The rapid global integration of artificial intelligence (AI) has generated widespread anxiety within African intellectual and policy discourse, often framed as resistance to AI itself. This paper argues that such resistance constitutes a strategic misdiagnosis.
AI is not a negotiable technological trend but an infrastructural transformation reshaping global knowledge systems, governance, and political economy. The real danger facing Africa is not AI per se, but the failure to decolonise AI—understood as the risk that African data, languages, epistemologies, and moral frameworks will be marginalised within global AI architectures. Drawing on postcolonial theory, philosophy of technology, epistemic justice, and contemporary AI governance literature, the paper demonstrates how AI risks reproducing colonial patterns of extraction in digital form. It advances a framework for AI decolonisation grounded in data sovereignty, epistemic sovereignty, institutional capacity, and constitutional governance, and calls for a shift from resistance to stewardship, ownership, and production.
Keywords: Artificial intelligence; decolonisation; Africa; epistemic justice; data sovereignty; digital coloniality.
1. Introduction
Africa is fighting the wrong war. As artificial intelligence becomes embedded in global governance, production, and knowledge systems, African debates have disproportionately focused on resisting AI as a threat to employment, creativity, and cultural authenticity. While these anxieties are understandable, they are strategically misplaced. AI is not a policy option that can be rejected; it is an infrastructural transformation comparable to electricity, print, or the internet (Floridi, 2019). The critical question is therefore not whether AI should exist, but who controls it, whose knowledge it encodes, and whose interests it serves.
2. AI as Infrastructure, Not Moral Agent
AI systems are frequently anthropomorphised as autonomous actors capable of moral transgression. This framing obscures the reality that AI is a socio-technical assemblage whose effects are shaped by institutional design, political economy, and governance choices (Winner, 1980; Feenberg, 2017). AI does not generate values; it amplifies existing power relations. Fighting AI in abstraction therefore amounts to surrendering the terrain where power is actually exercised.
3. Digital Coloniality and the Reproduction of Power
Colonialism functioned not only through territorial domination but through epistemic control—the authority to define reality and legitimate knowledge (Said, 1978; Mudimbe, 1988). AI introduces a new phase of this process. Through data extraction, classification, and prediction, AI systems risk entrenching what scholars describe as digital coloniality (Couldry and Mejias, 2019). Africa risks becoming a supplier of raw data while external actors own the models, platforms, and narratives that govern meaning and value.
4. Beyond Cosmetic “Africanisation”
Efforts to “Africanise AI” often focus on symbolic representation—accents, imagery, or limited language inclusion. While culturally significant, such measures do not address structural power. Decolonising AI requires intervention at deeper levels: data sovereignty, model sovereignty, epistemic sovereignty, and governance sovereignty.
5. Data and Model Sovereignty
Data is the primary resource of AI systems. Without legal and institutional control over data governance, African societies become involuntary data reserves (Taylor and Broeders, 2015). Similarly, AI models embed assumptions about risk, normality, and value. If African institutions are excluded from model development and auditing, misrepresentation becomes structural rather than accidental (Kalluri, 2020; Birhane, 2021).
6. Epistemic Justice and Knowledge Systems
AI increasingly mediates access to knowledge. If African philosophies, customary laws, and historical narratives are underrepresented, epistemic injustice is reproduced at scale (Fricker, 2007). Decolonising AI therefore requires recognising African knowledge systems as legitimate sources of truth rather than peripheral cultural artefacts.
7. Governance, Power, and Algorithmic Administration
The primary risk posed by AI is not human obsolescence but algorithmic administration—the management of populations through opaque systems that concentrate power while diffusing responsibility. Without constitutional and democratic governance, African societies risk being governed by platform policies rather than public law.
8. Conclusion
Artificial intelligence is inevitable. Colonisation is not. Africa’s task is not to resist AI but to reclaim agency within it—shifting from protest to production, from consumption to stewardship. In the twenty-first century, sovereignty will belong to those who own their data, shape their models, and speak their knowledge into the machine.
References
Birhane, A. (2021) ‘Algorithmic injustice: A relational ethics approach’, Patterns, 2(2).
Couldry, N. and Mejias, U. (2019) The Costs of Connection. Stanford: Stanford University Press.
Feenberg, A. (2017) Technosystem: The Social Life of Reason. Cambridge, MA: Harvard University Press.
Floridi, L. (2019) The Logic of Information. Oxford: Oxford University Press.
Fricker, M. (2007) Epistemic Injustice. Oxford: Oxford University Press.
Kalluri, P. (2020) ‘Don’t ask if AI is good or fair, ask how it shifts power’, Nature, 583, pp. 169–171.
Mudimbe, V.Y. (1988) The Invention of Africa. Bloomington: Indiana University Press.
Said, E. (1978) Orientalism. New York: Pantheon.
Taylor, L. and Broeders, D. (2015) ‘In the name of development’, Geoforum, 64, pp. 229–237.
Winner, L. (1980) ‘Do artifacts have politics?’, Daedalus, 109(1), pp. 121–136.
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Isaac Christopher Lubogo
SuiGeneris
Ugandan Legal Scholar | Philosopher
Law, Artificial Intelligence Governance, Knowledge Systems, Decolonial Political Economy
Kampala, Uganda
Bantu MEDIA 