Decolonizing global AI governance: assessment of the state of decolonized AI governance in Sub-Saharan Africa

Author:

Ayana Gelan123,Dese Kokeb123,Daba Nemomssa Hundessa123,Habtamu Bontu123,Mellado Bruce423,Badu Kingsley523,Yamba Edmund523,Faye Sylvain Landry623,Ondua Moise723,Nsagha Dickson823,Nkweteyim Denis823,Kong Jude Dzevela923ORCID

Affiliation:

1. School of Biomedical Engineering, Jimma University, Jimma, Ethiopia

2. Global South Artificial Intelligence for Pandemic and Epidemic Preparedness and Response Network (AI4PEP)

3. Africa-Canada Artificial Intelligence & Data Innovation Consortium (ACADIC)

4. The University of the Witwatersrand, Private Bag 3, Johannesburg, Wits 2050, South Africa

5. Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana

6. Cheikh Anta Diop University, Avenue Cheikh Anta DIOP, Dakar SENEGAL

7. The University Ngaoundere, PO Box 454, Ngaoundere. City, Adamawa Province, Cameroon

8. The University of Buea, PO Box 63, Buea, South West Province, Cameroon

9. Artificial Intelligence & Mathematical Modeling Lab (AIMM Lab), Dalla Lana School of Public Health, University of Toronto, 155 College St Room 500, Toronto, ON M5T 3M7

Abstract

Global artificial intelligence (AI) governance must prioritize equity, embrace a decolonial mindset, and provide the Global South countries the authority to spearhead solution creation. Decolonization is crucial for dismantling Western-centric cognitive frameworks and mitigating biases. Integrating a decolonial approach to AI governance involves recognizing persistent colonial repercussions, leading to biases in AI solutions and disparities in AI access based on gender, race, geography, income and societal factors. This paradigm shift necessitates deliberate efforts to deconstruct imperial structures governing knowledge production, perpetuating global unequal resource access and biases. This research evaluates Sub-Saharan African progress in AI governance decolonization, focusing on indicators like AI governance institutions, national strategies, sovereignty prioritization, data protection regulations, and adherence to local data usage requirements. Results show limited progress, with only Rwanda notably responsive to decolonization among the ten countries evaluated; 80% are ‘decolonization-aware’, and one is ‘decolonization-blind’. The paper provides a detailed analysis of each nation, offering recommendations for fostering decolonization, including stakeholder involvement, addressing inequalities, promoting ethical AI, supporting local innovation, building regional partnerships, capacity building, public awareness, and inclusive governance. This paper contributes to elucidating the challenges and opportunities associated with decolonization in SSA countries, thereby enriching the ongoing discourse on global AI governance.

Funder

International Development Research Centre

Social Sciences and Humanities Research Council of Canada

Natural Sciences and Engineering Research Council of Canada

Publisher

The Royal Society

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