Black Computing: On Beth Coleman and Octavia Butler AI

LIBERATION PROJECT

by Beth Coleman

7

THE GENERATIVE CONDITION: ON AI, ALIEN LOVE, AND WILD THINGS Beth Coleman in conversation with Etienne Turpin

9

Alice

31

Oceanic

41

WITH AND AGAINST: CONSPIRING WITH ALIENS TOWARDS POSSIBLE WORLDS

by M. Murphy BLACK COMPUTING: ON BETH COLEMAN AND OCTAVIA BUTLER AI

by Mitch McEwen

59

77

WHAT IS TEMPORAL RELATIONALISM? THE PHILOSOPHY OF THE FUTURE

by Lee Smolin

91

Doppelganger

97

hummmm hummmm hummmm

by JJJJJerome Ellis

106 BPP

Contributors & Bibliographic Note

117 132

08

BLACK COMPUTING: ON BETH COLEMAN AND OCTAVIA BUTLER AI

81

by Mitch McEwen I looked back at the brick building of the Historical Society, itself a converted early mansion. “If we told anyone else about this, anyone at all, they wouldn’t think we were so sane.’’

— Octavia Butler, Kindred

The images produced by Beth Coleman for Reality was Whatever Happened: Octavia Butler AI and Other Possible Worlds point toward a new potential for the aesthetics of the Black Radical Tradition to engage with the opacity of the Black Box in Machine Learning. To address this work, I will consider the work both as a set of images and as computational processes. What most interests me is how the model that produces the OBAI images stages a speculative black mode of artificial intelligence.

I am entering a dialogue with this work not as a computer scientist or art critic, but as a designer. I practice design of the built environment, primarily architecture and urban design, sometimes through exhibitions, software, and robotics. In the built environment, contemporary ethics raises questions of climate change, industrial pollution, gentrification, unceded land claims, and more. To think transformation of the built environment along these ethical dimensions demands engagement with extensive datasets and intersecting realms of spatial change. The fields of architecture, landscape

Mitch McEwen

82

architecture, and urban planning could gain immensely from a decolonial approach to automated intelligence. With OBAI as a guide, I will call this approach one of black computing.

Blackness and racial data arguably invented the need for computing. I am thinking of the Hollerith Machine, which used holes in census forms to tabulate data of race and gender and place in the United States at the end of the nineteenth century.1 Yet, there are few examples of research 1 Special thanks to Womack for projects in Machine Learning that deploy black- Autumn introducing me to this ness or racial difference in a generative way. Here technological history; see census.gov/history I mean artificial intelligence and machine learning /www/innovations specifically, not computation broadly speaking. This /technology/the _hollerith_tabulator.html. is distinct from the important and critical research highlighting the perpetuation of racial and racist frameworks in the midst of supposedly unbiased technology—whether facial recognition, policing, or otherwise. As an architectural designer, I find the presumed whiteness of AI to be deeply troubling, since AI increasingly participates in the design of our environment at every scale.

Black computing, 2022; courtesy of the author.

architecture, must generate other computable possibilities.

“Black is beautiful” is an instruction at this level, a protocol, a program unfurled into the realm of cultural production and also consciousness. It is a programming path of black computing as basic and repetitively active as “Hello, World” programs that circulate with programming languages as the default introduction and demonstration to the nexus of language and platform.

Black computing, if it had a history, would be a history of messing with social data. I turn here to Autumn Womack’s understanding of black life resisting and exceeding the sociological. Womack’s book, The Matter of Black Living: The Aesthetic Experiment of Racial Data, 1880–1930, presents the notion of un-disciplining racial data. She studies the technological entanglement of black life with and against and outside of quantification. Thus, according to Womack’s analysis, even the pre-eminent sociologist W.E.B. Du Bois pulls the social scientific into collusive praxis with the literary, poetic, and fictitious in the midst of its urban surveying and measuring. Reading early-twentieth-century social surveys as a form of data technology co-invented with literary aesthetics and black life, Womack studies the technological entanglement of black life with and against and outside of quantification. The technologies of visual data production yield “over-exposure” and “black space” in the unmappability of black life to data regimes. Our life does not just exceed the frame. Our life breaks the machine.

Our life over-exposes the fissures and makes more black life, more protocols of black as beautiful.

83

Let us presume that black computing not only exists as technique and aesthetic and method, but that it has a history that precedes what we usually call computer science. Black computing, as a mode of algorithmic processing and data

Black Computing: on Beth Coleman and Octavia Butler AI

Mitch McEwen

84

the psilocybinic aesthetic of over-exposure In the artificial intelligent media of Beth Coleman, the overexposure of black incomputability begets the psychedelic saturation of black computing. It is not an accident that the aesthetics of black computing evoke the psychedelic. That the work of Beth Coleman’s OBAI series gestures toward the psychedelic is not a throw-back to the 1960s or 1970s—that is, to a time period of black power as a political rubric and popular cultural production adjacent to psychedelia. Rather, black computing aligns itself with psychedelia at the level of consciousness and networks.

Psychedelics—or, more specifically psilocybin— activate brain activities outside the default mode network of consciousness. I am relating Coleman’s work specifically to psilocybin because these are the active psychedelic component of so-called magic mushrooms. The mycelium.

Psilocybin, like the rhizomatic fungi that generate them, cannot be confined to our defaults. This is true at the level of the brain.2 I want to linger on the psychedelic 2 Merlin Sheldrake, Life: How reading of black computing while also attending to Entangled Fungi Make Our Worlds, Change Our Minds, the level of experience. and Shape Our Futures How psilocybin operates as the psyche- (London: Random delic—resistant to rational explanation—echoes House, 2020), 110. the fugitivity of black life. Does it echo, or are these the same synesthetic soundings? Indeed, the trippy colors of the psychedelic—bright pinks and purples, bleached out forms—might be read as a remapping, recoloring of landscape, which is to say the visual recognition of lifeforms and their interrelationships. What we read in the history of painting or landscape architecture—two fields that were one discipline until as recently as the late nineteenth century—as landscape, that is, green for grass, a horizon line for the sky meeting the land, instantiates a colonial geography onto our imagination of the planet. The agricultural and feudal geographies of Western Europe appear over and over in this thick green band. Not sand, nor the ocean and its depths. Yet, if you ask a climate scientist to

Black Computing: on Beth Coleman and Octavia Butler AI

pick a zone of the planet that can stand in as a model for the entire earth’s atmosphere, she will point to the tropical ocean—the troposphere.

In considering the aesthetic of—I won’t say psychedelic anymore, so as to make space for a visual imaginary other than the popular cultural imagery bounded by the late twentieth century—the psilocybinic as one of black computing, I want to think the over-exposure of black space itself. To return again to to over-exposure: this, too, has a default coloration. The white of over-exposure being the de facto white of photographic paper. We would usually, in a photographic sense, locate over-exposure in a brightening into white. What trippy synesthesia do we figure in the over-exposure of black space? The psilocybinic rendering of black computing emerges in Coleman’s OBAI series as an over-exposure that might rescript the relationship between 3 Autumn Womack, blackness and data.3 While the politics of such a The Matter of Black rescripting might be necessarily opaque, the matter Living: The Aesthetic Experiment of Racial of such relationships between blackness and data Data, 1880–1930 (The generates a tropospheric cosmos of images.

University of Chicago

85

Press, 2022), 221.

Alice Borderland

Mitch McEwen

86

I encounter this aesthetic potential of black computing in the OBAI images, which seem to stage blurs and color bleeds and figural warping that one would easily associate with a human mis/handling of an image or its data or an interruption in its medium, a hiccup or an intervention in fact-making. This is especially true in the Alice series. In Alice Borderland, a figure is wearing a suit and tie in a mostly black and white image, but the head is a black inky mass, blotted and liquid—dense black with crenulated smudged edges. In the BPP landscape series, Liberation School reads as the gray tones of a black and white photograph, save for a central swath of sky blue.

What at the base of the image reads as the aerial view of a crowd of people dissolves at the horizon line to a similarly gray toned array of smudges and splotches, receding in the

Liberation School

Black Computing: on Beth Coleman and Octavia Butler AI

Zooxanthellae

same perspective field as the crowd in the foreground. The series can be understood not so much as collage but is instead more of a warping between photographic image and rhythm, something more sonic than visual, a transition from visual recognition to noise. On closer inspection, the Alice images are not so neatly divided between suit and ink splotch. The shirt of the figure repeats and fades out across the suit lapel, like a cross fade between tracks.

It turns out that OBAI is not staging a “human” intervention in a machinic production of image-making. These are not photos that have been treated with ink or collaged.

Rather, the series generates the work within the realm of computing, machine vision, and the coding of afro-futurism into visual data. Coleman deploys a computing method known as generative adversarial networks (GANs) to create synthetic data—image data—that become the OBAI images.

The series hails Octavia Butler’s Xenogenesis trilogy as inspiration or, perhaps, precedent. The Xenogenesis trilogy

Mitch McEwen

88

crafts a parable of interplanetary and interspecies mingling. We might consider the trilogy in relation to Kindred, Butler’s time travel fiction that melds 1970s Los Angeles with a nineteenth century plantation. We might relate the interspecies mingling of Xenogenesis to the interconnected miscegenations and fantasies of racial purity endemic to plantation economies and their aftermath.

Coleman’s work brings these imaginaries of planetary travel and interspecies mingling—imaginaries which are inevitably thick with racial signification—into her work with computing. Or, should I say she brings computing into her work with interspecies mingling? The form of computing that Coleman deploys to generate the series relies upon randomness pooled within samples of data.4 Working 4 “The generator is an convolutional with GANs also means computing with randomness inverse network, in a sense: as a generative force. Can this generative process While a standard convolutional classifier make GANs a form of black computing? takes an image and it to A method introduced less than a decade downsamples produce a probability, ago, GANs are most well-known for easing the the generator takes a vector of random production of “deep fake” videos (i.e. videos that noise and upsamples to an image. The appear to be recorded by a digital camera, but are itfirst throws away data actually computer generated). There is a long history through downsampling like of image manipulation, such as Photoshop and its techniques maxpooling, and the pre-digital precursors. But a GAN behaves very second generates new data.” Via wiki.pathmind differently from these predecessors. GAN also act .com/generative very differently from image processing software. It -adversarial-network -gan. is not a set of digital editing actions associated with graphics that resemble tools, raising analogies to brushes and scissors. A GAN requires a purpose-built network of data and a means of randomizing that data. It requires two networks with adversarial goals that use Machine Learning.

One network, the Discriminator, uses Machine Learning to assess what hearkens back to the original data set. The creative network, the Generator, deploys Machine Learning and randomized change to generate new versions 5 “[…] the generative model generates of itself.5 samples by passing random noise through a multilayer perceptron […]” See arxiv.org /pdf/1406.2661.pdf.

Black Computing: on Beth Coleman and Octavia Butler AI

generative networks

89

I want to pause here and go back to the Hollerith Machine that I mentioned earlier. The Census Bureau employee Hermann Hollerith invented the machine in response to a Census Bureau competition in 1888. The goal of the competition was to elicit a more efficient means to tabulate data. Could we imagine such urgency to process demographic data without the background of Reconstruction? Could we grasp this need to tabulate without the will of black America making the radical shift from rural property to American citizenry, or what Saidiya Hartmann calls the chorus of wayward lives?

Returning to GANs, the language of Discriminator and Generator is literal but also revelatory in its asocial clarity about the social. The adversarial relationship is productive for both the Discriminator and the Generator. At the level of the model, GAN should not be conflated with discrimination in the sense of societal discrimination. A GAN is not racist because it discriminates one bit of data from another. The technology codifies forms of sifting, binary separations, hierarchies, classification, labeling, and adversity. Yet—and here’s the part I am calling black—the GAN computes by staging a means to adversarially exceed the initial classification— progressing, seemingly undoing, and seemingly progressing.

These procedures are not directly determined by a racist society. Rather, they can give some insight into an algorithm of racial difference (Generator) and racism (Discriminator), and the means by which the two play off each other. What might be undone by not only the random shifting of excellence and exceptionalism or the steady creep of progress—the gradient of momentum and its data egression—but some other ruptures that kick the D and G out of sync?

Perhaps this is a way of inhabiting the afro-pessimism and afro-optimism split synthetically. What other models might be modeled? If “black is beautiful’ operates at the level of a “Hello, world” script introducing black aesthetics, what modes of blackness meet the computational intensity of neural network machine learning? The fact that GANs do not require feedback loops indicates their break from the

Mitch McEwen

90

cybernetic model of organic computing (feedback systems, life propagation, evolutionary models, etc.). The GAN is not African, but black. The system is artificial. It requires time and momentum, not origins and cycles.

Part of the brilliance of OBAI is to deploy Octavia Butler as an interlocutor with this form of AI. The link in GANs between time and what I’m calling black computing finds a ready-made narrator in the science fiction of Octavia Butler. Time shifts, and species struggle to escape each other, but also disrupt the escape with co-mingling. These patterns become an interplanetary cosmology in the Xenogenesis trilogy. We can also map them in Kindred, operating across the layers of history and networks of power that link a twentieth-century apartment in Los Angeles to a colonial plantation in Maryland.

The logic of the GAN does not work with sets as much as gradients. The stochastic movement of facts across the gradient constitutes what computer scientists call momentum. Perhaps we can think these gradient-based updates as opacity, in the sense Glissant gives the term. With OBAI, we may encounter this momentum as an opacity that is not specifically visual, but temporal.6 This temporality 6 Édouard Glissant, of Relation produces black computing when it becomes ad- Poetics [1990], trans. Betsy versarially out of sync, as the Generator generates Wing (Ann Arbor: University of Michigan too fast or too randomly for the Discriminator to Press, 2006). catch on, or (even better) pulls the Discriminator out beyond the realm of what it can afford to calculate. The GAN makes something that it thinks is a stochastic gradient of something else, and we see something black we have never seen before.

Black Computing: on Beth Coleman and Octavia Butler AI

Du Bois!s data precedents

91

We can also read OBAI as participating in the legacy of data portraiture as invented by W.E.B. Du Bois. If one thinks of the “undisciplined data” active in these data portraits, part of what they stage is the momentum of the adversarial nets of black and white worlds.7 The data portraits do 7 On “undisciplined data,” see Womack. not capture a static dataset on a plane of Cartesian coordinates. Rather, most of the data portraits imply a reading in perspective or in motion. They portray data of black life through speculative modes open to perception through time—through implied momentum and mass.

In Du Bois’s series of data portraits, the terms of data production are recursively generative through measurability and its relationship to the plane of the page. The speculative momentum of depth perception does not interrupt the data portrait’s capacity to measure facts in the dimensions of the plane of the page. The measurable plane of the page and the speculative motion of depth through Assessed Valuation of All Taxable Property Owned by Georgia Negroes.

Charted prepared

by W.E.B. Du Bois and collaboration for the “American Negro” Exhibit of the American Section at the Paris Exposition Universelle in 1900.

Ink and watercolor, 710 × 560 mm. Library of Congress Prints and Photographs Division.

Mitch McEwen

92

the plane each gain legibility and opacity from each other.

A data portrait may stage not only a probability dimension through depth perception but also the adversarial dimension—its multilayer perceptron. To do this, a data portrait must stage its own interruption.

“ASSESSED VALUATION OF ALL TAXABLE PROPERTY OWNED BY GEORGIA NEGROES” charts jagged interruptions in the measured rings of surface. It is as if part of what the data needs to denote is even the extent to which the data is generated not only by the living of life but also the erasing or confining or interrupting of life. The adversarial aspect of the data generation interrupts the rings, piercing into the center. What does it mean?

Starting with 1875, the decade appears centered and placed at the bottom edge of the circle that denotes the dollar amount as a surface area. The concentric circle is black and marked 1875. The concentric ordering of the quantities means they can only be read as increasing. The gap from 1890 to 1895 is thin compared to all except 1875 to 1880. Both those time periods are figured close to the tone of the page. The former is the negative space of the page, demarcated by the most outer ring, which appears in red. The dollar amount for each time period also appears as a number, centered within a jaggedly edged triangle that pierces the concentric circles—each one pointed toward the center, each jagged triangle dragging the colors of the outer rings into the black center.

The pessimism here is active. The data is not stable.

It does not “grow” organically. At each period of time, an adversarial dataset might erode this data set. Time itself renders the data unstable to itself, future data eroding into the past, erasing, re-codifying it. In Du Bois’s work, the instability of data in the midst of blackness generates new modes of representation that imply computing.

The OBAI series does something comparable, but at the level of black aesthetics or the recognition of blackness. The stochastic gradient from representations of black imaginaries generate new modes of representation that imply black computing, in the midst of black computing.

Black Computing: on Beth Coleman and Octavia Butler AI

alien ethics

8

93

The ethical dilemmas of AI have reached my field peripherally, through black studies and spatial computing technology (including parametric optimization and robotics). The computational power of parametric modelling and machine learning could, ostensibly, create potential for locally grown materials, crowd-directed construction labor, read-writable building regulations, mutual aid construction networks, and remotely editable buildings. The actual use of the computing tools, however, has generally been the construction of more intricately curvy sports stadia and luxury towers. As activists, such as Who Builds Your Architecture? (WBYA?), have highlighted, high-tech advanced design often means the See whobuilds.org. same low-tech, exploitative construction system.8 But the need for black computing in AI reaches far beyond problem solving. Black computing recognizes that the ambition of AI must always already occur in the midst of human difference and in the midst of black fugitivity. Beth Coleman is thus stewarding black computing into new realms of machinic and alien intelligence; Reality Was Whatever Happened stakes out new methods for black aesthetics to engage with the opacity of the Black Box in Machine Learning.

Because of this, it is important to consider Coleman’s work both as a set of images and as computational processes.

OBAI stages a speculative black mode of artificial intelligence that indicates not only an aesthetics but an ethics. This is because it does not simply represent this contemporary ethics—this alien ethics—but generates an alien ethics. The work does this not in spite of technology—but in the very middle of it.

Mitch McEwen