Basking in the ubiquitous adoption of mobile technology in Africa, experts in the technology domain prognose a similar upswing in the application of artificial intelligence (AI), especially in the communications space, and expect it to help leapfrog critical challenges on the continent. With predictions of significant advancements relying on AI over the next 20 years, there seem yet very sparse collective attempts by regional governments in Africa and the continent as a whole to deal with critical emerging issues. This is especially the case with regard to data protection and privacy, such as government surveillance or corporate influence over customers. Though the challenge of specific AI-related cyberpolicy formulation on the continent may appear unrealistic at this early stage, it is imperative to initiate critical discussions on the context-specific requirements with regard to adapting existing or formulating new regulatory policy as it pertains to AI.
At the regional level, the focus has largely been on the policy element of data privacy, with the Economic Community of West African States (ECOWAS) leading the way via the 2010 Supplementary Act on Personal Data Protection within ECOWAS. Similar, albeit non-binding policy instruments have also been developed by the East African Community (EAC) – the 2012 Bill of Rights for the EAC and the 2011 draft EAC Legal Framework for Cyber Laws. In the same regard, the Southern African Development Community (SADC) established the Model Law on Data Protection in 2012, but it is non-binding on member states, making implementation and enforcement difficult. However, disharmony at the regional level with respect to policy formulation generally undermines levels of compliance. This situation demands more continent-level coherence for easier adoption and implementation. If it persists as it is, the disharmony inadvertently increases the gap between the frontiers of global technology and mechanisms of local and regional governance that has geopolitical ramifications for the continent.
Institutional challenges for regional/continental data protection policy harmonisation in Africa
A challenge with respect to the continental-level data policy process is that it is a very slow and painstaking process. As a result, although less than half the countries on the continent have implemented policies on data, many have been forced to move ahead without necessarily looking to the region for guidance. In addition, with the largely top-down approach of data policy engagement by the AU and the Regional Economic Communities (RECs), with people just making laws on behalf of countries, regional instruments are bound to run into significant adoption challenges. In this light, research indicates that a top-down regional policy engagement process might only be designed to “serve narrow regime interests at the expense of broader national and collective interests.”
Another challenge impacting the adoption of the AU Malabo Convention is the lack of sector or industry-specific considerations with regard to data protection and privacy guidelines akin to the European model laws. This creates unhelpful levels of uncertainty and unpredictability, especially for multinational organisations seeking compliance within national boundaries.
This situation makes Africa’s relationship with data governance unclear – a lack of clarity that is compounded by capacity constraints. The policy-making institution in Africa is largely led by a traditionally analogue generation that predates the internet age, making the understanding of data-led digital policy engagements challenging. There is therefore a lack of capacity and understanding of who should take responsibility in the region with regard to data-driven technology and its imperatives with respect to digital rights. This general lack of understanding leads to a lack of policy direction with respect to emerging issues such as AI.
The existing lack of capacity and technical expertise at the policy-making echelon for data governance in Africa poses a significant implementation and process management cost to a harmonised regional policy framework. Further training and assistance for policy makers may be required; more so as a large number of AU member countries are yet to establish independent data privacy regulatory authorities. Bridging this capacity gap among policy makers within the AU region is imperative, as an unclear understanding of emerging technological developments with respect to data policy might produce the unintended consequences of limiting the region’s competitiveness in the AI economy. This is of importance when it comes to issues such as data availability for multinational organisations operating on the continent that collect, process and share data for AI-based applications and services, especially those that are mobile phone based. For example, a forced data localisation regime on the pretext of maintaining national security and sovereignty might restrict cross-border data transfers for such multinational data companies who may choose to move their foreign direct investment to more favourable destinations.
In adapting current regional data protection frameworks in Africa to deal effectively with the emerging challenges of AI, there are many lessons that Africa needs to learn from other regions that have moved forward earlier with policies and practices relevant to data protection and related cyberpolicy.
While the European Union's General Data Protection Regulation (GDPR) is a model for regional data protection policy collaboration, it can be improved on and not just taken as a silver bullet solution for the continent. Nevertheless, many of its requirements are worth adopting. For example, considering the cross-border imperatives of AI systems, regional data policy instruments should be framed in such a way that data-handling firms operating in Africa must be made to sign up to the data protection and privacy laws within their operational jurisdictions, whether or not they are registered as a business entity in those jurisdictions. This is of significant importance for Africa considering the fact that critical data-related projects across the continent are handled and processed outside her borders. Some key examples in this regard include the Kenya Digital ID project, which is hosted and processed by a foreign company, and the data collected by Ghana’s Electoral Commission, which is not hosted in-country. Moreover, none of the big data firms – Facebook, Google, Amazon and Microsoft – are registered as business entities in any African country.
The following action steps are suggested for civil society:
- Capacity building for effective policy making: Africa has been saddled with the burden of leaders who are behind technology advancements. Keeping pace with evolving technologies will require policy evolution and adaptations. Civil society can help in bridging these capacity deficits in such a manner that cross-country peculiarities and spillovers are taken into consideration. They can engage in the build-out of AI knowledge centres across the region that will help bridge these critical gaps by encouraging a thorough understanding of the issues involved, and serve as a resource to help understand the policy directions of the various RECs with respect to AI.
- Pushing for AI-related principles and values in data protection policy: Data protection laws and frameworks are built on general principles, like most technology laws, which are developed to regulate appropriate behaviour regardless of technology evolution with time. However, AI involves a number of specific issues that need to be addressed. Civil society can advocate for appropriate contextual principles and values around which the regional entities can coordinate on data protection policy relevant to AI. Critical among these principles for Africa is the right to privacy of an individual, which is fundamental for our existence as human beings. Furthermore, people need to become more aware with respect to transparency and openness. Another principal area of concern with regard to AI policy is the issue of bias, as AI is currently being developed in primarily two regions of the world: the West and China/Russia. In each of these regions, there is a paucity of data being fed into AI machines that correlates with the African experience. Furthermore, AI data policy for the continent must not be a one-sided issue; it has to be gender-centric and also take into consideration marginalised groups as well as the diversity of different languages and cultures within the region in order to achieve a broad-based result that engenders equitable technology access.
- Socioeconomic needs assessment: Civil society can advocate for the adoption of relevant AI-related data policy by helping to match it to the socioeconomic needs in particular contexts in the region. A needs analysis of countries must be done with respect to AI technology so policy can be linked to economic solutions. AI is useless to African countries if it is not applied in a way that solves their needs.
- Multistakeholder policy advocacy: Civil society can contribute to a multistakeholder process that also includes governments, citizens, universities and the private sector to help collaboratively adapt current regulatory frameworks in such a manner that they promote digital innovation while protecting the privacy and security of citizens.
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 Such as the Global Cyber Security Capacity Centre pioneered by the University of Oxford. https://www.oxfordmartin.ox.ac.uk/cyber-security
This report was originally published as part of a larger compilation: “Global Information Society Watch 2019: Artificial intelligence: Human rights, social justice and development"
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APC Serial: APC-201910-CIPP-R-EN-P-301
ISBN APC Serial: APC-201910-CIPP-R-EN-DIGITAL-302