Big Brother: A critique of the 4th Industrial Revolution
Investment in transportation, agriculture, healthcare, and education should take priority over investment in surveillance technologies.
While artificial intelligence (AI), a signature technology of the 4th Industrial revolution (4IR), has been projected to transform the socioeconomic landscape of Africa by creating new efficiencies in the public and private sectors, it has some way to go to live up to this hope. Instead of exciting public-led applications such as the use of AI by the National Health Service (NHS) in the United Kingdom to fight diseases, the most promising applications of AI in Africa are, not surprisingly, private sector-dominated. From behemoths like Google and Facebook to smaller startups, private firms are attempting to create impact at scale in Africa through applications such as chatbots in healthcare and the financial industry and AI drone-empowered disease surveillance in agriculture. As I’ve explained elsewhere, African countries will falter in their quest for an AI-led 4IR economic boost if they neglect investments in foundational 2nd and 3rd IR technologies such as efficient transport systems, power grids, and reliable broadband connections for a critical mass of the population. The 4IR does not happen in a bubble; it feeds upon successful integration with 2nd and 3rd IR technologies. Little wonder, then, that the most visible public-private partnership in AI deployment for societal good during the Covid-19 pandemic was its use for disease surveillance in Johannesburg — within Africa’s most advanced economy where 2nd and 3rd IR technologies are better developed than in most of Africa.
A huge part of AI’s ineffectual public sector-led impact in Africa is poor statistical capacity, which might be a good intervention point for AI capacity-building grants for the continent. Government and other public statistical agencies are poorly equipped to keep accurate and granular records in critical sectors such as economic indicators, health data, environmental data, and even transportation data. AI systems feed on large, accurate, and digitized datasets to produce insights for development, and in Africa today, the organizations with the capacity to harness such data power are typically in the private sector. We probably should not expect a replica of a UK NHS intervention in Africa anytime soon. There doesn’t seem to be enough political will to build efficient public statistical systems in Africa. The only exception seems to be in biometric surveillance.
It seems ironic that one of the most extensive public sector-led applications of AI in Africa is the implementation of biometric surveillance technology. Many African cities have become urban experiments in the deployment of AI-powered biometric surveillance. A few examples will suffice. In 2019, Police in Uganda bought $126 million worth of CCTV surveillance technology from telecommunications firm Huawei to help control crime in Kampala, the country’s capital. In Nairobi, Kenya, Huawei has also implemented a new communications network which links 1,800 surveillance cameras with 195 police bureaus and 7,600 police officers. In South Africa, the Department of Homeland Security’s (DHA) draft identity management policy proposed that biometric information recorded by numerous surveillance cameras installed in public spaces across the country will be linked to the DHA’s population register and this database shared with the Police. In Madagascar, Huawei is also installing over 1,000 CCTV cameras in the country’s major cities. Other African countries which have deployed surveillance technology include Algeria, Botswana, Côte d’Ivoire, Egypt, Ghana, Malawi, Nigeria, Rwanda, South Africa, Tanzania, Uganda, Zambia, and Zimbabwe.
A conspicuous thread linking many of these projects is Huawei, the Chinese telecommunications giant. Many of these surveillance projects are linked with Huawei’s safe cities project, a Chinese-led global partnership in security infrastructure. China has been a major partner in Africa’s economic renaissance, having built about 70% of the 4G telecommunications infrastructure on the continent. The Infrastructure Consortium for Africa estimates China’s contribution to infrastructure development financing at $25.7 billion in 2018, about a quarter of the total $100.8 billion committed to infrastructure projects. China is also emerging as perhaps Africa’s most important trading partner, with an estimated $200 billion worth of trade in 2019.
China will remain an important partner for Africa. Nevertheless, it does not seem right that in the poorest continent on the planet, the most visible, public-led 4IR implementation is in security — and is simply a tool to maintain authoritarianism in many countries. Security is not the most urgent problem confronting Africa. Indeed, there are those who would argue that Africa’s security challenges are exacerbated by poor governance. The same local political will that has brought about these security investments in Africa can also be brought to ensure that 4IR impacts are more strongly felt in public sectors such as transportation, agriculture, healthcare, education — probably Africa’s greatest needs. A good place to start might be in partnerships to strengthen public statistical capacities and international knowledge transfers critical for the success of AI applications in Africa. The China-African partnership might be more meaningful if some of the agenda setting is African and recognizes that implementing effective public sector AI applications which improve the livelihoods of ordinary people will improve security better than a thousand biometric surveillance systems.
