POTENTIAL ROLE OF AFRICAN UNION IN DEVELOPMENT OF AI GOVERNANCE ACROSS THE CONTINENT
DOI:
https://doi.org/10.46827/ejsss.v10i4.1822Trefwoorden:
AI, AI governance, AI strategiesSamenvatting
This study addressed the fragmentation of AI governance approaches across Africa and examined the African Union's (AU) potential role in unifying these efforts. Using qualitative document analysis of AU publications and academic literature, the research explored the AU's continental AI governance approach, key initiatives, challenges, and future directions. Findings revealed that the AU made significant progress through initiatives such as the Continental AI Strategy (2024), the African Research Centre for Artificial Intelligence (ARCAI), the African Digital Compact, and the AU Data Policy Framework. However, challenges persisted, including regulatory fragmentation among member states and infrastructure disparities. The study discussed the AU's proposed governance mechanisms, including a high-level coordination mechanism on AI and adaptable regulation models, while noting threats from rapid global AI development and widening digital divides. It concluded that the AU's success in AI governance hinged on balancing innovation with ethics, addressing Africa-specific challenges, and fostering collaboration. Key recommendations included accelerating model AI regulation development, prioritizing digital infrastructure initiatives, enhancing ARCAI's role in building local expertise, and strengthening Africa's voice in global AI governance. This research contributes to the literature on AI governance in Africa, offering insights for policymakers on developing uniquely African approaches to inform global discussions.
Article visualizations:
Referenties
Addy, A., Nyante, F., Mensah, G. B., & Frimpong, P. O. (2023). AI-augmented governance of the Ghanaian healthcare delivery system: Ethical and privacy issues in patients' medical records, access and retrieval. International Journal of Law Management & Humanities, 6(5), 2066–2091. http://dx.doi.org/10.10000/IJLMH.115984
African Union. (2020). The digital transformation strategy for Africa 2020-2030. https://au.int/sites/default/files/documents/38507-doc-dts-english.pdf
African Union. (2024, August 9). Continental artificial intelligence strategy. https://au.int/en/documents/20240809/continental-artificial-intelligence-strategy
African Union. (2024, June 17). African ministers adopt landmark continental artificial intelligence strategy. https://au.int/en/pressreleases/20240617/african-ministers-adopt-landmark-continental-artificial-intelligence-strategy
African Union. (2024, August 28). African Union committed to developing AI capabilities in Africa. https://au.int/en/pressreleases/20240828/african-union-committed-developing-ai-capabilities-africa
African Union. (2024, September 13). Unpacking the potential of artificial intelligence to accelerate youth development. https://au.int/en/pressreleases/20240913/unpacking-potential-artificial-intelligence-accelerate-youth-development
African Union. (2024, September 13). Artificial intelligence (AI) for sustainable youth development in Africa: A policy brief. https://au.int/en/documents/20240913/artificial-intelligence-ai-sustainable-youth-development-africa-p-o-l-i-c-y-b-r-i
African Union. (2024). AI for sustainable youth development finalized copy. https://au.int/sites/default/files/documents/44080-doc-AI_for_Sustainable_Youth_Development_finalized_copy-1.pdf
Bowen, G. A. (2009). Document analysis as a qualitative research method. Qualitative Research Journal, 9(2), 27–40. https://doi.org/10.3316/QRJ0902027
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications. Retrieved from https://www.ucg.ac.me/skladiste/blog_609332/objava_105202/fajlovi/Creswell.pdf
Daly, A., Hagendorff, T., Hui, L., Mann, M., Marda, V., Wagner, B., Wang, W. W., & Witteborn, S. (2021). Artificial intelligence, governance and ethics: Global perspectives. In S. Esayas & T. Mahler (Eds.), Regulating artificial intelligence in industry (pp. 182–201). Routledge. Retrieved from https://www.routledge.com/Regulating-Artificial-Intelligence-in-Industry/Bielicki/p/book/9781032159652
Dignum, V. (2023). Responsible artificial intelligence: Recommendations and lessons learned. In D. O. Eke, K. Wakunuma, & S. Akintoye (Eds.), Responsible AI in Africa (pp. 1–20). Springer Nature. https://doi.org/10.1007/978-3-031-08215-3_9
Eke, D. O., Chintu, S. S., & Wakunuma, K. (2023). Towards shaping the future of responsible AI in Africa. In D. O. Eke, K. Wakunuma, & S. Akintoye (Eds.), Responsible AI in Africa (pp. 21–40). Springer Nature. https://doi.org/10.1007/978-3-031-08215-3_8
Eke, D. O., Wakunuma, K., & Akintoye, S. (2023). Introducing responsible AI in Africa. In D. O. Eke, K. Wakunuma, & S. Akintoye (Eds.), Responsible AI in Africa (pp. 41–60). Springer Nature. https://doi.org/10.1007/978-3-031-08215-3_1
Gasser, U. (2023). An EU landmark for AI governance. Science, 380(6651), 1203. https://doi.org/10.1126/science.adj1627
Hickman, E., & Petrin, M. (2021). Trustworthy AI and corporate governance: The EU's ethics guidelines for trustworthy artificial intelligence from a company law perspective. European Business Organization Law Review, 22, 593–625. Retrieved from https://link.springer.com/article/10.1007/s40804-021-00224-0
Kwanya, T. (2023). Working with robots as colleagues: Kenyan perspectives of ethical concerns on possible integration of co-bots in workplaces. In D. O. Eke, K. Wakunuma, & S. Akintoye (Eds.), Responsible AI in Africa (pp. 61–80). Springer Nature. https://doi.org/10.1007/978-3-031-08215-3_4
Larsson, S. (2021). AI in the EU: Ethical guidelines as a governance tool. In A. Bakardjieva Engelbrekt, K. Leijon, A. Michalski, & L. Oxelheim (Eds.), The European Union and the technology shift. Palgrave Macmillan.
Mäntymäki, M., Minkkinen, M., Zimmer, M. P., Birkstedt, T., & Viljanen, M. (2023). Designing an AI governance framework: From research-based premises to meta-requirements. In Proceedings of the 31st European Conference on Information Systems (ECIS 2023). Association for Information Systems. Retrieved from https://www.researchgate.net/publication/370155604_Designing_an_AI_governance_framework_From_research-based_premises_to_meta-requirements
Mensah, G. B., Nyante, F., Addy, A., & Frimpong, P. O. (2023). Navigating the fragmented landscape: A clarion call for the consolidation of Ghana's AI governance framework. ResearchGate Preprint. https://doi.org/10.13140/RG.2.2.31296.75526
Nieminen, M., Gotcheva, N., Leikas, J., & Koivisto, R. (2019). Ethical AI for the governance of the society: Challenges and opportunities. In Proceedings of the 30th European Conference on Information Systems (ECIS 2020). Association for Information Systems. Retrieved from https://ceur-ws.org/Vol-2505/paper03.pdf
Okolo, C. T., Aruleba, K., & Obaido, G. (2023). Responsible AI in Africa—Challenges and opportunities. In D. O. Eke, K. Wakunuma, & S. Akintoye (Eds.), Responsible AI in Africa (pp. 81–100). Springer Nature. https://doi.org/10.1007/978-3-031-08215-3_3
Robles, P., & Mallinson, D. J. (2023). Catching up with AI: Pushing toward a cohesive governance framework. Politics & Policy, 51(3), 355–372. https://doi.org/10.1111/polp.12529
Ruttkamp-Bloem, E. (2023). Epistemic just and dynamic AI ethics in Africa. In D. O. Eke, K. Wakunuma, & S. Akintoye (Eds.), Responsible AI in Africa (pp. 101–120). Springer Nature. https://doi.org/10.1007/978-3-031-08215-3_2
Stahl, B. C., Leach, T., Oyeniji, O., & Ogoh, G. (2023). AI policy as a response to AI ethics? Addressing ethical issues in the development of AI policies in North Africa. In D. O. Eke, K. Wakunuma, & S. Akintoye (Eds.), Responsible AI in Africa (pp. 121–140). Springer Nature. https://doi.org/10.1007/978-3-031-08215-3_7
Stix, C. (2021). The ghost of AI governance past, present and future: AI governance in the European Union. In J. Bullock & V. Hudson (Eds.), Oxford University Press handbook on AI governance. Oxford University Press.
Yin, R. K. (2018). Case study research and applications: Design and methods (6th ed.). SAGE Publications. Retrieved from https://study.sagepub.com/yin6e
Zhang, B., & Dafoe, A. (2020). U.S. public opinion on the governance of artificial intelligence. arXiv. https://doi.org/10.48550/arXiv.1912.12835


