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AI Against Terror: Harnessing Technology to Combat Terrorism in the Horn of Africa

AI Against Terror: Harnessing Technology to Combat Terrorism in the Horn of Africa
27th September 2024 Abraham Ename Minko
In Insights

Introduction

Countries in the Horn of Africa, including Somalia, Ethiopia, Eritrea, and Djibouti, have long faced challenges from terrorism and violent extremism. Groups like Al Shabaab have taken advantage of the region’s instability by spreading propaganda online and carrying out deadly attacks. Just in August 2024, Al Shabaab struck a beach in Mogadishu with a suicide bomb, killing at least 37 and injuring more than 200.  Their ability to recruit, radicalise and mobilise people locally and globally demonstrates how modern terrorist organizations can adapt to situations. They don’t just rely on violence, they use online platforms to promote their agenda and coordinate activities effectively.

In today’s era, terrorism has evolved as groups use the internet to connect with an audience. Online platforms offer a ground for these groups to share their beliefs, attract members and raise funds. For instance, Al Shabaab has leveraged social media sites like Twitter and Telegram to spread their message drawing supporters and operatives from outside the Horn of Africa region. This shift towards tactics highlights the need for strategies, beyond traditional law enforcement or military actions.

Artificial intelligence (AI) has become a tool in the fight against terrorism, providing capabilities for analysing data, detecting threats, and strategically intervening. AI’s ability to process large amounts of data in time offers an advantage in identifying and preventing threats before they emerge, giving it a crucial edge in combating terrorism.

Moreover, the socio-political environment of the Horn of Africa complicates terrorism efforts. The region’s political instability, economic challenges, and social issues create a ground for extremist ideologies to flourish. Local grievances often align with jihadist narratives making groups like Al Shabaab more resilient and attractive to marginalised populations. The interconnected nature of global factors calls for an approach to counterterrorism where AI can make a significant impact.

By leveraging AI technologies, governments and security agencies can enhance intelligence, improve surveillance, and disrupt propaganda efforts. This Insight explores the use of AI to combat terrorism in the Horn of Africa, examining the roles of relevant groups and offering recommendations for tech companies and policymakers.

Advanced Threat Detection and Surveillance

AI technology can transform the methods used by intelligence agencies in detecting and monitoring activities in regions like the Horn of Africa, where groups such as Al Shabaab operate with sophisticated tactics. Using machine learning algorithms and natural language processing (NLP), vast amounts of data gathered from sources like media intercepted communications and digital platforms can be analysed to uncover patterns and signals that may indicate planning and recruitment efforts. For example, Al Shabaab has been known to use messaging applications like Telegram to coordinate attacks and spread their propaganda. Conventional surveillance techniques, where targets are physically followed or watched, AI can automate the analysis of communication patterns flagging unusual spikes in activity that could signify an impending threat.

A prime illustration of AI’s effectiveness in threat detection lies in its application for tracking and forecasting the movements of operatives. In an instance from 2019, Kenyan security forces teamed up with partners to employ AI-driven analysis in mapping out the networks linked to Al Shabaab members involved in the DusitD2 hotel attack in Nairobi. By scrutinising communication metadata and social media engagements, AI algorithms successfully pinpointed operatives and predicted their actions, resulting in several successful interventions. This scenario underscores how AI can enrich awareness by providing intelligence that conventional approaches might miss.

Furthermore, artificial intelligence (AI) has the potential to greatly enhance the monitoring of groups’ online radicalisation efforts. AI can play a role, in combatting activities by identifying and flagging extremist content for removal. Companies like Facebook and YouTube have already started using AI to detect and eliminate material, although the technology is still advancing.      

Despite these advancements, incorporating AI in threat detection and monitoring poses challenges. There are considerations surrounding privacy issues and the potential misuse of surveillance tools. For instance, while AI tools used to track terrorists could be beneficial, governments could exploit them to suppress opposition. Additionally, the effectiveness of AI systems hinges on the quality and diversity of data they are trained on. In regions like the Horn of Africa where data infrastructure may be lacking, ensuring accurate and comprehensive data collection presents an obstacle.

Improving Border Security and Tracking Movement

Enhancing border security and monitoring individuals’ movements play a role in combating terrorism in the Horn of Africa, an area marked by borders and vast unguarded territories. AI-powered surveillance systems, which include drones equipped with facial recognition technology and predictive analytics, can greatly bolster border security. For instance,      in Somalia and Kenya, where groups like Al Shabaab frequently cross borders with operatives and supplies, AI technology can analyse real-time drone footage to detect activities or patterns that human operators might overlook. The use of recognition at checkpoints can help identify known terrorists or individuals of interest, facilitating responses based on solid information. 

There are three cases particularly illustrative of the use of AI to enhance border security in the region.

  1.  The partnership between the Kenyan government and the European Union to      monitor activities along the Kenya-Horn of Africa borders. AI systems process data from sources such as surveillance cameras, drones, and social media to anticipate and prevent movements, across borders by organizations.
  2. In 2020, drones powered by AI were used to monitor the flow of goods and people along the border. This stopped attempts to smuggle weapons meant for Al Shabaab. The use of AI technologies has made patrolling and response tactics more effective, resulting in a drop in terrorist activities at the border.
  3. Over in Ethiopia, the introduction of AI at border checkpoints has also enhanced the detection and monitoring of movements. For instance, the Ethiopian government has employed AI to analys     e data gathered at border crossings to track individuals suspected of ties with terrorist groups     . By spotting irregular travel patterns and pinpointing risks, this system helped capture high-profile operatives planning attacks within the nation.      

Despite the progress AI brings to border security and movement monitoring, it comes with its set of obstacles and moral dilemmas. The use of facial recognition technology raises privacy concerns, in regions where data protection regulations may be lacking or inadequate. Errors in identification can result in detentions and violations of rights, exacerbating existing tensions that extremist groups exploit.

Moreover, the efficiency of AI systems in border security relies heavily on the accessibility and reliability of data. In regions lacking infrastructure and data gathering capabilities, there exists a risk of biased data leading to ineffective or even harmful outcomes. Furthermore, implementing AI for border security demands investments in technology and training. Many nations in the Horn of Africa face limitations that pose challenges in adopting and sustaining AI systems. Collaborative efforts between governments and international bodies like the United Nations or the African Union are crucial for bridging this gap by facilitating the transfer of technology and expertise required for the successful implementation of AI-driven border security measures.

AI holds promise in bolstering border security and monitoring activities in the Horn of Africa, offering sophisticated tools for surveillance and response to threats. However, it is imperative to address considerations and practical hurdles to ensure the responsible and efficient use of these technologies, thereby promoting regional stability and security.

Addressing Online Radicalisation and Propaganda

Effectively countering radicalisation and propaganda plays a role in combating violent extremism in the Horn of Africa where groups such as Al Shabaab have adeptly leveraged digital platforms to disseminate their ideologies and recruit new members. The rise of media and encrypted messaging platforms has enabled these organizations to expand their reach circumvent security measures and foster a sense of belonging among isolated individuals. AI technology can play a role, in addressing these issues by automating the identification of material and bolstering efforts to create alternative narratives.

Al Shabaab’s online presence is meant to attract and radicalize supporters. Through videos, articles, and social media posts they disseminate messages that are often tailored to exploit grievances and socio-political concerns. AI algorithms, those leveraging natural language processing (NLP) can sift through amounts of online content to pinpoint extremist rhetoric. Major platforms like Facebook and YouTube have begun using AI to detect and delete terrorist-promoting content. Nevertheless, this remains a challenge as extremist factions continuously adapt their strategies to evade detection. In turn, AI systems must stay updated to identify communication patterns and propaganda tactics.

A notable instance showcasing the impact of AI is the partnership between the African Union and technology firms, in countering Al Shabaab propaganda. AI tools have been employed to monitor media platforms for material flagging accounts that disseminate radical messages.

This strategy has been effective in disrupting the connections between these groups, making it harder for them to recruit members. Moreover, using AI-powered sentiment analysis can offer insights into the feelings of individuals engaging with content enabling targeted interventions. This approach aids in pinpointing individuals to radicalisation. Offering them alternative perspectives and support before they fully embrace extremist beliefs.

Nevertheless, leveraging AI to combat radicalis ation comes with challenges. One key concern is finding a balance between security and privacy. Extensive monitoring of behaviour raises worries about surveillance and potential violations of rights. There is also the issue where valid content may be mistakenly identified as nefarious material, potentially restricting freedom of expression. To address these issues effectively, it is crucial to establish guidelines and oversight mechanisms (governments should implement them and enforce them for citizens) to ensure the transparent use of AI tools. Collaboration with civil society organizations and human rights groups can aid in developing guidelines that uphold both security requirements and individual liberties.

Moreover, crafting counternarratives necessitates an understanding of local contexts and the drivers behind extremism. AI can support this effort by analysing data to pinpoint arguments and messages related to extremism that might impact people. 

However, it is important to involve communities and trusted individuals in creating and spreading these narratives to ensure they are genuine and impactful. For instance, programs that enlist extremists to share their stories and how they turned away from beliefs can be very influential. AI can assist in identifying and promoting these voices so they reach the people. Using AI has the potential to combat radicalisation and propaganda by automatically detecting extremist content and improving the creation of effective counter-narratives. Still, it’s crucial to handle the implementation of these technologies to address issues and make sure they respect individual rights. By combining technology with community involvement and support, the Horn of Africa can better tackle the terrorist groups’ digital tactics and lessen the risk of radicalisation.

Conclusion

In summary, incorporating AI technology into counter strategies in the Horn of Africa shows great potential for boosting security and stability in the area. AI can bring about improvements in enhanced threat detection, strengthened border control, and effective anti-radicalisation initiatives. Nevertheless, it is important to implement AI ethically and collaborate with governments, technology firms, and civil society. By using AI, the Horn of Africa stands to make progress in the fight against terrorism, ensuring a safer and more stable future, for its inhabitants.

Abraham Ename Minko is a senior researcher and policy analyst in Peace, Security, and Conflict Resolution. He is completing a Ph.D. in Political Science and International Relations at Istanbul University in Türkiye. His research interests are UN Peace Operations, Terrorism and Counter Violent Extremism, Peace and Conflict Resolution, Mediation and Negotiation, International Humanitarian Law and Armed Conflicts, Peacekeeping, and Peacebuilding. 

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