http://www.egs.edu Benjamin H. Bratton, born 1968, is an American theorist, sociologist and professor of visual arts, contemporary social and political theory, philosophy, and design.

The Post-Anthropocene: The Turing-incomplete Orchid Mantis Evolves Machine Vision. Public open lecture for the students and faculty of the European Graduate School EGS Media and Communication Studies department program Saas-Fee Switzerland Europe. 2015.

Benjamin H. Bratton, (b. 1968), is an American theorist, sociologist, and professor of visual arts, contemporary social and political theory, philosophy, and design. His research deals with computational media and infrastructure, design research management & methodologies, classical and contemporary sociological theory, architecture and urban design issues, and the politics of synthetic ecologies and biologies.

Bratton completed his doctoral studies in the sociology of technology at the University of California, Santa Barbara​, and was the Director of the Advanced Strategies Group at Yahoo! before expanding his cross-disciplinary research and practice in academia. He taught in the Department of Design/Media Art at UCLA from 2003-2008, and at the SCI Arc​ (Southern California Institute of Architecture)​ for a decade, and continues to teach as a member of the Visiting Faculty. While at SCI Arc, Benjamin Bratton and Hernan Diaz-Alonso co-founded the XLAB courses, which placed students in laboratory settings where they could work directly and comprehensively in robotics, scripting, biogenetics, genetic codification, and cellular systems​. Currently, in addition to his professorship at EGS, Bratton is an associate professor of Visual Arts at the University of California, San Dieg​o, where he also directs the Center for Design and Geopolitics, partnering with the California Institute of Telecommunications and Information Technology​.

In addition to his formal positions, Benjamin H. Bratton is a regular visiting lecturer at numerous universities and institutions including: Columbia University, Yale University, Pratt Institute, Bartlett School of Architecture, University of Pennsylvania, University of Southern California, University of California, Art Center College of Design, Parsons The New School for Design, University of Michigan, Brown University, The University of Applied Arts in Vienna, Bauhaus- University, Moscow State University, Moscow Institute for Higher Economics, and the Architectural Association School of Architecture in London.

Bratton's current projects focus on the political geography of cloud computing, massively- granular universal addressing systems, and alternate models of ecological governance. In his most recent book, The Stack: On Software and Sovereignty (MIT Press, 2015), Bratton asks the question, "What has planetary-scale computation done to our geopolitical realities?​" and in response, offers the proposition "that smart grids, cloud computing, mobile software and smart cities, universal addressing systems, ubiquitous computing, and other types of apparently unrelated planetary-scale computation can be viewed as forming a coherent whole—an accidental megastructure called The Stack that is both a computational apparatus and a new geopolitical architecture.​"

Other more recent texts include the following: Some Trace Effects of the Post-Anthropocene: On Accelerationist Geopolitical Aesthetics, On Apps and Elementary Forms of Interfacial Life: Object, Image, Superimposition, Deep Address, What We Do is Secrete: On Virilio, Planetarity and Data Visualization, Geoscapes & the Google Caliphate: On Mumbai Attacks, Root the Earth: On Peak Oil Apohenia and Suspicious Images/ Latent Interfaces (with Natalie Jeremijenko), iPhone City, Logistics of Habitable Circulation (introduction to the 2008 edition of Paul Virilio’s Speed and Politics). As well, recent online lectures include: 2 or 3 Things I Know About The Stack, at Bartlett School of Architecture, University of London, and University of Southampton;Cloud Feudalism at Proto/E/Co/Logics 002, Rovinj, Croatia; Nanoskin at Parsons School of Design; On the Nomos of the Cloud at Berlage Institute, Rotterdam, École Normale- Superiore, Paris, and MOCA, Los Angeles; Accidental Geopolitics at The Guardian Summit, New York; Ambivalence and/or Utopia at University of Michigan and UC Irvine, and Surviving the Interface at Parsons School of Design.

n 1953, at the dawn of modern computing, Nils Aall Barricelli played God. Clutching a deck of playing cards in one hand and a stack of punched cards in the other, Barricelli hovered over one of the world’s earliest and most influential computers, the IAS machine, at the Institute for Advanced Study in Princeton, New Jersey. During the day the computer was used to make weather forecasting calculations; at night it was commandeered by the Los Alamos group to calculate ballistics for nuclear weaponry. Barricelli, a maverick mathematician, part Italian and part Norwegian, had finagled time on the computer to model the origins and evolution of life.

Inside a simple red brick building at the northern corner of the Institute’s wooded wilds, Barricelli ran models of evolution on a digital computer. His artificial universes, which he fed with numbers drawn from shuffled playing cards, teemed with creatures of code—morphing, mutating, melting, maintaining. He created laws that determined, independent of any foreknowledge on his part, which assemblages of binary digits lived, which died, and which adapted. As he put it in a 1961 paper, in which he speculated on the prospects and conditions for life on other planets, “The author has developed numerical organisms, with properties startlingly similar to living organisms, in the memory of a high speed computer.” For these coded critters, Barricelli became a maker of worlds.

Until his death in 1993, Barricelli floated between biological and mathematical sciences, questioning doctrine, not quite fitting in. “He was a brilliant, eccentric genius,” says George Dyson, the historian of technology and author of Darwin Among The Machines and Turing’s Cathedral, which feature Barricelli’s work. “And the thing about geniuses is that they just see things clearly that other people don’t see.”

Barricelli programmed some of the earliest computer algorithms that resemble real-life processes: a subdivision of what we now call “artificial life,” which seeks to simulate living systems—evolution, adaptation, ecology—in computers. Barricelli presented a bold challenge to the standard Darwinian model of evolution by competition by demonstrating that organisms evolved by symbiosis and cooperation.

Pixar cofounder Alvy Ray Smith says Barricelli influenced his earliest thinking about the possibilities for computer animation.

In fact, Barricelli’s projects anticipated many current avenues of research, including cellular automata, computer programs involving grids of numbers paired with local rules that can produce complicated, unpredictable behavior. His models bear striking resemblance to the one-dimensional cellular automata—life-like lattices of numerical patterns—championed by Stephen Wolfram, whose search tool Wolfram Alpha helps power the brain of Siri on the iPhone. Nonconformist biologist Craig Venter, in defending his creation of a cell with a synthetic genome—“the first self-replicating species we’ve had on the planet whose parent is a computer”—echoes Barricelli.

Barricelli’s experiments had an aesthetic side, too. Uncommonly for the time, he converted the digital 1s and 0s of the computer’s stored memory into pictorial images. Those images, and the ideas behind them, would influence computer animators in generations to come. Pixar cofounder Alvy Ray Smith, for instance, says Barricelli stirred his earliest thinking about the possibilities for computer animation, and beyond that, his philosophical muse. “What we’re really talking about here is the notion that living things are computations,” he says. “Look at how the planet works and it sure does look like a computation.”

Despite Barricelli’s pioneering experiments, barely anyone remembers him. “I have not heard of him to tell you the truth,” says Mark Bedau, professor of humanities and philosophy at Reed College and editor of the journal Artificial Life. “I probably know more about the history than most in the field and I’m not aware of him.”

Barricelli was an anomaly, a mutation in the intellectual zeitgeist, an unsung hero who has mostly languished in obscurity for the past half century. “People weren’t ready for him,” Dyson says. That a progenitor has not received much acknowledgment is a failing not unique to science. Visionaries often arrive before their time. Barricelli charted a course for the digital revolution, and history has been catching up ever since.

Barricelli_BREAKER-02 EVOLUTION BY THE NUMBERS: Barricelli converted his computer tallies of 1s and 0s into images. In this 1953 Barricelli print, explains NYU associate professor Alexander Galloway, the chaotic center represents mutation and disorganization. The more symmetrical fields toward the margins depict Barricelli’s evolved numerical organisms.From the Shelby White and Leon Levy Archives Center, Institute for Advanced Study, Princeton. Barricelli was born in Rome on Jan. 24, 1912. According to Richard Goodman, a retired microbiologist who met and befriended the mathematician in the 1960s, Barricelli claimed to have invented calculus before his tenth birthday. When the young boy showed the math to his father, he learned that Newton and Leibniz had preempted him by centuries. While a student at the University of Rome, Barricelli studied mathematics and physics under Enrico Fermi, a pioneer of quantum theory and nuclear physics. A couple of years after graduating in 1936, he immigrated to Norway with his recently divorced mother and younger sister.

As World War II raged, Barricelli studied. An uncompromising oddball who teetered between madcap and mastermind, Barricelli had a habit of exclaiming “Absolut!” when he agreed with someone, or “Scandaloos!” when he found something disagreeable. His accent was infused with Scandinavian and Romantic pronunciations, making it occasionally challenging for colleagues to understand him. Goodman recalls one of his colleagues at the University of California, Los Angeles who just happened to be reading Barricelli’s papers “when the mathematician himself barged in and, without ceremony, began rattling off a stream of technical information about his work on phage genetics,” a science that studies gene mutation, replication, and expression through model viruses. Goodman’s colleague understood only fragments of the speech, but realized it pertained to what he had been reading.

“Are you familiar with the work of Nils Barricelli?” he asked.

“Barricelli! That’s me!” the mathematician cried.

Notwithstanding having submitted a 500-page dissertation on the statistical analysis of climate variation in 1946, Barricelli never completed his Ph.D. Recalling the scene in the movie Amadeus in which the Emperor of Austria commends Mozart’s performance, save for there being “too many notes,” Barricelli’s thesis committee directed him to slash the paper to a tenth of the size, or else it would not accept the work. Rather than capitulate, Barricelli forfeited the degree.

Barricelli began modeling biological phenomena on paper, but his calculations were slow and limited. He applied to study in the United States as a Fulbright fellow, where he could work with the IAS machine. As he wrote on his original travel grant submission in 1951, he sought “to perform numerical experiments by means of great calculating machines,” in order to clarify, through mathematics, “the first stages of evolution of a species.” He also wished to mingle with great minds—“to communicate with American statisticians and evolution-theorists.” By then he had published papers on statistics and genetics, and had taught Einstein’s theory of relativity. In his application photo, he sports a pyramidal moustache, hair brushed to the back of his elliptic head, and hooded, downturned eyes. At the time of his application, he was a 39-year-old assistant professor at the University of Oslo.

Although the program initially rejected him due to a visa issue, in early 1953 Barricelli arrived at the Institute for Advanced Study as a visiting member. “I hope that you will be finding Mr. Baricelli [sic] an interesting person to talk with,” wrote Ragnar Frisch, a colleague of Barricelli’s who would later win the first Nobel Prize in Economics, in a letter to John von Neumann, a mathematician at IAS, who helped devise the institute’s groundbreaking computer. “He is not very systematic always in his exposition,” Frisch continued, “but he does have interesting ideas.”

Barricelli_BREAKER_2crop PSYCHEDELIC BARRICELLI: In this recreation of a Barricelli experiment, NYU associate professor Alexander Galloway has added color to show the gene groups more clearly. Each swatch of color signals a different organism. Borders between the color fields represent turbulence as genes bounce off and meld with others, symbolizing Barricelli’s symbiogenesis.Courtesy Alexander Galloway Centered above Barricelli’s first computer logbook entry at the Institute for Advanced Study, in handwritten pencil script dated March 3, 1953, is the title “Symbiogenesis problem.” This was his theory of proto-genes, virus-like organisms that teamed up to become complex organisms: first chromosomes, then cellular organs, onward to cellular organisms and, ultimately, other species. Like parasites seeking a host, these proto-genes joined together, according to Barricelli, and through their mutual aid and dependency, originated life as we know it.

Standard neo-Darwinian doctrine maintained that natural selection was the main means by which species formed. Slight variations and mutations in genes combined with competition led to gradual evolutionary change. But Barricelli disagreed. He pictured nimbler genes acting as a collective, cooperative society working together toward becoming species. Darwin’s theory, he concluded, was inadequate. “This theory does not answer our question,” he wrote in 1954, “it does not say why living organisms exist.”

Barricelli coded his numerical organisms on the IAS machine in order to prove his case. “It is very easy to fabricate or simply define entities with the ability to reproduce themselves, e.g., within the realm of arithmetic,” he wrote.

The early computer looked sort of like a mix between a loom and an internal combustion engine. Lining the middle region were 40 Williams cathode ray tubes, which served as the machine’s memory. Within each tube, a beam of electrons (the cathode ray) bombarded one end, creating a 32-by-32 grid of points, each consisting of a slight variation in electrical charge. There were five kilobytes of memory total stored in the machine. Not much by today’s standards, but back then it was an arsenal.

Barricelli saw his computer organisms as a blueprint of life—on this planet and any others.

Inside the device, Barricelli programmed steadily mutable worlds each with rows of 512 “genes,” represented by integers ranging from negative to positive 18. As the computer cycled through hundreds and thousands of generations, persistent groupings of genes would emerge, which Barricelli deemed organisms. The trick was to tweak his manmade laws of nature—“norms,” as he called them—which governed the universe and its entities just so. He had to maintain these ecosystems on the brink of pandemonium and stasis. Too much chaos and his beasts would unravel into a disorganized shamble; too little and they would homogenize. The sweet spot in the middle, however, sustained life-like processes.

Barricelli’s balancing act was not always easygoing. His first trials were riddled with pests: primitive, often single numeric genes invaded the space and gobbled their neighbors. Typically, he was only able to witness a couple of hereditary changes, or a handful at best, before the world unwound. To create lasting evolutionary processes, he needed to handicap these pests’ ability to rapidly reproduce. By the time he returned to the Institute in 1954 to begin a second round of experiments, Barricelli made some critical changes. First, he capped the proliferation of the pests to once per generation. That constraint allowed his numerical organisms enough leeway to outpace the pests. Second, he began employing different norms to different sections of his universes. That forced his numerical organisms always to adapt.

Even in the earlier universes, Barricelli realized that mutation and natural selection alone were insufficient to account for the genesis of species. In fact, most single mutations were harmful. “The majority of the new varieties which have shown the ability to expand are a result of crossing-phenomena and not of mutations, although mutations (especially injurious mutations) have been much more frequent than hereditary changes by crossing in the experiments performed,” he wrote.

When an organism became maximally fit for an environment, the slightest variation would only weaken it. In such cases, it took at least two modifications, effected by a cross-fertilization, to give the numerical organism any chance of improvement. This indicated to Barricelli that symbioses, gene crossing, and “a primitive form of sexual reproduction,” were essential to the emergence of life.

“Barricelli immediately figured out that random mutation wasn’t the important thing; in his first experiment he figured out that the important thing was recombination and sex,” Dyson says. “He figured out right away what took other people much longer to figure out.” Indeed, Barricelli’s theory of symbiogenesis can be seen as anticipating the work of independent-thinking biologist Lynn Margulis, who in the 1960s showed that it was not necessarily genetic mutations over generations, but symbiosis, notably of bacteria, that produced new cell lineages.

Barricelli saw his computer organisms as a blueprint of life—on this planet and any others. “The question whether one type of symbio-organism is developed in the memory of a digital computer while another type is developed in a chemical laboratory or by a natural process on some planet or satellite does not add anything fundamental to this difference,” he wrote. A month after Barricelli began his experiments on the IAS machine, Crick and Watson announced the shape of DNA as a double helix. But learning about the shape of biological life didn’t put a dent in Barricelli’s conviction that he had captured the mechanics of life on a computer. Let Watson and Crick call DNA a double helix. Barricelli called it “molecule-shaped numbers.”

Barricelli_BREAKER

What buried Barricelli in obscurity is something of a mystery. “Being uncompromising in his opinions and not a team player,” says Dyson, no doubt led to Barricelli’s “isolation from the academic mainstream.” Dyson also suspects Barricelli and the indomitable Hungarian mathematician von Neumann, an influential leader at the Institute of Advanced Study, didn’t hit it off. Von Neumann appears to have ignored Barricelli. “That was sort of fatal because everybody looked to von Neumann as the grandfather of self-replicating machines.”

Ever so slowly, though, Barricelli is gaining recognition. That stems in part from another of Barricelli’s remarkable developments; certainly one of his most beautiful. He didn’t rest with creating a universe of numerical organisms, he converted his organisms into images. His computer tallies of 1s and 0s would then self-organize into visual grids of exquisite variety and texture. According to Alexander Galloway, associate professor in the department of media, culture, and communication at New York University, a finished Barricelli “image yielded a snapshot of evolutionary time.”

When Barricelli printed sections of his digitized universes, they were dazzling. To modern eyes they might look like satellite imagery of an alien geography: chaotic oceans, stratigraphic outcrops, and the contours of a single stream running down the center fold, fanning into a delta at the patchwork’s bottom. “Somebody needs to do a museum show and show this stuff because they’re outrageous,” Galloway says.

Barricelli was an uncompromising oddball who teetered between madcap and mastermind.

Today, Galloway, a member of Barricelli’s small but growing cadre of boosters, has recreated the images. Following methods described by Barricelli in one of his papers, Galloway has coded an applet using the computer language Processing to revive Barricelli’s numerical organisms—with slight variation. While Barricelli encoded his numbers as eight-unit-long proto-pixels, Galloway condensed each to a single color-coded cell. By collapsing each number into a single pixel, Galloway has been able to fit eight times as many generations in the frame. These revitalized mosaics look like psychedelic cross-sections of the fossil record. Each swatch of color represents an organism, and when one color field bumps up against another one, that’s where cross-fertilization takes place.

“You can see these kinds of points of turbulence where the one color meets another color,” Galloway says, showing off the images on a computer in his office. “That’s a point where a number would be—or a gene would be—sort of jumping from one organism to another.” Here, in other words, is artificial life—Barricelli’s symbiogenesis—frozen in amber. And cyan and lavender and teal and lime and fuchsia.

Galloway is not the only one to be struck by the beauty of Barricelli’s computer-generated digital images. As a doctoral student, Pixar cofounder Smith became familiar with Barricelli’s work while researching the history of cellular automata for his dissertation. When he came across Barricelli’s prints he was astonished. “It was remarkable to me that with such crude computing facilities in the early 50s, he was able to be making pictures,” Smith says. “I guess in a sense you can say that Barricelli got me thinking about computer animation before I thought about computer animation. I never thought about it that way, but that’s essentially what it was.”

Cyberspace now swells with Barricelli’s progeny. Self-replicating strings of arithmetic live out their days in the digital wilds, increasingly independent of our tampering. The fittest bits survive and propagate. Researchers continue to model reduced, pared-down versions of life artificially, while the real world bursts with Boolean beings. Scientists like Venter conjure synthetic organisms, assisted by computer design. Swarms of autonomous codes thrive, expire, evolve, and mutate underneath our fingertips daily. “All kinds of self-reproducing codes are out there doing things,” Dyson says. In our digital lives, we are immersed in Barricelli’s world.

Cellular Forms uses a simplified model of cellular growth to create intricate sculptural shape. Structures are created out of interconnected cells, with rules for the forces between cells, as well as rules for how cells accumulate internal nutrients. When the nutrient level in a cell exceeds a given threshold the cell splits into two, with both the parent and daughter cells reconnecting to their immediate neighbours. Many different complex organic structures are seen to arise from subtle variations on these rules, creating forms with strong reminiscences of plants, corals, internal organs and micro-organisms. The aim is to create structures emergently: exploring generic similarities between many different forms in nature rather than recreating any particular organism, in the process exploring universal archetypal forms that can come from growth processes rather than top-down externally engineered design. For other videos of my work take a look at my channel: vimeo.com/channels/andylomas

For medical researchers and biochemists, simulation software will vastly speed the early stages of screening for new compounds. And for molecular biologists, models that are of sufficient accuracy will yield new understanding of basic cellular principles.

This kind of modeling is already in use to study individual cellular processes like metabolism. But Dr. Covert said: “Where I think our work is different is that we explicitly include all of the genes and every known gene function. There’s no one else out there who has been able to include more than a handful of functions or more than, say, one-third of the genes.”

The simulation of the complete life cycle of the pathogen, Mycoplasma genitalium, was presented on Friday in the journal Cell. The scientists called it a “first draft” but added that the effort was the first time an entire organism had been modeled in such detail — in this case, all of its 525 genes.

In my last 3quarksdaily article I considered the ability of science-fiction – and the impossible objects it contains – to highlight the gap between us and ‘The Thing Itself’ (the fundamental reality underlying all phenomena). In this follow-up I ask whether the way these fictional ‘Things’ determine their continued existence – by copying, cloning or imitation – can teach us about our conception of nature.

Seth Brundle: What's there to take? The disease has just revealed its purpose. We don't have to worry about contagion anymore... I know what the disease wants.

Ronnie: What does the disease want?

Seth Brundle: It wants to... turn me into something else. That's not too terrible is it? Most people would give anything to be turned into something else.

Ronnie: Turned into what?

Seth Brundle: Whaddaya think? A fly. Am I becoming a hundred-and-eighty-five-pound fly? No, I'm becoming something that never existed before. I'm becoming... Brundlefly. Don't you think that's worth a Nobel Prize or two?

The Fly, 1986

In David Cronenberg’s movie The Fly (1986) we watch through slotted fingers as the body of Seth Brundle is horrifically transformed. Piece by piece Seth becomes Brundlefly: a genetic monster, fused together in a teleportation experiment gone awry. In one tele-pod steps Seth, accompanied by an unwelcome house-fly; from the other pod emerges a single Thing born of their two genetic identities. The computer algorithm designed to deconstruct and reconstruct biology as pure matter cannot distinguish between one entity and another. The parable, as Cronenberg draws it, is simple: if all the world is code then ‘all the world’ is all there is.

Science fiction is full of liminal beings. Creatures caught in the phase between animal and human, between alien and Earthly, between the material and the spirit. Flowing directly from the patterns of myth Brundlefly is a modern day Minotaur: a manifestation of our deep yearning to coalesce with natural forces we can’t understand. The searing passions of the bull, its towering stature, are fused in the figure of the Minotaur with those of man. The resultant creature is too fearsome for this world, too Earthly to exist in the other, and so is forced to wander through a labyrinth hovering impossibly between the two. Perhaps Brundlefly’s labyrinth is the computer algorithm winding its path through his genetic code. As a liminal being, Brundlefly is capable of understanding both worlds from a sacred position, between realities. His goal is reached, but at a cost too great for an Earthly being to understand. Seth the scientist sacrifices himself and there is no Ariadne’s thread to lead him back.

In her book on monsters, aliens and Others Elaine L. Graham reminds us of the thresholds these ‘Things’ linger on:

“[H]uman imagination, by giving birth to fantastic, monstrous and alien figures, has… always eschewed the fiction of fixed species. Hybrids and monsters are the vehicles through which it is possible to understand the fabricated character of all things, by virtue of the boundaries they cross and the limits they unsettle.”

Elaine L. Graham, Representations of the Post/Human

Hybrids such as the Minotaur or Brundlefly are meeting points for disparate categories of representation. They symbolise the tragic limits of human perception. Unable to grasp the world in and of Itself (nature) we colonise it with ever more fabricated representations and imitations (culture) which only result in distancing us yet further from The Thing Itself. One such category of fabrication, a favourite in science fiction, is ‘code’. Brundlefly is a Thing caught on the threshold between, what in geek-terminology we might call, wetware and software. Cronenberg’s parable plays into the hands of every techno-fearing luddite: a monster born from our desire to reduce nature to science; to simplify lumpy, oozing, unpredictable flesh in the patterns of an efficient genetic code.

We are all the tragic Brundefly because whilst we see beauty and endless creative potential in the natural world around us, we find it impossible to quantify those same categories in the reductive models we have devised to describe them. To describe nature, whether genetic codes unwinding or bees busying around their nest, we gasp at its “creativity”, ascribing its endless variation a human-like attention to detail. But as Richard Dawkins alludes to below, the most creative force in nature is the absolute opposite of perfection: it is in fact error. The world that science has modelled for us is a world riddled with mistakes, failures and run away coding errors. In order to ‘create’ nature must, as Alexander Pope said of the human, err:

“Think about the two qualities that a virus, or any sort of parasitic replicator, demands of a friendly medium, the two qualities that make cellular machinery so friendly towards parasitic DNA, and that make computers so friendly towards computer viruses. These qualities are, firstly, a readiness to replicate information accurately, perhaps with some mistakes that are subsequently reproduced accurately; and, secondly, a readiness to obey instructions encoded in the information so replicated.”

Richard Dawkins, Viruses of the Mind

It is beneficial for life that errors exist and are propagated by biological systems. Too many copying errors and all biological processes would be cancerous, mutating towards oblivion. Too much error management (redundancy) and biological change, and thus evolution, could never occur.

Simply put, exchange within and between natural systems has no value unless change, and thus error, is possible within the system. What science fiction allows us to do is peek into a world where nature’s love for error is switched off, or allowed to run rampant. What would be the consequence of a truly ‘perfect’ natural process, devoid of error? In John Carpenter’s The Thing we see the result of such a process: a nature perfect by our standards, but terrible in its consequences.

Blair: You see, what we're talking about here, is an organism that imitates other life forms, and it imitates them perfectly. When this thing attacked our dogs, it tried to digest them, absorb them, and in the process shape its own cells to imitate them. This, for instance...That's not dog, it's imitation. We got to it before it had time to finish.

Norris: Finish what?

Blair: Finish imitating these dogs.

The Thing, 1982

John Carpenter's The Thing (1982) is a claustrophobic sci-fi masterpiece, containing all the hallmarks of a great horror film. As in The Fly, the film depicts a sinister turn for the body, where the chaos of the replicating, cancerous cell is expanded to the human scale and beyond. In The Thing we watch as an alien force terrorises an isolated Antarctic outpost. The creature exhibits the awesome ability to imitate its host, devouring any creature (or human) it comes across before giving birth to an exact copy in a burst of blood and protoplasm. The Thing copies cell by cell and its process is so perfect - at every level of replication - that the resultant simulacrum speaks, acts and even thinks like the original. The Thing is so relentless, its copies so perfect, that the outpost's Doctor is sent mad at the implications:

Blair: If a cell gets out it could imitate everything on the face of the earth... and it's not gonna stop!!!

In The Thing it is we, the human race, who are trapped between realities. A twist in the truth that highlights our own liminal nature. If, as Dawkins suggests, evolution is about the imperfect copy, then, like the tragic Brundlefly, or the towering figure of the Minotaur, the characters in The Thing are torn between two equally horrifying worlds. In one, the alien Thing aims for perfection, cloning its hosts cell by cell until, like The Ship of Argo, an entirely new, but identical world remains. In the other, the beauty of nature, in all its intricacy, is the result of a billion years of ugly mutation. 

Which process is closest to the truth? Which result is more hideous? I have not the authority to say. In science fiction every improbable event is balanced by the existence of an equally improbable reality. The Thing Itself, the world beneath phenomenon, and the Things that inhabit it, have always been impossible to comprehend. Where science fiction takes us, kicking and screaming, is right back to the real world, our knuckles a little whiter from the journey.

by Daniel Rourke

If you enjoyed this essay, you may also like:

• 'The Thing Itself' : A Sci-fi Archaeology
• Ranciere's Ignoramus
• A Diatribe from the Remains of Dr. Fred McCabe
• Inside Code: A Conversation...
• Communicating the Body \ Interpreting the Code
• Speaking About Ants, Superman and Centaurs

Jacques Rancière prepares for us a parable. A student who is illiterate, after living a fulfilled life without text, one day decides to teach herself to read. Luckily she knows a single poem by heart and procures a copy of that poem, presumably from a trusted source, by which to work. By comparing her knowledge, sign by sign, word by word, with the poem she can, Rancière believes, finally piece together a foundational understanding of her language: “From this ignoramus, spelling out signs, to the scientist who constructs hypotheses, the same intelligence is always at work – an intelligence that translates signs into other signs and proceeds by comparisons and illustrations in order to communicate its intellectual adventures and understand what another intelligence is endeavoring to communicate to it. This poetic labour of translation is at the heart of all learning.” The Emancipated Spectator (2008)

What interests me in Rancière’s example is not so much the act of translation as the possibility of mis-translation. Taken in light of The Ignorant Schoolmaster we can assume that Rancière is aware of the wide gap that exists between knowing something and knowing enough about something for it to be valuable. But what distinction can we uncover between the ‘true’ and the ‘false’, hell, even between the ‘true’ and ‘almost true’? How does one calculate the value of what is effectively a mistake? Error appears to be a crucial component of Rancière’s position. In a sense, Rancière is positing a world that has from first principles always uncovered itself through a kind of decoding. A world in which subjects “translate signs into other signs and proceed by comparison and illustration”. Now forgive me for side-stepping a little here, but doesn’t that sound an awful lot like biological development? Here’s a paragraph from Richard Dawkins (worth his salt as long as he is talking about biology): “Think about the two qualities that a virus, or any sort of parasitic replicator, demands of a friendly medium, the two qualities that make cellular machinery so friendly towards parasitic DNA, and that make computers so friendly towards computer viruses. These qualities are, firstly, a readiness to replicate information accurately, perhaps with some mistakes that are subsequently reproduced accurately; and, secondly, a readiness to obey instructions encoded in the information so replicated.” Viruses of the Mind (1993)

Hidden amongst Dawkins’ words, I believe, we find an interesting answer to the problem of mis-translation I pose above. A mistake is useless if accuracy is your aim, but what if your aim is merely to learn something? To enrich and expand the connections that exist between your systems of knowledge. As Dawkins alludes to above, it is beneficial for life that errors do exist and are propagated by biological systems. Too many copying errors and all biological processes would be cancerous, mutating towards oblivion. Too much error management (what in information theory would be metered by a coded ‘redundancy‘) and biological change, and thus evolution, could never occur. Simply put, exchange within and between systems is almost valueless unless change, and thus error, is possible within the system. At the scale Rancière exposes for us there are two types of value: firstly, the value of repeating the message (the poem) and secondly, the value of making an error and thus producing entirely new knowledge. In information theory the value of a message is calculated by the amount of work saved on the part of the receiver. That is, if the receiver were to attempt to create that exact message, entirely from scratch. In his influential essay, Encoding, Decoding (1980), Stuart Hall maps a four-stage theory of “linked but distinctive moments” in the circuit of communication:

production circulation use (consumption) reproduction

John Corner further elaborates on these definitions:

the moment of encoding: ‘the institutional practices and organizational conditions and practices of production’; the moment of the text: ‘the… symbolic construction, arrangement and perhaps performance… The form and content of what is published or broadcast’; and the moment of decoding: ‘the moment of reception [or] consumption… by… the reader/hearer/viewer’ which is regarded by most theorists as ‘closer to a form of “construction”‘ than to ‘the passivity… suggested by the term “reception”‘

(source) At each ‘moment’ a new set of limits and possibilities arises. This means that the way a message is coded/decoded is not the only controlling factor in its reception. The intended message I produce, for instance, could be circulated against those intentions, or consumed in a way I never imagined it would be. What’s more, at each stage there emerges the possibility for the message to be replicated incorrectly, or, even more profoundly, for a completely different component of the message to be taken as its defining principle. Let’s say I write a letter, intending to send it to my newly literate, ignoramus friend. The letter contains a recipe for a cake I have recently baked. For some reason my letter is intercepted by the CIA,who are convinced that the recipe is a cleverly coded message for building a bomb. At this stage in the communication cycle the possibility for mis-translation to occur is high. Stuart Hall would claim is that this shows how messages are determined by the social and institutional power-relations via which they are encoded and then made to circulate. Any cake recipe can be a bomb recipe if pushed into the ‘correct’ relationships. Every ignoramus, if they have the right teacher, can develop knowledge that effectively lies beyond the teacher’s. What it is crucial to understand is that work is done at each “moment” of the message. As John Corner states, decoding is constructive: the CIA make the message just as readily as I did when I wrote and sent it. These examples are crude, no doubt, but they set up a way to think about exchange (communication and information) through its relationships, rather than through its mediums and methods. The problem here that requires further examination is thus: What is ‘value’ and how does one define it within a relational model of exchange? Like biological evolution, information theory is devoid of intentionality. Life prospers in error, in noise and mistakes. Perhaps, as I am coming to believe, if we want to maximise the potential of art, of writing and other systems of exchange, we first need to determine their inherent redundancy. Or, more profoundly, to devise ways to maximise or even increase that redundancy. To determine art’s redundancy, and then, like Rancière’s ignoramus, for new knowledge to emerge through mis-translation and mis-relation.