Introduction

The use of artificial intelligence (AI) and integration of autonomous systems continues to form an integral part of our daily lives, with AI growing at an exponential rate. Consequently, the need to develop and utilize rigorous regulatory mechanisms to keep AI in check has gained traction globally. This has been made necessary due to the vast capabilities that AI has, as well as the uncertainties surrounding its full potential. Concerns around the potential that AI possesses has been a cause for concern for researchers, policy makers and governments agencies among other actors.   This can in part be attributed to risks such as misaligned AI, breach of data protection laws, identity theft amongst others. The nature of risks associated with AI  have both short term and long term effects and regulatory mechanisms are being employed to help address both kinds of risks. 

Regulatory interventions have in recent years become a priority, with developed countries being at the forefront. This is evidenced by the amount of effort at regional and national level with regards policy formulation and legislation. Countries like the USA, China and Spain already have in place legislation to respond to diverse concerns that may crop up as a result of AI. ^[1] This is largely due to the fact that most developments around AI have been a reserve of already developed countries (the AI development space has been predominantly a reserve of USA, China and Europe).

Despite this, developing countries have not been left behind, with efforts being made at regional levels to respond to the capabilities that AI has.^[2] Though it is necessary to adopt and implement proper governance measures, expecting currently existing measures to produce uniform results world over is, in my view, impractical. There exists a dichotomy between already developed countries and developing countries which is attributed to various salient factors.^[3] This dichotomy further compounds the intricacies of policy formulation. ^[4] 

This piece will focus on Africa, and will highlight some of the current challenges that countries in Africa are likely to encounter with regards AI governance, given the exponential rate of development and deployment of AI systems. I assert that developing countries cannot be expected to apply the same governance measures as the ones in developed countries, due to the existing socio-economic and geo-political differences. In the grand scheme of things, these differences affect the efficiency and enforceability of laws and policy, as states are limited in terms of capacity. I conclude by highlighting some of the areas where African states can improve, if they are to achieve robust AI governance frameworks in their respective jurisdictions. 

A preliminary disclaimer is that the views expressed herein and the areas identified are not exhaustive. Discourse on AI Regulation and policy in Africa is quite broad, and what I have captured in this piece is merely a brief overview of the status quo. 

Some Challenges to Effective AI Governance in Africa

Economic Strength and Short-term Cause Prioritization 

The first and probably most obvious distinction between already developed and developing countries is linked to economic strength. This directly affects capacity in the global south in terms of infrastructure that can accommodate AI development, deployment and regulation.^[5] Countries in Africa, have had a long history of overdependence on the north and are more likely to rely on foreign debt, for example, to be able to run efficiently and effectively.^[6] With the limited resources available, priority is bound to be given to sustainability programs and projects, rather than longtermist initiatives (this assertion is made with the presumption that funds received are not the subject of corruption and misappropriation). In the long run, little or no focus is directed to emerging technologies such as AI which have the potential to significantly transform life as we know it. This can be seen in the number of African countries, for instance, that have taken measures towards AI regulation through policy formulation.^[7] 

Developed countries tell a different narrative, as the time, energy and resources allocated towards funding AI research, and monitoring its development is phenomenal. Independent and state funded organizations prioritize research on the potential benefits and risks that are associated with AI, and ultimately, a greater vision of Transformative AI (TAI) is kept alive.^[8] The difference in terms of priorities between the global economic giants and developing countries then becomes more apparent. Governments in both the global north and the global south have pressing problems, as unique as they may be, but the global south lacks in capacity and resources. A focus on sustainability would undoubtedly seem more feasible in such an instance, thus resulting in a systemic neglect of other potential cause areas such as AI. 

Inclusive and Vibrant AI Discourse 

The conversations surrounding AI in the global south are not as vibrant as it is in the global north. This issue goes deeper to the kind of political, social, cultural and intellectual space that is in the south. Conversations around AI in the global north are not limited to academic and research institutions, but extend to other actors such as the media.^[9] This then plays a crucial role in helping shape public opinion as well as providing avenues for people to express their thoughts, ideas and concerns. People from all cadres are able to openly engage in discussions around AI. thus ensuring a well-informed public. 

While such public participation and information outlets are available and open to people in the global south, their priorities are entirely different. A significant number of institutions, both academic and philanthropic, focus their efforts on combating the present challenges in the global south. This would include tropical diseases, hunger, promoting democracy, poverty amongst other cause areas. Most conversations in the south reflect the state of affairs in the individual countries. With a seemingly full agenda, it is quite the task to expect people to shift their time, energy and resources, to technologies that are yet to be fully realized in the south. Under such circumstances, cause prioritization is on the basis of moral valuations based on a temporal scale.

Conclusion

While efforts are being made in jurisdictions such as Europe and America to ensure that basic principles such as transparency are met in relation to AI^[10], the global south is yet to fully appreciate the potential that AI has. This in turn results in the apparent complacency that the global south has exhibited thus far.

The global south still has a lot of work to do to ensure that :

1. There is a deep understanding of AI, its capabilities, benefits and risks,
2. There is adequate infrastructure to provide an environment that can accommodate AI deployment, use and regulation,
3. There are adequate institutions channeling their efforts towards generating and disseminating information regarding AI to the general public as well as policy makers,
4. The likely tremors and ripple effects that might be associated with the adoption of AI in the global south are adequately anticipated,
5. AI research from the global south is designed in a manner that reflects the values, principles and ethos of the diverse global south, and that
6. AI governance mechanisms are developed and adopted in a manner that does not prejudice the global south or advance neocolonialism.

Despite the stark differences that are currently there, there is no denying that AI has already secured its place in the world. The rate at which society transforms as a result of AI and related technologies will be largely influenced by the choices we make in the present. Is the global south ready to adopt measures simply because they apply to the global north? I find this quite shallow and to some extent, lazy. These differences should inspire the  global south to actually put in more and more effort towards research and advancement of policy specific to AI. We cannot expect to see the fruits of our efforts spontaneously, but in the long run, the collective effort is bound to pay off. With autochthonous research and national and regional investment, there is potential for a solution to AI regulation and governance. If adequate effort is put in, the global south  will be at a better position to absorb the immediate tremors that come with the adoption of AI systems. 

Should this be realized, the global south will not need to directly transplant Western and Eurocentric mechanisms for the regulation of AI. Such a feat would instead enable collaborative research and investment towards more long term solutions at a global scale. ^[11]

1. ^{^}

   Nestor Maslej, Loredana Fattorini, Erik Brynjolfsson, John Etchemendy, Katrina Ligett, Terah Lyons, James Manyika, Helen Ngo, Juan Carlos Niebles, Vanessa Parli, Yoav Shoham, Russell Wald, Jack Clark, and Raymond Perrault, “The AI Index 2023 Annual Report,” AI Index Steering Committee, Institute for Human-Centered AI, Stanford University, Stanford, CA, April 2023.

2. ^{^}

   ‘Resolution on the need to undertake a Study on human and peoples’ rights and artificial intelligence (AI), robotics and other new and emerging technologies in Africa’ , African Commission on Human and Peoples Rights, ACHPR/Res. 473 (EXT.OS/ XXXI) 10 March 2021 -<https://achpr.au.int/en/adopted-resolutions/473-resolution-need-undertake-study-human-and-peoples-rights-and-art > on 20 July 2023

3. ^{^}

   Arkadiusz Michał Kowalski, ‘Global South-Global North Differences’ in Walter Leal Filho, Luciana Brandli, Amanda Lange Salvia, Pinar Gökcin Özuyar, Tony Wall, and Anabela Marisa Azul (eds), No Poverty. Encyclopedia of the UN Sustainable Development Goals, Springer International Publishing, 2020. 

4. ^{^}

    Dr Rachel Adams, ‘ AI in Africa: Key concerns and considerations for the future of the continent’, Africa Policy Research Institute, 30 May 2022, -<https://afripoli.org/ai-in-africa-key-concerns-and-policy-considerations-for-the-future-of-the-continent >- on 22 June 2023. 

5. ^{^}

   Dr Rachel Adams, ‘ AI in Africa: Key concerns and considerations for the future of the continent’.

6. ^{^}

    ‘Africa faces a mounting debt crisis,’ The Economist, 16 May 2023, -<https://www.economist.com/middle-east-and-africa/2023/05/16/africa-faces-a-mounting-debt-crisis >- on 22 June 2023.

7. ^{^}

   Aleksandra Gadzala, ‘Coming to life: Artificial intelligence in Africa’, Atlantic Council; Africa Center, November 2018, -<https://www.atlanticcouncil.org/wp-content/uploads/2019/09/Coming-to-Life-Artificial-Intelligence-in-Africa.pdf  >- on 28 June 2023.

8. ^{^}

    Transformative AI refers to AI that has transformative power, similar to or comparable to the agricultural and industrial revolution; see Holden Karnofsky, ‘Some background on our views regarding advanced Artificial Intelligence’, Open Philanthropy, May 6 2016, -<https://www.openphilanthropy.org/research/some-background-on-our-views-regarding-advanced-artificial-intelligence/#1-defining-transformative-artificial-intelligence-transformative-ai >- on 27 June 2023.

9. ^{^}

   Dennis Nguyen & Erik Hekman, ‘The news framing of artificial intelligence: a critical exploration of how media discourses make sense of automation’, AI & Society, 17 May 2022, -<https://link.springer.com/article/10.1007/s00146-022-01511-1 >- on 28 June 2023.

10. ^{^}

     ‘EU AI Act: The first regulation on Artificial Intelligence’, European Parliament News, 8 June 2023, -<https://www.europarl.europa.eu/news/en/headlines/society/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence >- on 28 June 2023. 

11. ^{^}

     Dr Rachel Adams, ‘ AI in Africa: Key concerns and considerations for the future of the continent’.