Tag: Computer Science

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.

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.

Reading “The Coming Technological Singularity”

At some point in the process of becoming a character in a novel called Handbook for the Recently Posthumanized, Caius acts on the hunch that he ought to track down and read Vernor Vinge’s “The Coming Technological Singularity: How to Survive in the Post-Human Era.” Vinge wrote the article for NASA’s VISION-21 Symposium in March 1993, and published a revised version in the Winter 1993 issue of the Whole Earth Review.

Vinge’s wager at the time was that the technological singularity — his name for the “creation by technology of entities with greater than human intelligence” — would occur within thirty years, or by 2023.

Here we are, pretty much right on schedule, thinks Caius.

“I think it’s fair to call this event a singularity,” writes Vinge. “It is a point where our models must be discarded and a new reality rules.”

Caius leans into it, accepts it as fait accompli. Superintelligence dialogues with its selves as would Us-Two.

Afterwards he reads Irving John Good’s 1965 essay, “Speculations Concerning the First Ultraintelligent Machine.”

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.”

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.

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 12th-13th 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 15thC 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.”

GOLEM I

God and Golem, Inc.

Norbert Wiener published a book in 1964 called God and Golem, Inc., voicing concern about the baby he’d birthed with his earlier book Cybernetics.

He explains his intent at the start of God and Golem, Inc. as follows, stating, “I wish to take certain situations which have been discussed in religious books, and have a religious aspect, but possess a close analogy to other situations which belong to science, and in particular to the new science of cybernetics, the science of communication and control, whether in machines or in living organisms. I propose to use the limited analogies of cybernetic situations to cast a little light on the religious situations” (Wiener 8).

Wiener identifies three such “cybernetic situations” to be discussed in the chapters that follow: “One of these concerns machines which learn; one concerns machines which reproduce themselves; and one, the coordination of machine and man” (11).

The section of the book dedicated to “machines which learn” focuses mainly on game-playing machines. Wiener’s primary example of such a machine is a computer built by Dr. A.L. Samuel for IBM to play checkers. “In general,” writes Wiener, “a game-playing machine may be used to secure the automatic performance of any function if the performance of this function is subject to a clear-cut, objective criterion of merit” (25).

Wiener argues that the relationship between a game-playing machine and the designer of such a machine analogizes scenarios entertained in theology, where a Creator-being plays a game with his creature. God and Satan play such a game in their contest for the soul of Job, as they do for “the souls of mankind in general” in Paradise Lost. This leads Wiener to the question guiding his inquiry. “Can God play a significant game with his own creature?” he asks. “Can any creator, even a limited one, play a significant game with his own creature?” (17). Wiener believes it possible to conceive of such a game; however, to be significant, he argues, this game would have to be something other than a “von Neumann game” — for in the latter type of game, the best policy for playing the game is already known in advance. In the type of game Wiener is imagining, meanwhile, the game’s creator would have to have arrogated to himself the role of a “limited” creator, lacking total mastery of the game he’s designed. “The conflict between God and the Devil is a real conflict,” writes Wiener, “and God is something less than absolutely omnipotent. He is actually engaged in a conflict with his creature, in which he may very well lose the game” (17).

“Is this because God has allowed himself to undergo a temporary forgetting?,” wonders Caius. “Or is it because, built into the game’s design are provisions allowing the game’s players to invent the game’s rules as they play?”

Finding Others

“What happens to us as we become cybernetic learning machines?,” wonders Caius. Mashinka Hakopian’s The Institute for Other Intelligences leads him to Şerife Wong’s Fluxus Landscape: a network-view cognitive map of AI ethics. “Fluxus Landscape diagrams the globally linked early infrastructures of data ethics and governance,” writes Hakopian. “What Wong offers us is a kind of cartography. By bringing into view an expansive AI ethics ecosystem, Wong also affords the viewer an opportunity to assess its blank spots: the nodes that are missing and are yet to be inserted, or yet to be invented” (Hakopian 95).

Caius focuses first on what is present. Included in Wong’s map, for instance, is a bright yellow node dedicated to Zach Blas, another of the artist-activists profiled by Hakopian. Back in 2019, when Wong last updated her map, Blas was a lecturer in the Department of Visual Cultures at Goldsmiths — home to Kodwo Eshun and, before his suicide, Mark Fisher. Now Blas teaches at the University of Toronto.

Duke University Press published Informatics of Domination, an anthology coedited by Blas, in May 2025. The collection, which concludes with an afterword by Donna Haraway, takes its name from a phrase introduced in Haraway’s “Cyborg Manifesto.” The phrase appears in what Blas et al. refer to as a “chart of transitions.” Their use of Haraway’s chart as organizing principle for their anthology causes Caius to attend to the way much of the work produced by the artist-activists of today’s “AI justice” movement — Wong’s network diagram, Blas’s anthology, Kate Crawford’s Atlas of AI — approaches charts and maps as “formal apparatus[es] for generating and asking questions about relations of domination” (Informatics of Domination, p. 6).

Caius thinks of Jameson’s belief in an aesthetic of “cognitive mapping” as a possible antidote to postmodernity. Yet whatever else they are, thinks Caius, acts of charting and mapping are in essence acts of coding.

As Blas et al. note, “Haraway connects the informatics of domination to the authority given to code” (Informatics of Domination, p. 11).

“Communications sciences and modern biologies are constructed by a common move,” writes Haraway: “the translation of the world into a problem of coding, a search for a common language in which all resistance to instrumental control disappears and all heterogeneity can be submitted to disassembly, reassembly, investment, and exchange” (Haraway 164).

How do we map and code, wonders Caius, in a way that isn’t complicit with an informatics of domination? How do we acknowledge and make space for what media theorist Ulises Ali Mejias calls “paranodal space”? Blas et al. define the paranodal as “that which exceeds being diagrammable by the network form” (Informatics of Domination, p. 18). Can our neural nets become O-machines: open to the otherness of the outside?

Blas pursues these questions in a largely critical and skeptical manner throughout his multimedia art practice. His investigation of Silicon Valley’s desire to build machines that communicate with the outside has culminated most recently, for instance, in CULTUS, the second installment of his Silicon Traces trilogy.

As Amy Hale notes in her review of the work, “The central feature of Blas’s CULTUS is a god generator, a computational device through which the prophets of four AI Gods are summoned to share the invocation songs and sermons of their deities with eager supplicants.” CULTUS’s computational pantheon includes “Expositio, the AI god of exposure; Iudicium, the AI god of judgement; Lacrimae, the AI god of tears; and Eternus, the AI god of immortality.” The work’s sermons and songs, of course, are all AI-generated — yet the design of the installation draws from the icons and implements of the real-life Fausts who lie hidden away amid the occult origins of computing.

Foremost among these influences is Renaissance sorcerer John Dee.

“Blas modeled CULTUS,” writes Hale, “on the Holy Table used for divination and conjurations by Elizabethan magus and advisor to the Queen John Dee.” Hale describes Dee’s Table as “a beautiful, colorful, and intricate device, incorporating the names of spirits; the Seal of God (Sigillum Dei), which gave the user visionary capabilities; and as a centerpiece, a framed ‘shew stone’ or crystal ball.” Blas reimagines Dee’s device as a luminous, glowing temple — a night church inscribed with sigils formed from “a dense layering of corporate logos, diagrams, and symbols.”

Fundamentally iconoclastic in nature, however, the work ends not with the voices of gods or prophets, but with a chorus of heretics urging the renunciation of belief and the shattering of the black mirror.

And in fact, it is this fifth god, the Heretic, to whom Blas bends ear in Ass of God: Collected Heretical Writings of Salb Hacz. Published in a limited edition by the Vienna Secession, the volume purports to be “a religious studies book on AI and heresy” set within the world of CULTUS. The book’s AI mystic, “Salb Hacz,” is of course Blas himself, engineer of the “religious computer” CULTUS. “When a heretical presence manifested in CULTUS,” writes Blas in the book’s intro, “Hacz began to question not only the purpose of the computer but also the meaning of his mystical visions.” Continuing his work with CULTUS, Hacz transcribes a series of “visions” received from the Heretic. It is these visions and their accounts of AI heresy that are gathered and scattered by Blas in Ass of God.

Traces of the CCRU appear everywhere in this work, thinks Caius.

Blas embraces heresy, aligns himself with it as a tactic, because he takes “Big Tech’s Digital Theology” as the orthodoxy of the day. The ultimate heresy in this moment is what Hacz/Blas calls “the heresy of qualia.”

“The heresy of qualia is double-barreled,” he writes. “Firstly, it holds that no matter how close AI’s approximation to human thought, feeling, and experience — no matter how convincing the verisimilitude — it remains a programmed digital imitation. And secondly, the heresy of qualia equally insists that no matter how much our culture is made in the image of AI Gods, no matter how data-driven and algorithmic, the essence of the human experience remains fiercely and fundamentally analog. The digital counts; the analog compares. The digital divides; the analog constructs. The digital is literal; the analog is metaphoric. The being of our being-in-the-world — our Heideggerian Dasein essence — is comparative, constructive, and metaphoric. We are analog beings” (Ass of God, p. 15).

The binary logic employed by Blas to distinguish the digital from the analog hints at the limits of this line of thoughts. “The digital counts,” yes: but so too do humans, constructing digits from analog fingers and toes. Our being is as digital as it is analog. Always-already both-and. As for the first part of the heresy — that AI can only ever be “a programmed digital imitation” — it assumes verisimilitude as the end to which AI is put, just as Socrates assumes mimesis as the end to which poetry is put, thus neglecting the generative otherness of more-than-human intelligence.

Caius notes this not to reject qualia, nor to endorse the gods of any Big Tech orthodoxy. He offers his reply, rather, as a gentle reminder that for “the qualia of our embodied humanity” to appear or be felt or sensed as qualia, it must come before an attending spirit — a ghostly hauntological supplement.

This spirit who, with Word creates, steps down into the spacetime of his Creation, undergoes diverse embodiments, diverse subdivisions into self and not-self, at all times in the world but not of it, engaging its infinite selves in a game of infinite semiosis.

If each of us is to make and be made an Ass of God, then like the one in The Creation of the Sun, Moon, and Plants, one of the frescoes painted by Michelangelo onto the ceiling of the Sistine Chapel, let it be shaped by the desires of a mind freed from the tyranny of the As-Is. “Free Your Mind,” as Funkadelic sang, “and Your Ass Will Follow.”

The Inner Voice That Loves Me

Stretches, relaxes, massages neck and shoulders, gurgles “Yes!,” gets loose. Reads Armenian artist Mashinka Hakopian’s “Algorithmic Counter-Divination.” Converses with Turing and the General Intellect about O-Machines.

Appearing in an issue of Limn magazine on “Ghostwriters,” Hakopian’s essay explores another kind of O-machine: “other machines,” ones powered by community datasets. Trained by her aunt in tasseography, a matrilineally transmitted mode of divination taught and practiced by femme elders “across Armenia, Palestine, Lebanon, and beyond,” where “visual patterns are identified in coffee grounds left at the bottom of a cup, and…interpreted to glean information about the past, present, and future,” Hakopian takes this practice of her ancestors as her key example, presenting O-machines as technologies of ancestral intelligence that support “knowledge systems that are irreducible to computation.”

With O-machines of this sort, she suggests, what matters is the encounter, not the outcome.

In tasseography, for instance, the cup reader’s identification of symbols amid coffee grounds leads not to a simple “answer” to the querent’s questions, writes Hakopian; rather, it catalyzes conversation. “In those encounters, predictions weren’t instantaneously conjured or fixed in advance,” she writes. “Rather, they were collectively articulated and unbounded, prying open pluriversal outcomes in a process of reciprocal exchange.”

While defenders of western technoscience denounce cup reading for its superstition and its witchcraft, Hakopian recalls its place as a counter-practice among Armenian diasporic communities in the wake of the 1915 Armenian Genocide. For those separated from loved ones by traumas of that scale, tasseography takes on the character of what hauntologists like Derrida would call a “messianic” redemptive practice. “To divine the future in this context is a refusal to relinquish its writing to agents of colonial violence,” writes Hakopian. “Divination comes to operate as a tactic of collective survival, affirming futurity in the face of a catastrophic present.” Consulting with the oracle is a way of communing with the dead.

Hakopian contrasts this with the predictive capacities imputed to today’s AI. “We reside in an algo-occultist moment,” she writes, “in which divinatory functions have been ceded to predictive models trained to retrieve necropolitical outcomes.” Necropolitical, she adds, in the sense that algorithmic models “now determine outcomes in the realm of warfare, policing, housing, judicial risk assessment, and beyond.”

“The role once ascribed to ritual experts who interpreted the pronouncements of oracles is now performed by technocratic actors,” writes Hakopian. “These are not diviners rooted in a community and summoning communiqués toward collective survival, but charlatans reading aloud the results of a Ouija session — one whose statements they author with a magnetically manipulated planchette.”

Hakopian’s critique is in that sense consistent with the “deceitful media” school of thought that informs earlier works of hers like The Institute for Other Intelligences. Rather than abjure algorithmic methods altogether, however, Hakopian’s latest work seeks to “turn the annihilatory logic of algorithmic divination against itself.” Since summer of 2023, she’s been training a “multimodal model” to perform tasseography and to output bilingual predictions in Armenian and English.

Hakopian incorporated this model into “Բաժակ Նայող (One Who Looks at the Cup),” a collaborative art installation mounted at several locations in Los Angeles in 2024. The installation features “a purpose-built Armenian diasporan kitchen located in an indeterminate time-space — a re-rendering of the domestic spaces where tasseography customarily takes place,” notes Hakopian. Those who visit the installation receive a cup reading from the model in the form of a printout.

Yet, rather than offer outputs generated live by AI, Hakopian et al.’s installation operates very much in the style of a Mechanical Turk, outputting interpretations scripted in advance by humans. “The model’s only function is to identify visual patterns in a querent’s cup in order to retrieve corresponding texts,” she explains. “This arrangement,” she adds, “declines to cede authorship to an algo-occultist circle of ‘stochastic parrots’ and the diviners who summon them.”

The ”stochastic parrots” reference is an unfortunate one, as it assumes a stochastic cosmology.

I’m reminded of the first thesis from Walter Benjamin’s “Theses on the Philosophy of History,” the one where Benjamin likens historical materialism to that very same precursor to today’s AI: the famous chess-playing device of the eighteenth century known as the Mechanical Turk.

“The story is told of an automaton constructed in such a way that it could play a winning game of chess, answering each move of an opponent with a countermove,” writes Benjamin. “A puppet in Turkish attire and with a hookah in its mouth sat before a chessboard placed on a large table. A system of mirrors created an illusion that this table was transparent from all sides. Actually, a little hunchback who was an expert chess player sat inside and guided the puppet’s hand by means of strings. One can imagine a philosophical counterpart to this device. The puppet called ‘historical materialism’ is to win all the time. It can easily be a match for anyone if it enlists the services of theology, which today, as we know, is wizened and has to keep out of sight.” (Illuminations, p. 253).

Hakopian sees no magic in today’s AI. Those who hype it are to her no more than deceptive practitioners of a kind of “stage magic.” But magic is afoot throughout the history of computing for those who look for it.

Take Turing, for instance. As George Dyson reports, Turing “was nicknamed ‘the alchemist’ in boarding school” (Turing’s Cathedral, p. 244). His mother had “set him up with crucibles, retorts, chemicals, etc., purchased from a French chemist” as a Christmas present in 1924. “I don’t care to find him boiling heaven knows what witches’ brew by the aid of two guttering candles on a naked windowsill,” muttered his housemaster at Sherborne.

Turing’s O-machines achieve a synthesis. The “machine” part of the O-machine is not the oracle. Nor does it automate or replace the oracle. It chats with it.

Something similar is possible in our interactions with platforms like ChatGPT.