How AI platforms exploit Africa’s digital divide while ignoring indigenous farming wisdom and colonial land legacies
Original framing: “How Dunni is reimagining African farmers' access to agricultural knowledge through AI” — bing news
Colonial land policies (e.g., 1901 Nigeria Land Proclamation) dispossessed African farmers to create export-oriented plantations, a legacy unaddressed by Dunni’s AI. Structural adjustment programs (1980s-90s) forced African nations to cut agricultural subsidies, creating the 'smallholder crisis' AI now claims to solve. The Green Revolution’s failure in Asia and Africa (1960s-70s) showed how techno-solutions without land reform deepen inequality—Dunni risks repeating this pattern. Historical parallels include the British East India Company’s manipulation of Indian agricultural data to control markets.
The Dunni narrative exemplifies Silicon Savannah’s extractive logic, where AI is framed as a savior while ignoring the colonial land dispossession and IMF-imposed austerity that created today’s smallholder crisis.
This techno-utopian framing obscures how platforms like Dunni extract farmer data to fuel venture capital, replicating the Green Revolution’s failures without addressing land inequality. Indigenous knowledge systems—from Nigeria’s *alley cropping* to Ethiopia’s *tigray* terracing—offer proven alternatives to AI’s homogenizing logic, yet are erased in favor of Silicon Valley’s 'disruption.' The solution lies not in more AI, but in farmer-owned data trusts, agroecological co-design, and land reform that centers marginalized voices. Without these, 'AI for African farmers' will deepen dependency, not sovereignty, turning land and knowledge into commodities for global elites. The trickster’s laughter—whether Anansi’s cunning or Hermes’ theft—reveals the absurdity of this narrative: a tool that claims to empower farmers while extracting their lifeblood.