VULANE MTHEMBU

Vulane Mthembu is Guest Editor of the AI in Africa Theme Section of this issue of herri.

By the time you read my musings here, most of the details contained within will be obsolete, outdated and serving a merely archival purpose, such is the pace at which artificial intelligence and its relentless march to either human dominance or abetment, depending on whom you ask about the topic, is progressing.

There have been few times in history when the populace has been so enthralled by technological advancement resulting in a plethora of speculative opinions flooding the already crowded “Information Superhighway” (also known as the internet, I’m an 80s baby). With it, concerns – most stemming from the datasets used to train AI – all justified. Next, human skills replacement. Africa and its inhabitants on the continent, where do we stand?

Being a closeted crypto-anarchist I might be incredibly biased on the topic pursuing it with cautious glee and admittedly being partial to some of the artistic exploits of the beast in recent years. My excuse:

the total and complete dominance of AI in our lives is inevitable.

Having just last week used the now immensely popular platform, DoNotPay, which purports to be the “first robot lawyer helping to fight corporations, beat bureaucracy and sue anyone at the press of a button”. It worked. 

Before we get a(head) of ourselves what is AI?: A Primer

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and act like humans. These intelligent machines can be designed to perform tasks that typically require human cognition, such as learning, problem-solving, decision-making, and even creativity.

AI has a long history, with early efforts dating back to the 1950s. However, it was not until the 21st century that AI began to make significant progress and become a topic of widespread interest and concern. This progress has been driven by advances in machine learning, which is a type of AI that allows computers to learn from data without being explicitly programmed.

AI has the potential to revolutionize many industries and transform the way we live and work. However, AI is also a source of concern for some people. One concern is that AI could potentially displace human workers, leading to job loss and economic disruption. There are also concerns about the ethical implications of AI, such as the potential for biased algorithms and the misuse of AI for harmful purposes. In addition, the development and deployment of AI raise questions about issues such as privacy and security. As a result, the ethical and societal implications of AI are an active area of research and debate.

End of the Politician: AI In complex decision making

In his book, The Political Philosophy of AI, Mark Coeckelbergh argues that AI in all its forms is political, and in a post-decolonisation Afrika posited by thinkers such as Olúfemi Táíwò in his book  Against Decolonisation: Taking African Agency Seriously (Hurst/African Arguments, 2022) asking is it time to abandon decolonisation, a serious look at governance and socio-political decisions ‘devoid’ of human tinkering and corruptible greed using a machine is now imperative if not very possible as speculated in the Cicero Foundation’s great argument paper (Georgios I. Zekos,2022).

Artificial intelligence has the potential to significantly enhance complex decision-making through its ability to analyze large amounts of data and extract insights and patterns that may not be immediately apparent to humans. This capability, known as data mining, allows AI to identify relevant factors and relationships within data sets, and to use this information to inform decision-making processes.

In addition to data mining, AI can also assist with complex decision-making through the use of predictive analytics. This involves using machine learning algorithms to analyze historical data and make predictions about future outcomes. These predictions can be used to inform decision-making by providing a probabilistic view of potential outcomes, which can help decision-makers to understand the risks and rewards associated with different choices.

Finally, AI can also be used to automate certain aspects of decision-making processes, such as by identifying and prioritizing tasks or by presenting options based on predetermined criteria. This can free up human decision-makers to focus on more complex or strategic tasks, and can improve efficiency and productivity.

Overall, AI has the potential to significantly enhance complex decision-making by providing data-driven insights, predictions, and automation. By leveraging the capabilities of AI, decision-makers can make more informed, data-driven decisions that are better aligned with their goals and objectives.

On ‘improper thinking and alien recombinations’

While working on this edition of herri, I was occupied by the thoughts and writings of the brilliant Dr Ramon Amaro, who has recently published work on Machine Learning Theory and Racial Bias, called The Black Technical Object On Machine Learning and the Aspiration of Black Being. Amaro, as one of the great researchers and cultural theorists in the field of AI research, in one of his lectures speaks of Machine Learning and the Collective Condition of Black Survival.

In On the Mode of Existence of Technical Objects, Gilbert Simondon argues that alienation in our contemporary techno-culture is caused by an imbalance in our perception and recognition of certain objects as having more value than others, which is pronounced by a desire for power in a partial and biased culture.

In his talk, AI as an Act of Thought, Dr. Amaro argues that there are similarities between Simondon’s thoughts on human-techno alienation and Frantz Fanon’s treatise on the mastery of language, the “abandoned” racialized object, and the affordances of power. He grounds these concepts in machine learning to consider what these provocations might mean in terms of racism and racialized exclusion in non-linear (and therefore, nonrepresentational) computational languages. Ultimately, Dr. Amaro questions how alternative “awarenesses” and systems of value might be achieved in the relation between machine-object-human (Amaro, 2021).

The ‘improper thinking and alien recombinations’ of Recursive Colonialism, Artificial Intelligence & Speculative Computation, a  symposium by The Critical Computation Bureau^{[1]The Critical Computation Bureau is a collective of researchers, artists, and writers working at the intersection of technology and culture, computer science and information theory, aesthetics and politics. We are the ideators, organisers, coordinators, executors of the Symposium “Recursive Colonialism, Artificial Intelligence & Speculative Computation”. The collective is globally situated in the US, the UK, and Southern Italy and, together with its networks spanning several continents, is engaged in interventions in the technopolitics of racial capitalism and its recursive regeneration. The CCB has mixed together critical and creative practices borrowing models and methods from philosophy of technology, black studies, political theory, computer science and information theory, media aesthetics, cultural and digital media theories. Mixing soundz and screenings with concepts, functions and percepts, the CCB is launching RC as a virtual space for improper thinking and alien recombinations. Members of the CCB are Luciana Parisi, Ezekiel Dixon-Román, Tiziana Terranova, Oana Pârvan, and Brian D’Aquino.}, a collective of researchers, artists, and writers working at the intersection of technology and culture, computer science and information theory and politics while exploring the philosophy of technology, black studies, political theory and computer science, have an immediacy and pertinence that cannot be overstated. Their reworking of thought systems will benefit eveyone and not only the “left behinds” as Chris Emezue puts it.

To be present, we need to engage on the continent and beyond, AI is not going away and this time the proverbial ostrich does not get to stick its equally proverbial head in the ground.

Happy Happenstance and Serious Serendipity

In 2021, while organising a game development and VR world-building jam in a virtual reality platform called VRChat, I encountered (yes, this is the new normal), a young man by the name of Baso aka: Supermalome, who happened to be part of a community with some members in the townships working, building and hanging out in the virtual world they have built. A thriving community. Baso documents how sangomas can live in vr and make virtual consultations possible, drawing parallels of the dream state of the otherworldliness of VR and ukuthwasa nokubhula and how AI can be used for procedural generations of these worlds.

Tiisetso builds food computers while Bobby Shabangu talks about AI bots populating Wikipedia within African knowledge entries. Stefanie Kastner muses on what effects European legislation will have on the development of AI in the region. “Everything, Everywhere all at once.”

Addressing bias in systems of value and racialized exclusion

With the speed of progress comes the need to keep an eye on the intrisic cognitive bias, on the possibility of mass human job losses and skills replacement, which I feel could be addressed by treating Universal Basic Income with the seriousness it deserves. Many innovative interventions have been proposed to address these and other questions surrounding AI; among them, The Art and Computation Retreat which is a collaboration between the German Informatics Society, the Goethe-Institut and the Weizenbaum-Institut, where artists, both traditional and polydisciplinary, are paired with computer science researchers to devise (h)activist approaches and methodologies to the challenges posed by the technology in a social framework.

Creating in the Age of AI and Robots in Residence, the latter project taking place across multiple African countries and involving a NAO robot travelling through multiple cities and being reprogrammed in each region. The goal is to teach the NAO local cultural skills in the selected host countries; an exercise in diversity in artificial intelligence.

THE FEW-TURE

Quantum Computing and Neuromorphic Computing and Artificial Intelligence development are the perfect storm, a beautiful convergence that will accelerate what we are witnessing currently to warp drive mode. As a shameless plug here is some of the work done by the Goethe-Institut in the field, Living in a Quantum State.

(Open AI’s ChatGPT wrote this last bit cos why the fuck do we still bother?)

Quantum computing is a type of computing that uses quantum-mechanical phenomena, such as superposition and entanglement, to perform operations on data. Quantum computers have the potential to solve certain problems much faster than classical computers, making them a promising technology for a wide range of applications, including artificial intelligence (AI).

There are several ways in which quantum computing is expected to shape the future of AI:

Enhanced machine learning: Quantum computers can potentially be used to train machine learning algorithms faster and more efficiently. This is because quantum computers can perform certain types of calculations much faster than classical computers, which could speed up the process of training machine learning algorithms on large datasets.

Improved pattern recognition: Quantum computers can potentially be used to analyze large amounts of data more quickly and accurately, which could improve the performance of AI systems that rely on pattern recognition, such as image or speech recognition systems.

Enhanced decision-making: Quantum computers can potentially be used to assist with decision-making by analyzing large amounts of data and providing recommendations or options based on that analysis. This could be useful in fields such as finance, healthcare, and transportation, where there are large amounts of data to be analyzed and decisions to be made.

Greater computational power: Quantum computers have the potential to perform certain types of calculations much faster than classical computers, which could enable them to solve complex problems that are beyond the capabilities of classical computers. This could open up new possibilities for AI applications in areas such as drug discovery, weather forecasting, and financial modelling.

Overall, the future role of quantum computing in AI is expected to be significant, as it has the potential to enhance the performance of machine learning algorithms, improve pattern recognition, and enable the solution of complex problems that are beyond the capabilities of classical computers. However, it is important to note that quantum computers are still in the early stages of development and it is not yet clear when they will be able to achieve the level of performance necessary to have a significant impact on AI.

AI lies not in the power to replace human decision-making but in the ability of AI to enable superhuman decision-making.

Sekou L. Remy^{[2] is a Staff Research Scientist at IBM Research-Africa in Nairobi, Kenya.}