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A ranger displays using the EarthRanger conservation platform at the Ol Pejeta Conservancy in Laikipia national park near Nanyuki, Kenya, May 22, 2019. Picture taken May 22, 2019. REUTERS/Baz Ratner
A ranger displays using the EarthRanger conservation platform at the Ol Pejeta Conservancy in Laikipia national park near Nanyuki, Kenya, May 22, 2019. Picture taken May 22, 2019. REUTERS/Baz Ratner
A ranger uses the EarthRanger conservation platform at the Ol Pejeta Conservancy in Laikipia national park near Nanyuki, Kenya, on May 22, 2019. (REUTERS/Baz Ratner)

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. Though 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. These limits reflect both the novelty and constraints of existing AI-enabled technology.  

Artificial intelligence and armed conflict in Africa 

Artificial intelligence (AI), at its most basic, leverages computing power “to simulate the behavior 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 Michael Horowitz argues, “a general-purpose technology with a multitude of applications,” like the internal combustion engine, electricity, or the internet. And as AI applications proliferate to military uses, it threatens to change the nature of warfare. According to the ICRC, “AI and machine-learning systems could have profound implications for the role of humans in armed conflict, especially in relation to: increasing autonomy of weapon systems and other unmanned systems; new forms of cyber and information warfare; and, more broadly, the nature of decision-making.”   

In at least two respects, AI is already affecting the dynamics of armed conflict and violence in Africa. First, AI-driven surveillance and “smart” policing platforms are being used to respond to attacks by violent extremist groups and organized criminal networks. Second, the development of AI-powered drones is beginning to influence combat operations and battlefield tactics.  

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. In Nairobi, Chinese tech giant Huawei has helped build an advanced surveillance system, and in Johannesburg automated license plate readers have enabled authorities to track violent, organized criminals with suspected ties to the Islamic State. Although such systems have significant limitations (more on this below), they are proliferating across Africa.   

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. A small, motion-activated “poacher cam” relies on an algorithm to distinguish between humans and animals and has contributed to at least one arrest. It’s not difficult to imagine how such a system might be repurposed for counterinsurgency or armed conflict, with AI-enabled surveillance and monitoring systems deployed to detect and deter armed insurgents.  

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. According to a United Nations report, the Kargu-2 represented a lethal autonomous weapons system because it had been “programmed to attack targets without requiring data connectivity between the operator and munition.” Although other experts have instead classified the Kargu-2 as a loitering munition, its use in combat in northern Africa nonetheless points to a future where AI-enabled weapons are increasingly deployed in armed conflicts in the region.  

Indeed, despite global calls for a ban on similar weapons, the proliferation of systems like the Kargu-2 is likely only beginning. Relatively low costs, tactical advantages, and the emergence of multiple suppliers have led to a booming market for low-and-mid tier combat drones currently being dominated by players including Israel, China, Turkey, and South Africa. Such drones, particularly Turkey’s Bakratyar TB2, have been acquired and used by well over a dozen African countries.   

While the current generation of drones by and large do not have AI-driven autonomous capabilities that are publicly acknowledged, the same cannot be said for the next generation, which are even less costly, more attritable, and use AI-assisted “swarming technology” to make themselves harder to defend against.  In February, the South Africa-based Paramount Group announced the launch of its “N-RAVEN” UAV system, which it bills as “a family of autonomous, multi-mission aerial vehicles featuring next-generation ‘swarm’ technologies.” The N-RAVEN will be able to swarm in units of up to twenty and is “designed for technology transfer and portable manufacture within partner countries.” These features are likely to be attractive to African militaries.  

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 fueled significant increases, overwhelming any progress that has resulted from governments adopting cutting-edge technology.  

This is because, in the first place, armed conflict is a human endeavor, with many factors that influence its outcomes. Even the staunchest defenders of AI-driven solutions, such as Huawei Southern Africa Public Affairs Director David Lane, admit that they cannot address the underlying causes of insecurity such as unemployment or inequality: “Ultimately, preventing crime requires addressing these causes in a very local way.” 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.  

In the second place, the aspects of armed conflict that AI seems most likely to disrupt—remote intelligence-gathering capabilities and air power—are technologies that enable armies to keep enemies at arms-length and win in conventional, pitched battles. AI’s utility in fighting insurgencies, in which non-state armed actors conduct guerilla attacks and seek to blend in and draw support from the population, is more questionable. To win in insurgencies requires a sustained on the ground presence to maintain order and govern contested territory. States cannot hope to prevail in such conflicts by relying on technology that effectively removes them from the fight.   

Finally, the use of AI to fight modern armed conflict remains at a nascent stage. To date, the prevailing available evidence has documented how state actors are adopting AI to fight conflict, and not how armed non-state actors are responding. Nevertheless, states will not be alone in seeking to leverage autonomous weapons. Former African service members speculate that it is only a matter of time before “before the deployment of ‘swarms’ or clusters of offensive drones” by non-state actors in Africa, given their accessibility, low costs, and existing use in surveillance and smuggling.  Rights activists have raised the alarm about the potential for small, cheap, swarming “slaughterbots,” that use freely available AI and facial recognition systems to commit mass acts of terror.  This particular scenario is controversial, but according to American University’s Audrey Kurth Cronin, “it is both technologically feasible and consistent with classic patterns of diffusion.”  

The AI armed conflict evolution 

These downsides and risks suggest the continued diffusion of AI is unlikely to result in the revolutionary changes to armed conflict suggested by some of its more ardent proponents and backers. Rather, modern AI is perhaps best viewed as continuing and perhaps accelerating long-standing technological trends that have enhanced sensing capabilities and digitized and automated the operations and tactics of armed actors everywhere. 

For all its complexity, AI is first and foremost a digital technology, its impact dependent on and difficult to disentangle from a “technical triad” of “data, algorithms, and computing power.” The impact of AI-powered surveillance platforms, from the EarthRanger software used at Liwonde to Huawei-supplied “smart policing” platforms, isn’t just a result of machine-learning algorithms that enable human-like reasoning capabilities, but also on the ability to store, collect, process collate and manage vast quantities of data. Likewise, as pointed out by analysts such as Kelsey Atherton, the Kargu 2 used in Libya can be classified as an autonomous loitering munition such as Israel’s Harpy drone. The main difference between the Kargu 2 and the Harpy, which was first manufactured in 1989, is where the former uses AI-driven image recognition, the latter uses electro-optical sensors to detect and hone in on enemy radar emissions.  

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.  

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.  

Incrementally and in concert with other emerging technologies, AI is transforming the tools and tactics of warfare. Nevertheless, experience from Africa suggests that humans will remain the main actors in the drama of modern armed conflict.  

Nathaniel Allen is an assistant professor with the Africa Center for Strategic Studies at National Defense University and a Council on Foreign Relations term member.
Marian “Ify” Okpali is a researcher on cyber policy and an academic specialist at the Africa Center for Strategic Studies at National Defense University. The opinions expressed in this article are those of the authors. 

Microsoft provides financial support to the Brookings Institution, a nonprofit organization devoted to rigorous, independent, in-depth public policy research.