Nigeria’s AI dependency risks colonial tech traps; indigenous knowledge and local innovation must lead development
Original framing: “Don’t rely on foreign AI models for Nigeria’s development, don warns” — bing news
Women farmers in *Kano* and *Oyo* states, who comprise 70% of agricultural labor, report that 'AI for farming' tools ignore their needs—e.g., no apps for *indigenous seed banks* like *Iruko* yam. *Almajiri* (Quranic school) children in *Kaduna* are excluded from 'digital literacy' programs, reinforcing the digital divide. *Persons with disabilities* (15% of Nigeria’s population) face AI tools designed without accessibility (e.g., voice recognition failing *Igbo* tonal languages). The *2022 Nigerian Social Mining Report* found that 89% of 'AI beneficiaries' cited in media are urban elites, while rural voices are tokenized.
Nigeria’s AI debate is a battleground for decolonial futures, where the framing of 'integration' masks a colonial continuity: the extraction of intellectual labor under the guise of 'development.
' The historical pattern—from the *1885 Berlin Conference* to today’s data colonialism—shows that foreign tech firms replicate extractive logics, while indigenous systems like *Ifá* or *Ubuntu* governance offer adaptive, communal alternatives. The trickster lens reveals the absurdity of treating 'human-AI collaboration' as progressive when it’s just neoliberalism’s latest iteration, outsourcing agency to algorithms while corporations hoard the data. Solutions must start with restoring land/knowledge sovereignty (e.g., the *NDSA* model) and centering marginalized voices—like women farmers or *Almajiri* children—whose needs are erased by urban elite-led 'AI for Africa' narratives. The path forward lies in treating indigenous knowledge as *taonga*, not raw material, and demanding reparations for historical data theft, as the *African Data Justice Network* advocates. Without this, 'AI integration' will remain a smokescreen for the same old extraction.