TLDR: Forbes Africa highlights the critical need for Artificial Intelligence development in Africa to be deeply rooted in the continent’s unique lived realities, values, and cultural contexts. The article emphasizes that ethical AI innovation must prioritize local consent, context, collaboration, and co-creation to avoid ‘algorithmic colonization’ and ensure equitable benefits. Despite significant challenges like infrastructural deficits and data underrepresentation, African nations are striving for AI independence through strategic policies, local innovation, and the integration of indigenous philosophies like Ubuntu.
In a recent report, Forbes Africa underscores the imperative for Artificial Intelligence (AI) development on the continent to be intrinsically linked to African realities, ensuring that technology serves its people equitably and preserves human dignity. The discourse centers on ethical AI innovation, which, according to experts, must begin with consent, proceed with context, and culminate in collaboration and co-creation, reflecting both quantitative data and nuanced cultural understanding.
The global standard for AI ethics was set in 2021 with UNESCO’s recommendations, covering critical areas such as data protection, inclusive governance, privacy, and risk. This framework posits AI governance as a paramount challenge of our era, demanding ethical best practices and shared responsibility globally. Africa’s commitment to this vision is evident in the African Union’s adoption of the Continental Artificial Intelligence Strategy in 2024, which prioritizes regulatory frameworks, local innovation, and the safeguarding of civil rights and liberties. Further solidifying this commitment, the Africa Declaration on Artificial Intelligence was signed in Kigali in April by 52 African states.
Despite these strategic advancements, Africa faces a distinct starting line in the global AI race. Only a handful of countries, including Rwanda, Kenya, South Africa, Egypt, Mauritius, and Nigeria, have established national AI strategies or regulatory bodies. The continent grapples with persistent infrastructural challenges, such as unreliable power and internet access, which impede its capacity for AI innovation and development. These inequities exacerbate the digital divide, directly impacting the evolution of ethically relevant AI for the African context.
Dhesen Ramsamy, Group Chief Technology and Data Officer at Old Mutual Limited, articulated to FORBES AFRICA that ‘AI ethics in Africa has to be grounded in our lived realities. It’s not just about fairness and privacy in the abstract, but about ensuring technologies serve people equitably, preserve human dignity and reflect local/African values.’ He stressed that ethical AI in Africa means assessing whether systems empower or exclude, and whether they genuinely understand the African context or merely overwrite it, aiming for AI to be a tool for inclusive development rather than a source of further disparity.
Experts caution that Western AI systems, often built on assumptions and data specific to their regions, risk imposing external values—a phenomenon termed ‘algorithmic colonization.’ This can sideline African narratives, such as community and interconnectedness, replacing them with imported ideals. Louis-Neil Korsten, CEO of Spock, highlighted that philosophies like Ubuntu, which emphasize collective wellbeing, should naturally inform a governance approach that prioritizes community benefit and ensures equitable value extraction from data.
Korsten advocates for ‘AI independence through competitive free markets,’ urging Africa to control its AI trajectory by developing application-layer solutions, leveraging open-source models, and eventually owning core models and infrastructure. This strategy aims to reduce reliance on dominant global players and ensure Africa’s future is shaped by its own market forces and governance. He also emphasized the need for decentralized data management, federated learning, and data-visiting models to keep data localized, alongside investment in diverse, representative datasets.
A significant challenge is the underrepresentation of African faces in computer vision training, accounting for only 2.8% of datasets. This leads to higher error rates, misidentification, and unfair outcomes in critical areas like credit, healthcare, and employment. Ramsamy noted the urgency to protect against exploitative data practices, algorithmic bias, and surveillance, especially as many African communities rapidly adopt digital ecosystems without established guardrails. He sees this as an opportunity to build ethical, inclusive, and uniquely African systems from the ground up.
Initiatives like the Deep Learning Indaba’s African Datasets Initiative, the MUTFER2024 dataset, Singularity University South Africa, and the African AI Ethics Alliance (led by Dr. Claudia Aranda) are actively working to advance African perspectives in technology and research, establishing context-specific ethical principles emphasizing data self-determination.
Korsten also pointed out the structural challenge posed by global tech giants’ power, warning against potential regulatory capture. He called for incentives to foster growth and competition among African players, promote widespread AI education, and encourage public-private partnerships to reach marginalized groups. Ramsamy added the challenge of balancing data sovereignty with practical implementation, given Africa’s limited datacenter capacity, stressing that data should not be indefinitely controlled by external entities.
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Ultimately, the ethical imperative is to prevent AI from exacerbating existing inequalities. With only 10% of AI’s projected $15.7 trillion economic impact expected to reach the Global South, Ramsamy concluded that ‘we must actively design ethical frameworks that prevent AI from becoming another tool of exclusion.’
