Author : Nathaniel Allen and Ify Okpali
Type of publication : Special report
Date of publication : April 2022
Even as the world’s leading militaries race to adopt artificial intelligence in anticipation of future great power war, security forces in one of the world’s most conflict-prone regions are opting for a more measured approach.
In Africa, AI is gradually making its way into technologies such as advanced surveillance systems and combat drones, which are being deployed to fight organized crime, extremist groups, and violent insurgencies. Although the long-term potential for AI to impact military operations in Africa is undeniable, AI’s impact on organized violence has so far been limited.
Artificial intelligence and armed conflict in Africa
Artificial intelligence (AI), at its most basic, leverages computing power “to simulate the behaviour of humans that requires intelligence.” Artificial intelligence is not a military technology like a gun or a tank. It is rather, as the University of Pennsylvania’s Mark Horowitz argues, “a general-purpose technology with a multitude of applications,” like the internal combustion engine, electricity, or the internet.
AI is perhaps most widely used in Africa in areas with high levels of violence to increase the capabilities and coordination of law enforcement and domestic security services. For instance, fourteen African countries deploy AI-driven surveillance and smart-policing platforms, which typically rely on deep neural networks for image classification and a range of machine learning models for predictive analytics.
AI-driven systems are also being deployed to fight organized crime. At Liwonde National Park in Malawi, park rangers use EarthRanger software, developed by the late Microsoft co-founder, Paul Allen, to combat poaching using artificial intelligence and predictive analytics. The software detects patterns in poaching that the rangers might overlook, such as upticks in poaching during holidays and government paydays.
In addition to the growing use of AI within surveillance systems across Africa, AI has also been integrated into weapon systems. Most prominently, lethal autonomous weapons systems use real-time sensor data coupled with AI and machine learning algorithms to “select and engage targets without further intervention by a human operator.” Depending on how that definition is interpreted, the first use of a lethal autonomous weapon system in combat may have taken place on African soil in March 2020. That month, logistics units belonging to the armed forces of the Libyan warlord Khalifa Haftar came under attack by Turkish-made STM Kargu-2 drones as they fled Tripoli.
AI is perhaps most widely used in Africa in areas with high levels of violence to increase the capabilities and coordination of law enforcement and domestic security services
AI’s limits, downsides, and risks
Though AI may continue to play an increasing role in the organizational strategies, intelligence-gathering capabilities, and battlefield tactics of armed actors in Africa and elsewhere, it is important to put these contributions in a broader perspective. AI cannot address the fundamental drivers of armed conflict, particularly the complex insurgencies common in Africa. African states and militaries may overinvest in AI, neglecting its risks and externalities, as well as the ways in which AI-driven capabilities may be mitigated or exploited by armed non-state actors.
AI is unlikely to have a transformative impact on the outbreak, duration, or mitigation of armed conflict in Africa, whose incidence has doubled over the past decade. Despite claims by its makers, there is little hard evidence linking the deployment of AI-powered smart cities with decreases in violence, including in Nairobi, where crime incidents have remained virtually unchanged since 2014, when the city’s AI-driven systems first went online.
The same is true of poaching. During the COVID-19 pandemic, fewer tourists and struggling local economies have fuelled significant increases, overwhelming any progress that has resulted from governments adopting cutting-edge technology.
No AI algorithm can prevent poverty or political exclusion, disputes over land or national resources, or political leaders from making chauvinistic appeals to group identity. Likewise, the central problems with Africa’s militaries—endemic corruption, human rights abuses, loyalties to specific leaders and groups rather than institutions and citizens, and a proclivity for ill-timed seizures of power—are not problems that artificial intelligence alone can solve.
The AI armed conflict evolution
The diffusion of AI across Africa, like the broader diffusion of digital technology, is likely to be diverse and uneven. Africa remains the world’s least digitized region. Internet penetration rates are low and likely to remain so in many of the most conflict-prone countries. In Somalia, South Sudan, Ethiopia, the Democratic Republic of Congo, and much of the Lake Chad Basin, internet penetration is below 20%. AI is unlikely to have much of an impact on conflict in regions where citizens leave little in the way of a digital footprint, and non-state armed groups control territory beyond the easy reach of the state.
AI cannot address the fundamental drivers of armed conflict, particularly the complex insurgencies common in Africa. African states and militaries may overinvest in AI, neglecting its risks and externalities, as well as the ways in which AI-driven capabilities may be mitigated or exploited by armed non-state actors
Taken together, these developments suggest that AI will cause a steady evolution in armed conflict in Africa and elsewhere, rather than revolutionize it. Digitization and the widespread adoption of autonomous weapons platforms may extend the eyes and lengthen the fists of state armies.
Non-state actors will adopt these technologies themselves and come up with clever ways to exploit or negate them. Artificial intelligence will be used in combination with equally influential, but less flashy inventions such as the AK-47, the nonstandard tactical vehicle, and the IED to enable new tactics that take advantage or exploit trends towards better sensing capabilities and increased mobility.
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