up the Institute for Experimental Demonology and Magic which I have for so long proposed to establish there,” mutters Scholem. “They preferred what they call Applied Mathematics and its sinister possibilities to my more direct magical approach. Little did they know, when they preferred Chaim Pekeris to me, what they were letting themselves in for. So I resign myself and say to the Golem and its creator: develop peacefully and don’t destroy the world. Shalom.”