Embedded Files
Africa, the Yoruba People and Artificial Intelligence
Africa, the Yoruba People and Artificial Intelligence
Africa is the second largest and second most populous continent in the world
It has five regions: Northern Africa, Central or Middle Africa , Southern Africa, East Africa, and Western Africa.
The West Africa sub-region consists of the following countries: Benin, Burkina Faso, Cape Verde, The Gambia, Ghana, Guinea, Guinea-Bissau, Ivory Coast, Liberia, Mali, Mauritania, Niger, Nigeria, Senegal, Sierra Leone, and Togo, as well as Saint Helena, Ascension and Tristan da Cunha
Nigeria is the most populous and comprises of three (3) major ethnic groups: Yoruba, Igbo and Hausa.
The Yoruba People
The Yoruba People
The Yoruba people are found in the Western part of Nigeria. They inhabit states such as Oyo, Osun, Lagos, Ogun, Ekiti and Ondo states. They speak the language, Yoruba. The Yoruba people are very learned. “complex number system."
The Mathematician Levi Conant calls it ‘the most peculiar number scales in existence' (Conant, 1896)
The Yoruba love festivities
The Yoruba love festivities
The people of Yoruba can also be found in other parts of the world, such as in the Republic of Benin, Togo, Brazil etc
AI technology was already prefigured in inchoate forms in the Yoruba culture and belief system.
Ifá Divination
Ifá Divination
Ifá is the way the gods, who used to be humans and who once lived among the Yoruba people of Western Nigeria, continue to communicate with the people.
Ifá has a universal character; it is not restricted to the Yoruba people of Western Nigeria. It is called by different names in many parts of the world and is practised among other groups of people within Nigeria. The Fa among the Fon of the Republic of Benin, Eva by Nupes, and Ifá in Cuba, USA, Brazil, Trinidad and Tobago, Jamaica, Suriname and Haiti. Afa by the Ewe of Togo, Ephod by Jews, Geomancy by Europeans, Malagasy, and Ramal or Hati by Arabs.
Ifá Divination
Ifá binary system
Ifá binary system
The above pictures illustrate the similarities between Ifá divination and Computer science, with some suggesting that computer science originated from Ifá.
Ifa has a universal character beyond just the Yoruba people. It is found and referred to by various names in the Republic of Benin, Nupes, Togo, Jews, Sierra Leone, Cuba, the Ivory Coast, USA, Brazil, Trinidad and Tobago, Jamaica, Ghana, Liberia, Suriname and Haiti.
The Yorubas believe that it was the gods who once lived as humans that bequeathed ifa divination to them as a means of communication between the living and the dead.
Ifá is an ancient binary computer system which connects the probabilities of numbers with the complex and technical nature of the human condition.
Computer Science binary code
Computer Science binary code
Several studies have reported a connection between computer science, the advent of AI, and the Ifá divination system. It is argued that the computer employs binary code similar to the binary system of Ifa. Like the computer, Yoruba anthomancy relies on a binary system; thus, it is a computer-based science we can use in mathematical education.
Studies report a connection between computer science, the advent of AI, and the Ifá divination system (Olojede & Fadahunsi, 2024; Omoregie, 2024; Alamu et al., 2013)
Sìgìdì and Ọ̀sanyín
Sìgìdì and Ọ̀sanyín
Sìgìdì
In the domain of humanoid robots, Africans also have precursors.
Sìgìdì is an automaton soldier on an errand to punish their enemies, usually sent on errand to inflict physical and spiritual harm. Sìgìdì was employed as a combatant in war situations.
Ọ̀sanyín
Òsanyin is similar to sìgìdì, but with the ability to speak with diagnostic and recommendation capabilities, similar to Ifa. People turn to Òsanyin for various existential issues, such as marriage, death, and epidemics. Metaphysically, it walks around and delivers messages on behalf of its owner.
The point here is that Sìgìdì and Òsanyin are traditional replicas of modern-day robots; while the former are programmed through metaphysical or spiritual science, the latter utilise empirical science.
Source: Olojede H.T. & Ayo Fadahunsi (2024) On Decolonising AI. Agidigbo. Vol.12, No.2, https://doi.org/10.53982/agidigbo.2024.1201.20-j
Selected African Union Documents
Selected African Union Documents
African Union (AU) - https://au.int/en/aureforms/overview
African Union Continental Artificial Intelligence Strategy
African Union Continental Artificial Intelligence Strategy
The African Union’s Continental AI Strategy, adopted in July 2024, sets an Africa-centric, development-first plan to harness AI for inclusive growth while safeguarding rights. It emphasises five strands—harnessing benefits, building capabilities, minimising risks, stimulating investment, and fostering cooperation—translated into fifteen actions. Implementation runs 2025–2030 in two phases: early governance frameworks, capacity building and resource mobilisation, followed by deployment of priority projects, aligned with AU data and cybersecurity instruments and Agenda 2063. It calls for national AI strategies, ethical and human-rights safeguards, skills pipelines, local-language/data efforts, and interoperable standards to build trustworthy, scalable AI ecosystems.
Continental AI strategy for Africa
https://au.int/en/documents/20240809/continental-artificial-intelligence-strategy
Digital Transformation Strategy for Africa 2020-2030
Digital Transformation Strategy for Africa 2020-2030
The African Union’s Digital Transformation Strategy for Africa (2020–2030) sets a continental roadmap to build an inclusive digital single market by 2030. It prioritises affordable broadband; secure data and cloud infrastructure; interoperable digital ID and payments; harmonised laws and standards; and widespread digital skills. The strategy drives e-government, e-commerce and digital financial services, and modernises agriculture, health and education through innovation and local content. It targets women, youth and rural populations, promotes startups and research, and safeguards cybersecurity, privacy and trust. Implementation hinges on national-REC-AU coordination, investment mobilisation, and rigorous monitoring, aligning with Agenda 2063 and the Sustainable Development Goals.
The Digital Transformation Strategy for Africa
https://au.int/sites/default/files/documents/38507-doc-dts-english.pdf
AU Convention on Cybersecurity and Personal Data aka Malabo Convention
AU Convention on Cybersecurity and Personal Data aka Malabo Convention
The AU’s Malabo Convention, formally the African Union Convention on Cyber Security and Personal Data Protection, entered into force in 2023. It sets a continental baseline for four pillars: electronic transactions, personal data protection, cybersecurity and cybercrime. States commit to harmonising laws; creating independent data-protection authorities; defining lawful processing, data-subject rights, and breach notification; securing networks and critical infrastructure; establishing CERT/CSIRT capabilities; criminalising cyber-offences; and cooperating across borders on investigations, evidence, and extradition. The Convention aims to build trust in Africa’s digital economy, enable safe e-commerce and e-government, protect fundamental rights, and strengthen resilience through capacity-building, standards, and coordinated incident response.
2023 Malabo Convention
https://au.int/en/treaties/african-union-convention-cyber-security-and-personal-data-protection
National AI Strategies of African Countries
National AI Strategies of African Countries
Rwanda’s National AI Policy (2023) is a growth and rights roadmap aligned with Vision 2050. It builds digital skills, data governance and compute; establishes a Responsible AI Office; promotes sandboxes, standards and procurement for trustworthy AI; and prioritises health, agriculture, education and public services to scale innovation, jobs and investment.
The National AI Policy - Rwanda
Mauritius’s 2018 AI Strategy seeks to make the country a hub by building skills, data and compute; creating an enabling ecosystem; and accelerating adoption in government and business. It prioritises health, agriculture, fintech, transport, manufacturing and the ocean economy, stressing ethics, standards and innovation to boost productivity, jobs and services
Mauritius Artificial Intelligence Strategy
https://treasury.govmu.org/Documents/Strategies/Mauritius%20AI%20Strategy.pdf
South Africa’s AI for Africa Blueprint positions AI as a development tool: expand connectivity and compute; build talent and research; grow startups; adopt AI in health, education, agriculture, public services; ensure ethical, rights-based governance, data protection and accountability; promote data standards and sandboxes; drive regional cooperation, investment and inclusive jobs
South Africa AI For Africa Blueprint
https://smartafrica.org/wp-content/uploads/2023/11/70029-eng_ai-for-africa-blueprint-min.pdf
Egypt’s National AI Strategy (led by MCIT) targets sustainable development by building skills, research and startups; developing data, cloud and compute infrastructure; embedding AI in government and priority sectors (health, agriculture, industry, tourism); establishing ethical governance and a National Council for AI; and expanding cooperation to attract investment and jobs.
Egypt National Artificial Intelligence Strategy
The Nigerian Government on Artificial Intelligence
The Nigerian Government on Artificial Intelligence
Source: National Information Technology Development Agency (NITDA) https://nitda.gov.ng/
The draft 73-page document divided into five (5) strategic pillars aims to use AI:
-as tools for growth and competitiveness in productivity, industries, jobs and attraction of foreign investment
for social development and inclusion through the improvement of access to essential services, education is one of them.
- for technological advancement and leadership through developing indigenous AI expertise, creating ethical and regulatory frameworks and becoming a regional and global leader.
https://ncair.nitda.gov.ng/wp-content/uploads/2024/08/National-AI-Strategy_01082024-copy.pdf
The Nigeria Data Protection Regulation (NDPR) 2019, issued by the National Information Technology Development Agency (NITDA), is the cornerstone of data privacy law in Nigeria. It establishes legal safeguards for processing personal data, mandating principles such as lawful processing, purpose limitation, and data security. It grants data subjects rights, including access and correction. The regulation imposes significant obligations on data controllers and processors, requiring compliance audits and appointing Data Protection Officers for major entities. Breaches can result in substantial penalties, up to two percent of annual revenue. The NDPR is broadly applicable to all transactions involving Nigerian data subjects.
https://nitda.gov.ng/wp-content/uploads/2020/11/NigeriaDataProtectionRegulation11.pdf
The National Digital Economy Policy and Strategy (NDEPS) 2020-2030 is Nigeria's strategic roadmap to diversify its economy from oil dependency by accelerating the adoption of digital technologies. Its core objectives are to strengthen infrastructure like broadband, enhance digital literacy and skills, foster innovation-driven entrepreneurship, and improve digital services across both public and private sectors. The policy aims to achieve inclusive economic growth, create millions of jobs, and firmly establish a sustainable digital economy in Nigeria by 2030, ensuring the nation becomes a key participant in the global digital landscape.
The National Policy for the Promotion of Indigenous Content in the Nigerian Telecommunications Sector (NPPIC) mandates the prioritisation of local talent, goods, and services within the industry. Its core objectives are to stimulate domestic manufacturing of telecom equipment, foster homegrown innovation and research, develop local expertise through skills transfer, and ensure Nigerian companies secure a significant portion of market contracts. The policy aims to retain capital within the economy, create sustainable jobs, boost national security, and position Nigeria as a key producer and exporter of telecommunications technology and services, rather than merely a consumer.
Research Papers on Africa and Artificial Intelligence
Research Papers on Africa and Artificial Intelligence
The paper argues that AI now permeates daily life, search engines, drafting texts, alarms, voice assistants, chatbots and most sectors, including education, healthcare and gender-related policy. Its ubiquity makes regulation urgent. Yet current debates and principles remain narrow and uneven, often reflecting limited constituencies. This paper proposes cognate ideals of the common good, solidarity, subsidiarity, human dignity and natural law as complementary foundations rooted in African thought. Grounded in these values, we argue for AI ethics that are genuinely inclusive, development-oriented and practicable, incorporating voices and perspectives from both Majority and Minority worlds. A legitimate framework must reflect African realities while engaging universal norms of justice and flourishing.
Helen Titilola Olojede
(2023)
Towards African Artificial Intelligence Ethical Principles. AI4D Lab. IEEE. https://doi.org/10.1109/AAIAC60008.2023.10465379
Artificial intelligence (AI) has recently emerged as a transformative force in teaching and learning practices, with profound implications for open and distance learning (ODL), which relies heavily on technology. Despite its global impact, the extent of African societies’ engagement with AI remains trivial. This paper critically reflects on the ethical, legal, social, pedagogical and technological implications of AI in ODL in sub-Saharan Africa, drawing insights from the Nigerian experience. Adopting the scoping review methodology, the paper explores and synthesises existing literature to foreground a critical analysis of the implications of AI in the African context.
Helen Titilola Olojede and Felix Kayode Olakulehin
(2024)
Africa Dreams of AI: A Critical Analysis of Its Limits in Open and Distance Learning. Journal of Ethics in Higher Education. https://doi.org/10.26034/fr.jehe.2024.6869
AI ethics is largely framed in the Global North, yet persistent bias and under-representation undermine fairness. Women hold about 22% of AI roles and 24% in cybersecurity; only 54% view robots and AI positively, versus 67% of men. From an African standpoint, the paper asks how to stop AI reproducing inequality and advance gender equity. It proposes a communal approach to conception, design, development and deployment: shared governance with affected communities, diverse teams, robust data and accountability mechanisms that deliver inclusive AI.
Helen Titilola Olojede
(2024)
Reflecting on Diversity and Gender Equality in Artificial Intelligence in Africa. The Thinker
https://journals.uj.ac.za/index.php/The_Thinker/article/view/3950/2226
Logic and probability, as mathematical and philosophical foundations, shape AI: logic structures valid inference and truth, while probability models uncertainty. The split between symbolic and data-driven AI is narrowing, since robust systems need both. Although AI’s formal birth is often linked to the 1956 Dartmouth meeting (Minsky, McCarthy), cognate ideas such as automatons, rule systems and computation also appear in non-Western traditions. This paper recovers those histories with an African focus, arguing for a decolonised genealogy of AI. It presents Yoruba Ifá as a case: a knowledge system built on logic and probabilistic reasoning, showing how indigenous ideas can inform AI.
Helen Titilola Olojede & Ayo Fadahunsi
(2024)
On Decolonising AI. Agidigbo. https://doi.org/10.53982/agidigbo.2024.1201.20-j
Debates on AI in education persist as its use raises ethical questions and worries about cognitive development. In Nigeria the stakes are higher: alongside ethics and cognition, institutions face infrastructure gaps, access barriers and affordability. This paper weighs AI’s pros and cons in higher education, noting benefits such as learner support, accessibility and scalability. Using content analysis, it argues that despite risks such as academic dishonesty, weakened trust, staff workload, digital colonialism and overreliance, Nigeria should harness AI for nationwide educational improvement. It recommends ongoing critical AI literacy for lecturers and students, clear institutional AI policies, and strong data governance.
'Femi Peters and Helen Titilola Olojede
(2025)
Influence of Generative Artificial Intelligence (GenAI) in Nigerian Higher Education Àgídìgbo. https://doi.org/10.53982/agidigbo.2025.1301.17-j
The paper argues that technosolutionism magnifies academic integrity risks in Open and Distance Education by assuming technology should permeate teaching, learning and assessment. It notes rapid uptake of generative AI: a 2023 Nature survey found nearly 30% drafting papers and 5% grants; arXiv analyses report sharp increases, with Computer Science prominent. The paper asks how to harness benefits while protecting integrity, including whether limits are needed, how to bolster honesty, and how to rethink publish or perish. Using discourse analysis and critical theory, it recommends clear green and red lines, disclosure norms, and assessment redesign that rewards authentic learning.
Helen Titilola Olojede
(2024)
Techno-solutionism a Fact or Farce? A Critical Assessment of GenAI in Open and Distance Education. Journal of Ethics in Higher Education.
https://doi.org/10.26034/fr.jehe.2024.5963
Technology Transfer (in the LLM context) and Culture in Africa
Technology transfer (TT) is a form of ‘town and gown’
It is the process whereby technology is spread/disseminated, or commercialised
In the research institution context, it is the process whereby novel inventions and innovations from those institutions’ labs are converted into products and commercialised either through licensing intellectual property to corporations or the establishment of start-up companies which typically license IP that was created by faculty.
Technology transfer is not limited to research institutions.
What is Technology Transfer ?
Technology transfer (TT) in LLM I define as the process whereby technology moves beyond the borders of continents, countries, companies, or individuals to other continents or regions.
The nature of TT here is that it quickly diffuses and becomes ubiquitous in the transferee space, making it challenging to curtail its spread, along with the attendant cultural, social, ethical, and socio-political implications it may have in the ‘host’ countries.
Technology transfer in the LLMs context shares a commonality with traditional technology transfer in which there is a movement, transference, and conveyance of technology.
However, LLM technology transfer differs from these traditional modes in that the movement of technology is from one end of the world to the other(s), from the Global North or the minority world to the Global South or the majority world, while the traditional transfer of technology mostly happens within a given society or country.
Large Language Models and Technology Transfer
Has technology transfer always been from the Global North to the Global South, as is the case with LLM?
Not quite. Africa was once an exporter of technology in what is now the 'lost science of Africa'.
African science has indelible footprints in many endeavours.
How?
METALLURGY
Anthropologists, Peter Schmidt and Donald Avery, revealed that between 1,500 and 2,000 years ago, Africans who lived on the Western shores of Lake Victoria in Tanzania, Rwanda and Uganda had produced carbon steel using ‘pre-heated forced draft furnaces.’
"we have found" said Schmidt, "a technological process in the African Iron Age which is exceedingly complex... to be able to say that a technologically superior culture developed in Africa more than 1,500 years ago overthrows popular and scholarly ideas that technological sophistication developed in Europe but not in Africa."
(Sertima, 1998: 9)
ASTRONOMY
Ancient Africans tied timekeeping to the heavens. Egyptians tracked the moon’s cycle to schedule agriculture, later linking the sun with festivals and seasons. The Dogon of Mali developed elaborate astronomical calendars, incorporating the risings of key stars, notably Sirius.
French anthropologists Marcel Griaule and Germaine Dieterlen reported Dogon traditions referencing an unseen companion, Sirius B, a claim that startled many observers. Scholars noted such knowledge arose outside Western instruments and methods, reflecting African practice where science, religion and history intermingle. Hunter Adams III argues early African inquiry blended intuition with observation, and urges modern research to unite both.
(Sertima, 1998)
MATHEMATICS
The Ishango bone from Lake Edward (Zaire, Democratic Republic of Congo) evidences Africa’s early mathematics (c. 9000–6500 BC). Discoverer Dr Jean de Heinzelin argued its notches show doubling, base-ten thinking and awareness of primes; Dr Alexander Marshack later proposed it served as a lunar calendar. Yorùbá numerals demonstrate abstract reasoning, including a distinctive subtractive system likely shaped by cowrie counting in fives.
Mathematical practice also appeared in measurement, such as Ashante brass weights for gold-dust currency; in patterned network games played by Shongo children; and in recreational calculation through the ayo board game, widespread across Nigeria and other African societies.
(Sertima, 1998)
MEDICINE
Medicine is another area. In surgery, evidence suggests that many African surgeons were as skilled and, in some instances, had superior skills to Western surgeons up to the 20th century. Robert Felkin, a British medical student, reported in 1879 a surgery in Bunyoro in Uganda where a caesarean operation took place under general anaestatia of banana alcohol used as an anaesthetic agent.
“Bunyoro´s medicine was well-developed for the time, in comparison with other sub-Saharan African cultures but also with occidental medicine. Bunyoro´s physicians were familiar with the concept of surgical asepsis and hand-washing, whereas these concepts were just emerging in Europe and were welcomed with skepticism. Banana alcohol is commonly produced in western Uganda for a long time .”
(Diop, 2021: 1)
References and Acknowledgements
References and Acknowledgements
Levi Leonard. (1896). The Number Concept. New York: Macmillan.
Zaslavsky, C. (1970). Mathematics of the Yoruba People and of Their Neighbours in Southern Nigeria Author(s). The Two-Year College Mathematics Journal, Vol. 1, No. 2. https://www.obafemio.com/uploads/5/1/4/2/5142021/math_in_yoruba.pdf
Sylvain Diop et al. (2021). Overview of surgical and anesthesia practice in sub-Saharan Africa during the 19th century: the example of the people of Bunyoro. Pan African Medical Journal. 2021;40(120). 10.11604/pamj.2021.40.120.32092
Olojede, H.T., & Fadahunsi, A. (2024). On Decolonising Artificial Intelligence. Agidigbo. Vol.12, No.2, December 2024. https://journals.abuad.edu.ng/index.php/agidigbo/issue/view/60
Sertima, I. V. (Ed.). (1998). Blacks in Science: Ancient and Modern. Transaction Books, New Brunswick.
GPT5 was used to generate some of the images.
Some images were obtained from Google.
Alamu F.O., Aworinde H.O., Isharufe, W. I. A. (2013). Comparative Study on Ifá Divinity and Computer Science. International Journal of Innovative Technology and Research. 1
Author
Author
We value all contributions to this page.
Please contact Alfina Jackson or Annelise Dixon on LinkedIn if you would like to contribute.
Page updated
Google Sites
Report abuse