On September 20th, 2024, Kluz Ventures hosted the annual Kluz Prize for PeaceTech Award Ceremony which brought together technology entrepreneurs, peacebuilders, funders, and other experts to celebrate innovative uses of technology for peace. The event featured presentations by the 2024 Kluz Prize for PeaceTech winners and a panel discussion with diverse industry experts.
Among other topics, artificial intelligence (AI) was featured as a way to foster peace, prevent violence, and rebuild societies after a conflict. From early warning systems that predict conflicts before they escalate to AI-driven platforms that accelerate humanitarian aid, the event’s speakers highlighted AI’s ability to address different phases of a conflict and promote stability. At the same time, the speakers also emphasized the ethical concerns around the use of AI and the importance of applying these technologies responsibly to avoid harm.
Image of the Kluz Prize for PeaceTech Award Ceremony by Jennifer Altman
The potential of AI for peace was echoed at the New York University (NYU) Peace Research and Education Program (PREP) and Becera event on September 19th on practical AI applications for good. There, speakers from diverse fields, including the United Nations, humanitarian organizations, tech companies, and academia, highlighted the importance of human-centered design in AI applications, the critical significance of adapting AI solutions to resource-constrained environments and global collaboration, with a particular emphasis on including voices from the Global South in shaping AI's role in peacebuilding.
In what follows we provide a series of case studies of how AI can be used to promote peace, leveraging what we learned at the Kluz Prize for PeaceTech and NYU Prep and Becera events. These case studies and applications of AI are limited to what was included in these initiatives and are not fully comprehensive. With these examples of the role of technology before, during, and after a conflict, we hope to broaden the discussion around the potential positive uses of AI in the context of today’s global challenges.
The table above summarizes the how AI may be harnessed throughout the conflict cycle and the supporting examples from the Kluz Prize for PeaceTech and NYU PREP and Becera events
(1) The Use of AI Before a Conflict
AI can support conflict prevention by predicting emerging tensions and supporting mediation efforts. In recent years, AI-driven early warning systems have been used to identify patterns that precede violence, allowing for timely interventions.
For instance, The Violence & Impacts Early-Warning System (VIEWS), developed by a research consortium at Uppsala University in Sweden and the Peace Research Institute Oslo (PRIO) in Norway, employs AI and machine learning algorithms to analyze large datasets, including conflict history, political events, and socio-economic indicators—supporting negative peace and peacebuilding efforts. These algorithms are trained to recognize patterns that precede violent conflict, using both supervised and unsupervised learning methods to make predictions about the likelihood and severity of conflicts up to three years in advance. The system also uses predictive analytics to identify potential hotspots, where specific factors—such as spikes in political unrest or economic instability—suggest a higher risk of conflict.
Image of the VIEWS Dashboard
AI-driven satellite systems can be used to identify critical natural resources that are often a source of conflict. Lunasonde, a space technology company, is using its AstroGPR™ satellite remote sensing radar to detect underground water sources that remain undetected. By creating a map of the water supply below the earth’s surface, the team aims to increase the water supply in communities facing water scarcity – with a focus on remote regions. By doing so, they can help prevent conflict over limited resources.
AI algorithms are increasingly used to monitor social media platforms and other online sources for signs of escalating tensions or planned violence. These systems can analyze vast amounts of data in real-time, detecting patterns and anomalies that might indicate impending conflict.
Panelists at the NYU event discussed the potential application of "Deliberative AI" for peace, which typically involves citizens directly in democratic processes. Panelists noted that Deliberative AI can support peacebuilding by facilitating inclusive dialogue, synthesizing diverse perspectives, and helping to identify common ground among conflicting parties. This innovative approach aims to enhance community engagement in peace processes by amplifying marginalized voices and facilitating more inclusive dialogues. Using AI to process and synthesize diverse perspectives could help find common ground in even the most polarized conflicts.
(2) The Use of AI During a Conflict
AI can enhance humanitarian efforts by improving the efficiency and responsiveness of aid distribution during conflicts. Through advanced data analytics and real-time decision-making support, AI helps organizations navigate complex and rapidly changing environments to address urgent humanitarian needs.
The Danish Refugee Council’s Data Entry and Exploration Platform (DEEP) is an online platform that provides open data and analytical tools to humanitarian organizations and other organizations supplying aid during crises. The platform uses generative AI and natural language processing (NLP) to automate several tasks such as summarizing and tagging information that can be time consuming and costly. Their objective is to support rapid humanitarian peace building after a crisis emerges.
Summary of projects developed using DEEP
AI can also help understand public sentiments during a conflict and provide real-time decision making support. AI-powered sentiment analysis tools can process large volumes of text data from various sources to gauge public opinion on peace processes and related issues. This can help policymakers understand the public mood and tailor their peacemaking approaches accordingly.
Finally, Project Didi uses AI, machine learning, natural language processing, and large language models to operationalize Zartman’s Ripeness Theory—a peacebuilding framework that traditionally has been applied qualitatively. By transforming this academic theory into a quantitative, data-driven tool, Project Didi offers a real-time method for identifying moments when conflicting parties are ready for negotiation, also known as moments of “ripeness.” In its initial phase, Project Didi applied its model to analyze terrorism, political acts, and diplomacy in Northern Ireland. The next phase will focus on the Israeli-Palestinian conflict, applying machine learning to publicly available data from news media, social media, and other sources.
(3) The Use of AI After a Conflict
AI and advanced technologies can also play a role in rebuilding societies after conflict has subsided. The aftermath of conflicts often leaves behind dangerous remnants such as landmines and unexploded ordnance (UXO), posing significant risks to civilians and hampering efforts at resettlement and reconstruction. While not directly a peacebuilding application, Aerobotics7’s advanced AI-driven drone-based solution (EAGLE A7) detects, tracks, and helps neutralize these types of hidden threats after a conflict. Aerobotics7 uses AI, sensor fusion, and autonomous systems to offer an alternative to traditional demining methods, which are often slow and put human lives at risk. The team is currently working to apply their technology to help make contaminated areas of Ukraine livable again.
Image of Aerobotics7’s AI-powered drone
The PREP event highlighted the need for context-appropriate AI tools in post-conflict settings. Unlike in commercial sectors, AI applications in these fields often need to function in low-resource, high-stakes environments. Developing AI tools that can operate effectively in resource-constrained settings is crucial for their widespread adoption in the field.
Furthermore, discussions at both events underscored the importance of ethical frameworks for AI governance in conflict-affected regions. A new paradigm of ethical data stewardship is emerging, reimagining data rights and consent in humanitarian settings with an emphasis on community values and expectations.
Lastly, both events emphasized the critical need for global collaboration in shaping the future of AI in peacebuilding. This collaboration must be truly global, ensuring that voices from the Global South are central to developing and implementing AI solutions for peace.
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These are just a few examples of how new and emerging technologies, such as AI, can foster peace and security amid conflict. Through studying these and other examples, we hope to better understand best practices around PeaceTech. Follow us on this journey by visiting our website, www.kluzprize.org, or explore the possibility of collaboration by emailing us at info@kluzprize.org.
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Thank you to Sara Marcucci for your support.