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Issue #08
Contents
editorial
KOFI AGAWU
African Art Music and the Challenge of Postcolonial Composition
PAUL ZILUNGISELE TEMBE
China’s Effective Anti-Corruption Campaign
DILIP M. MENON
Changing Theory: Thinking Concepts from the Global South
BEN WATSON
Talking about music
Theme AI in Africa
blk banaana
An (Other) Intelligence
VULANE MTHEMBU
Umshini Uyakhuluma (The Machine Speaks) – Africa and the AI Revolution: Exploring the Rapid Development of Artificial Intelligence on the Continent.
OLORI LOLADE SIYONBOLA
A Brief History of Artificial Intelligence in Africa
CHRIS EMEZUE & IYANUOLUWA SHODE
AI and African Languages: Empowering Cultures and Communities
NOLAN OSWALD DENNIS
Toward Misrecognition. | Project notes for a haunting-ting
SLINDILE MTHEMBU
AI and documenting black women's lived experiences: Creating future awareness through AI-generated sonics and interpretive movement for the future of freeing suffering caused on black bodies.
ALEXANDRA STANG
Artificially Correct? How to combat bias and inequality in language use with AI
BAKARY DIARRASSOUBA
Bambara: The Jeli (Griot) Project
ROY BLUMENTHAL
Artificial Intelligence and the Arcane Art of the Prompt
AI GENERATED
"AI on Artificial Intelligence in Africa" and "Exploring its impact on Art and Creativity"
JULIA SCHNEIDER
AI in a biased world
MBANGISO MABASO
Bana Ba Dinaledi: Telling African Stories using Generative AI Art.
ALEX TSADO & BETTY WAIREGI
African AI today
BOBBY SHABANGU
Using Artificial Intelligence to expand coverage of African content on Wikipedia
DARRYL ACCONE
Welcome to The End of Beauty: AI Rips the Soul Out of Chess
VULANE MTHEMBU & ChatGPT
Hello ChatGPT - A conversation with OpenAI's Assistant
DIMITRI VOUDOURIS
Evolution of Sιήκ
STEFANIE KASTNER
Beyond the fact that most robots are white: Challenges of AI in Africa
MARTIJN PANTLIN
Some notes from herri’s full stack web developer on the AI phenomenon
galleri
THANDIWE MURIU
4 Universal Truths and selected Camo
ZENZI MDA
Four Portals
TIISETSO CLIFFORD MPHUTHI
Litema
NESA FRÖHLICH
Agapanthus artificialis: Biodiversität im digitalen Raum. Vierteilige Serie, Johannesburg 2022.
STEVEN J FOWLER
2 AI collaborations and 9 asemic scribbles
PATRICIA ANN REPAR
Integrating Healing Arts and Health Care
SHERRY MILNER
Fetus & Host
borborygmus
JANNIKE BERGH
BCUC = BANTU CONTINUA UHURU CONSCIOUSNESS
GWEN ANSELL
Jill Richards: Try, try, try...
VULANE MTHEMBU & HEIKKI SOINI
Nguni Machina remixed
AFRICAN NOISE FOUNDATION
Perennial fashion – noise (After Adorno).
RAJAT NEOGY
Do Magazines Culture?
NDUMISO MDAYI
Biko and the Hegelian dialectic
LEHLOHONOLO MAKHELE
The Big Other
frictions
KHAHLISO MATELA
At Virtue’s Zone
DIANA FERRUS
In memory of “Lily” who will never be nameless again
VUYOKAZI NGEMNTU
Six Poems from the Shadows
SIHLE NTULI
3 Durban Poems
SIBONELO SOLWAZI KA NDLOVU
I’m Writing You A Letter You Will Never read
OMOSEYE BOLAJI
People of the Townships episode 3
claque
SIMON GIKANDI
Introducing Pelong Ya Ka (excerpt)
UNATHI SLASHA
"TO WALK IS TO SEE": Looking Inside the Heart - Sophonia Machabe Mofokeng’s Pelong ya Ka
VANGILE GANTSHO
Ilifa lothando – a Review of Ilifa by Athambile Masola
ZIZIPHO BAM
Barbara Boswell found in The Art of Waiting for Tales
WAMUWI MBAO
Hauntings: the public appearance of what is hidden
CHARL-PIERRE NAUDÉ
Dekonstruksie as gebundelde terrorisme
VUYOKAZI NGEMNTU
Ibuzwa Kwabaphambili - A Review
MPHUTLANE WA BOFELO
Taking radical optimism beyond hope - Amakomiti: Grassroots Democracy in South Africa’s Shack Settlements
PATRIC TARIQ MELLET
WHITE MISCHIEF – Our past (again) filtered through the lens of coloniality: Andrew Smith’s First People – The lost history of the Khoisan
CHANTAL WILLIE-PETERSEN
BHEKI MSELEKU: an infinite source of knowledge to draw from
JEAN MEIRING
SULKE VRIENDE IS SKAARS - a clarion call for the importance of the old and out-of-fashion
GEORGE KING
Kristian Blak String Quartets Neoquartet
ekaya
PAKAMA NCUME
A Conversation with Mantombi Matotiyana 9 April 2019
KYLE SHEPHERD
An Auto-Ethnographic Reflection on Process
PAULA FOURIE
Ghoema
DENIS-CONSTANT MARTIN
The Art of Cape Town Singing: Anwar Gambeno (1949-2022)
ESTHER MARIE PAUW
Something in Return, Act II: The Blavet-Varèse project
STEPHANUS MULLER
Afrikosmos: the keyboard as a Turing machine
MKHULU MNGOMEZULU
Ubizo and Mental Illness: A Personal Reflection
off the record
FRANK MEINTJIES
James Matthews: dissident writer
SABATA-MPHO MOKAE
Platfontein, a place the !Xun and Khwe call home
NEO LEKGOTLA LAGA RAMOUPI
A Culture of Black Consciousness on Robben Island, 1970 - 1980
NELSON MALDONADO-TORRES
Outline of Ten Theses on Coloniality and Decoloniality*
ARYAN KAGANOF
An interview with Don Laka: Monday 10 February 2003
JONATHAN EATO
Recording and Listening to Jazz and Improvised Music in South Africa
MARKO PHIRI
Bulawayo’s movement of Jah People
STEVEN BROWN
Anger and me
feedback
MUSA NGQUNGWANA
15 May 2020
ARYAN KAGANOF / PONE MASHIANGWAKO
Tuesday 21 July 2020, Monday 27 July, 2020
MARIA HELLSTRÖM REIMER
Monday 26 July 2021
SHANNON LANDERS
22 December 2022
FACEBOOK FEEDBACK
Facebook
the selektah
CHRIS ALBERTYN
Lost, unknown and forgotten: 24 classic South African 78rpm discs from 1951-1965.
hotlynx
shopping
contributors
the back page
CHRIS BRINK
Reflections on Transformation at Stellenbosch University
MARK WIGLEY
Discursive versus Immersive: The Museum is the Massage
© 2023
Archive About Contact Africa Open Institute
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    #08
  • Theme AI in Africa

NOLAN OSWALD DENNIS

Toward Misrecognition. | Project notes for a haunting-ting

Project notes for a haunting-ting

Of course this is already old news, computers interface with the world through code. The speed and volume at which machines produce data necessitates an equally fast bulk method of processing – enter artificial intelligence. A double win. AI neural networks have the ability to scrutinise massive amounts of data at incredible speeds with the added benefit of refining their algorithms as they process that data. This learning as they work is an act of computation (sorted, flagging, reorganising) as well as consumption (adjusting their internal procedures based on what they receive from without). In effect turning the data they process into a training dataset which is fed forward into their data processing. This is a feature not a bug.

The artist Trevor Paglen[1]thenewinquiry.com writes about the shift in visual culture from a human centred endeavour to a machine-centric practice of image making and viewing.

The vast majority of images are now produced by machines for the exclusive consumption of other machines

(note. The autocorrect algorithm in my word processor suggests I replace consumption with ‘computation’ – a significant slippage, I will stay with consumption). By far most images in the world will never be seen by a human eye at all.

Equally as important as access to, and circulation of, these images, is the shift in function of machine-images. These images are no longer primarily representational objects, instead they are operational images engaged in mediation, activation and enforcement. While these utilitarian functions are more or less legible at the point of deployment, the images themselves are altogether more mysterious than we may realise.

Digital images are coded information, their native format is not visual but machine readable code. In order for them to be ‘seen’ in any customary sense they must be coaxed out of the image file and output as pixels of light on a screen or printed onto a physical medium. This inefficiency means most files are never realised as visually perceptible images, in any case they are not for us.

While the internal logic of machine intelligence is rigorous (more or less) it is also relatively unsophisticated and governed by highly developed pattern recognition procedures. Powerful, yes, but within tightly constrained realms determined primarily by huge dataset sorting and recombining processes. In spite of their name, the horizon of machine intelligence is understanding. In addition to all their speed and size advantages, the critical benefit of machine learning is the ability to develop and function without human input either in code or in data acquisition. We can assess their performance but not understand their procedures. To us they are opaque and impenetrable. To them we are too.

However the development of increasingly convincing natural language processing algorithms opens the doors of perception to another, weirder, possibility. While NLP is not fundamentally different to other pattern recognition procedures, the consequences of parsing natural language (everyday speech) and generating natural language responses are. These NLP developments shift the threshold of credibility from replicating intelligence (mutual understanding) to recognition of otherness (mutual alienation). A misrecognition perhaps, but that’s okay.

Orientated toward alienation, misrecognition becomes a feature not a bug.

An operational perspective on machine intelligence emphasises the effectiveness of any given performance. A machine must perform tasks always better than a human could in order to persuade us of its intelligence. It is not a mistake that the turing test[2]Turing test is a competition between a human and a machine. It is not a mistake that it is a test either.

Writing about gambling addiction Alexis C. Madrigal [3]theatlantic.com identifies the machine zone. A particular interface between human consciousness and machine procedure, Madrigal describes this zone as a rhythm, a kind of dance between machine prompt and human feedback, human prompt and machine feedback. A repeating cycle of minor gestures between an oblivion-seeking human consciousness and an obliging machine which, when in alignment, distorts spacetime and draws us into the security of the loop. United in apathy, both human and machine give nothing.

This fine-tuned feedback loop is mobilised by casinos and social media companies to keep us in the machine zone where they can extract profit from our desire for a kind of doom scrolling, demonic zen. However misused by nefarious forces, the notion of the machine zone offers an antidote to the utilitarian imagination of intelligence proposed by AI researchers. Overdetermined by capitalist logics of competition and racial-colonial reduction of what counts as human (and therefore intelligent) it seems that for the sake of both ourselves and the machines there must be another way.

I’ve been thinking about whether machine learning might be thought of as learning for the machine. Instead of training machines to execute tasks (really the saddest description of intelligence) we might share with machines another way of being, invert the relationship, teach them how to teach perhaps.

courtesy the artist and Goodman Gallery

My work recently has involved collecting idiosyncratic datasets drawn from the archives of black liberation theory. In biko.fanon (touch/hold) (2018) a dataset is created of all sentences mentioning the words touch and hold in the work of black consciousness theorist Steve Biko and revolutionary psychiatrist Frantz Fanon. This dataset is then recombined using a pseudorandom script to print a scrolling receipt of a conversation between these two figures about touching and holding. I had been thinking about this machine as a performer translating a conceptual proposition on a stage, a performer summoning spectres from the near past. Machine learning presents us with an opportunity to reconceive this kind of relation.

The urgent critique of artificial intelligence from the racialised and colonised world is the critique of implicit and inherited bias.

These machines fail at relatively benign tasks like recognising the faces of people of colour because their training data is determined by the distribution of power and problems in the world at large. Another way to think about this is that these AI models are a reflection of that power, a version of the critique of colonial education which seeks to turn the colonised into new iterations of the coloniser. Is there another possibility for AI models?

I am trying to conceive of a machine learning model trained on black liberation theory. A neural network tasked with iterating the eccentricities of an archive so precious and yet so carelessly unattended to. The task, as always, is channelling the spirit, divining the possibilities and deploying the ghosts. The other etymological root of intelligence is legō – to care.

Notes
1. ↑ thenewinquiry.com
2. ↑ Turing test
3. ↑ theatlantic.com
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CHRIS EMEZUE & IYANUOLUWA SHODE
SLINDILE MTHEMBU
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Archive About Contact Africa Open Institute