Why Africa Needs an Ubuntu-Inspired AI Framework
Artificial intelligence is rapidly becoming a foundational technology, comparable to electricity or the internet. Like previous general-purpose technologies, it promises productivity gains, new services, and economic growth. However, history shows that such technologies rarely spread evenly, often widening gaps long before any convergence occurs.
The Historical Context
A classic illustration of this pattern is the adoption of electricity in the late 19th century. Major productivity gains emerged decades after its invention, initially benefiting large urban factories capable of investing in new machinery and organizational redesign, while smaller firms and rural areas fell behind. This uneven diffusion initially widened economic disparities, as detailed by Paul David in “The Dynamo and the Computer.” Only later, as supporting infrastructure and skills spread, did broader convergence in productivity occur.
The UNDP’s Warning
This is the central warning of the United Nations Development Programme’s report, “The Next Great Divergence.” Examining AI through a human development lens, the report argues that without deliberate policy choices, AI is likely to intensify inequality both between and within countries rather than reduce it. AI, the report insists, is not destiny; its impact will depend on choices made now about investment, governance, skills, and who gets to participate in shaping these systems.
Africa’s Unique Challenges
For Africa, this warning is not abstract; it describes conditions that are already visible. The UNDP identifies three channels through which AI may shape inequality: people, the economy, and governance. Across all three, starting points matter. Countries with reliable electricity, high-quality connectivity, compute infrastructure, skilled workforces, and strong institutions are positioned to capture early gains. Others risk slower uptake, weaker system performance, and growing dependence on externally developed technologies.
Current Digital Landscape
Although the report focuses on Asia and the Pacific, its diagnosis resonates strongly in African contexts. Many African countries face gaps in digital infrastructure, limited access to compute, shortages of specialized skills, and constrained regulatory capacity. Where these foundations are weak, AI adoption often takes the form of donor-funded pilots, vendor-controlled platforms, or imported “black-box” systems.
Natural language processing systems deployed or piloted in Africa, including translation and conversational tools, have struggled because the underlying models were trained on data that doesn’t reflect local languages, dialects, or cultural context. This results in inaccurate outputs and reliance on data and expertise residing outside the countries where they are used, illustrating the risks of vendor-controlled, black-box AI adoption when local foundations are weak.
Impact on People, Economy, and Governance
For people, AI offers the promise of improved health diagnostics, personalized education, and more accessible public services. However, when African communities are missing from datasets—or are represented only through proxies—systems trained elsewhere misclassify, exclude, or distort lived realities. The report highlights risks of biased or opaque systems that deny benefits, undermine rights, and erode trust, particularly for women, rural populations, and marginalized groups.
For the economy, AI may raise productivity and create new forms of work, but gains are likely to concentrate where skills, capital, and innovation ecosystems already exist. Countries unable to invest in infrastructure, research, and local enterprise risk being locked into low-value roles in global AI value chains, acting as data sources or end-users rather than creators.
In terms of governance, AI can strengthen public administration and decision-making, but only where institutions can audit systems, enforce accountability, and provide meaningful avenues for redress. In lower-capacity settings, the report warns that governments may become dependent on systems they cannot fully understand, adapt to, or contest, weakening both sovereignty and public trust.
Choice, Not Inevitability
Crucially, the UNDP does not present this outcome as inevitable. Whether AI narrows or widens inequality depends on how governments sequence action, invest in solid foundations—power, connectivity, compute—and soft capacity, such as skills, institutions, and governance, along with design frameworks that put people at the center of technological change.
The Ubuntu Framework
Building on a key insight from Gwagwa et al., a governance framework that treats AI as relational and social rather than purely technical or proprietary is proposed. This framework emphasizes inclusivity and collective well-being in shaping who benefits from and who is accountable for AI systems.
The forthcoming “Ubuntu AI Framework” and “Ubuntu AI Scorecard” respond to this challenge. Rooted in the African ethic of Ubuntu, which embodies the idea of “I am because we are,” these frameworks are products of collective reflection rather than top-down design. They emerged from gatherings where researchers, artists, technologists, and civil society actors discussed questions of power, inclusion, and accountability in the age of AI.
Operationalizing Capability
The Ubuntu AI Scorecard translates these values into measurable standards, assessing AI partnerships on ownership, skills, data sovereignty, governance, and socio-economic impact. This ensures Africa is a co-creator, not just a data source. The Scorecard evaluates AI initiatives not only on technical or cost criteria but also on whether they contribute to developmental outcomes.
In doing so, it complements regulation by embedding development considerations directly into decision-making. This approach fosters a more equitable and sustainable AI ecosystem in Africa, aligning with the continent’s unique challenges and aspirations.
