Image adapted by The GovLab from GFDRR Labs, Open Cities AI Challenge Dataset, Version 1.0 (Radiant MLHub), licensed under ODbL-1.0. Building outlines added by The GovLab.
At a time marked by the highest number of armed conflicts since World War II, identifying and advancing new approaches for durable peace is more critical than ever before. There is an opportunity to expand today’s peacebuilding toolkits to include emerging technologies that reflect the speed and scale of today’s dynamic and complex conflicts.
PeaceTech is an emerging field that describes “the intentional use of technologies and data to save lives, safeguard human dignity, prevent, mitigate, or recover from conflict, enable accountability, and help people to live with dignity, agency, and security.” Since the 2010s, the field has grown rapidly, bringing together disciplines including peacebuilding, humanitarian action, data science, artificial intelligence, geospatial technologies, and digital governance.
Today, PeaceTech encompasses a wide range of technologies, from AI and satellite imagery to mapping tools, digital platforms, and data analytics, that support conflict prevention, early warning, mediation, humanitarian response, accountability, and post-conflict recovery.
In this blog, we bring together a selection of academic papers, books, policy briefs, and reports on PeaceTech, primarily from 2024 to 2026, alongside one foundational reading from 2020. These readings discuss what PeaceTech is, its potential and risks in the context of today’s geopolitical landscape, and what it takes to build a responsible PeaceTech ecosystem.
Below we summarize the readings identified. The readings are presented alphabetically and highlight current debates and topics surrounding technologies for peace. We conclude with three cross-cutting takeaways.
Published in the Data & Policy special issue on Data for Peace, Damla Aras and Timothy Westlake present a case study of a pilot project conducted by the United Nations Development Programme (UNDP) and the United Nations Assistance Mission in Afghanistan (UNAMA). The project developed an augmented intelligence model, combining machine learning with human expertise, to forecast multidimensional vulnerability, including economic, financial, environmental, and essential service risks. The model achieved 70-80% predictive accuracy up to one year in advance, demonstrating how augmented intelligence can support early warning systems while keeping human judgment central to decision-making. The authors conclude by proposing an Enhanced Policy Decision (EPD) platform that integrates AI-supported forecasting with expert analysis to improve early warning and policy response.
Christine Bell gives an overview of technologies implemented in PeaceTech and explains how they work together. Using a fitness tracker as an example, Bell introduces concepts like cloud and edge computing, the Internet of Things, big data, geographic information systems, remote sensing, machine learning, artificial intelligence, and generative AI. She then connects these technologies to four areas of PeaceTech: mobile and cloud-based tools that support local initiatives, geospatial technologies that monitor conflict and provide early warnings, data analytics that help identify conflict trends, and artificial intelligence that assists with prediction, documentation, and decision-making. Bell argues that peacebuilders do not need to become technical experts, but they should understand these technologies well enough to work effectively with technical specialists, choose appropriate digital tools, and evaluate their security, infrastructure, and practical limitations in conflict settings. She concludes that digital transformation should support peacebuilding objectives rather than become an end in itself.
Common Space, a nonprofit organization that promotes open-access satellite imagery for public-good uses, published a report on the role of satellite imagery in humanitarian response. Drawing on survey responses from 241 respondents representing 195 organizations, along with case studies from organizations including the Associated Press, MapAction, the Human Rights Center, and the World Food Programme, the report finds broad demand for open high-resolution imagery. Respondents identified restrictive licensing as the primary barrier to humanitarian use (61%) and emphasized the need for a system that provides reliable access, transparent community-guided governance, and tools that make imagery immediately usable for humanitarian response.
Nathan Coyle and Mamadou Bodian argue that the future of PeaceTech depends on shifting authority over data, technology, and governance toward African institutions and communities. They argue that many AI-enabled PeaceTech tools rely on data, infrastructure, and governance systems developed outside Africa, limiting their legitimacy and relevance in conflict-affected settings. To address these challenges, the authors emphasize the need for African actors to have greater control over how conflict data is collected, stored, interpreted, and used. In their view, stronger regional infrastructure, community ownership, and cooperation among local organizations would make PeaceTech more legitimate, more accurate, and more responsive to local realities, rather than reproducing existing global power asymmetries.
Andreas T. Hirblinger examines the growing use of digital technologies in peacebuilding across different stages of conflict, from conflict prevention and mitigation to peace mediation and longer-term conflict transformation. Drawing on research in South Sudan, Sri Lanka, and Northern Ireland, the book examines efforts to counter harmful speech on social media, localized early warning and response, AI-enhanced mediation and dialogue, and online interactions that can contribute to political change and reconciliation. Hirblinger argues for moving beyond a focus on individual digital tools to consider how technologies are socially embedded and how digital peacebuilding is shaped by relationships between people, technologies, institutions, and political contexts. He develops the concept of “apomediated peacebuilding” to explain how knowledge about conflict and peace is increasingly shaped through networks of people and digital technologies. The book ultimately argues for a more critical approach to digital innovation that considers how these socio-technical relationships affect the prospects for conflict transformation.
Andreas Hirblinger and Suda Perera argue that PeaceTech should not be viewed as a technology-driven solution to conflict. Instead, they maintain that digital tools should support locally defined peacebuilding practices and reflect the social, political, and cultural contexts in which they are used, rather than imposing universal or technology-centered approaches. Drawing on the decolonial concept of the pluriverse, a “world in which many worlds fit,” they argue that peacebuilding should recognize multiple ways of knowing, being, and practicing peace rather than reproduce a single, technology-centered model. They argue that effective PeaceTech depends on recognizing different ways of understanding and building peace, with technology serving as a tool to support local priorities rather than shaping peacebuilding itself.
The International Panel on the Information Environment (IPIE), an independent scientific organization based in Switzerland, published a report examining how AI is being used in peacebuilding. Drawing on approximately 600 academic articles, policy reports, and other publications, the authors identify six applications of AI in peacebuilding: conflict prediction, conflict mapping, digital inclusion and citizen engagement, pro-social engagement, mediation and negotiation, and cross-cutting risks and limitations. The report finds that most AI applications remain in pilot stages, with limited evidence of their real-world impact, and emphasizes that AI should support human judgment. It also warns that AI is a dual-use technology that can enable surveillance, misinformation, and polarization if deployed without appropriate safeguards, and recommends prioritizing human rights and stronger policy and ethical guidance for AI deployment.
In this editorial introducing the Data & Policy special collection on Data for Peace, Innar Liiv et al. synthesize nine peer-reviewed papers on how novel data sources and emerging technologies can support peacebuilding. The authors show how tools including machine learning, network analysis, specialized text classifiers, and large-scale predictive analytics can deepen understanding of conflict dynamics, strengthen early warning systems, support conflict prevention, facilitate mediation and consensus-building, assist reconstruction, and improve the evaluation and monitoring of peacebuilding activities.
Across the collection, they argue that data-driven peacebuilding must be grounded in human rights, local knowledge, participatory engagement, and strong governance to avoid reproducing the harms it seeks to address. They conclude that the promise of data for peace lies not only in what technology can measure or predict, but in how it can help societies co-create more just and peaceful futures.
Roger Mac Ginty and Pamina Firchow question the assumption that collecting more data quickly or treating it as inherently objective automatically fosters peace. Instead, they argue that data is shaped by power, politics, and context, and that overreliance on technical evidence can obscure local knowledge and the social and political realities of conflict. To address these challenges, the authors recommend five principles for responsible data use in peacebuilding: critically assessing whether new data collection is necessary, using data to empower communities, recognizing the limits of quantitative evidence, maximizing the value of existing data, and applying conflict-sensitive “do no harm” principles throughout data collection and analysis.
Panic, Branka, and Paige Arthur. AI for Peace. Boca Raton, FL: CRC Press, 2024.
Branka Panic and Paige Arthur present artificial intelligence as a tool that can strengthen peacebuilding when it is applied responsibly and ethically. Rather than focusing on AI’s military uses, they examine its potential to support conflict prevention through applications such as early warning systems, countering hate speech, human rights investigations, humanitarian response, and climate-related conflict analysis. The authors argue that these benefits depend on strong ethical governance, emphasizing principles such as fairness, transparency, accountability, privacy, inclusivity, and meaningful human oversight. They maintain that AI should complement rather than replace human decision-making and advocate an “ethics in crisis” approach that enables AI to be deployed quickly in conflict settings while maintaining ethical standards.
In this policy brief, Lisa Schirch examines how digital technologies are reshaping peacebuilding. Schirch traces the evolution of digital peacebuilding through five generations: (1) basic information and communication technologies, (2) crowdsourcing and citizen participation, (3) responses to the weaponization of social media and cyber conflict, (4) advocacy for technology governance and regulation, and (5) digital social movements that promote responsible online engagement. Schirch outlines several examples, including Ushahidi’s crowdsourced election violence monitoring in Kenya, and concludes with 25 areas where digital technologies can support peacebuilding. These include early warning, election monitoring, and dialogue. Schirch emphasizes the need to address surveillance and privacy risks to ensure digital technologies support rather than undermine peacebuilding.
Image developed by The GovLab, adapted from Lisa Schirch, 25 Spheres of Digital Peacebuilding and PeaceTech
Stefaan Verhulst and Artur Kluz argue that PeaceTech remains underfunded despite its potential to strengthen peacebuilding efforts. The authors discuss the rapidly growing investment in defense technologies with comparatively limited funding for peacebuilding. They argue that governments, philanthropies, investors, and the private sector should treat PeaceTech as a strategic investment by expanding funding, supporting innovation ecosystems, and scaling technologies that help predict violence, improve humanitarian response, verify ceasefires, and strengthen post-conflict recovery.
Martin Wählisch and Felix Kufus argue that while PeaceTech can strengthen conflict prevention, dialogue, and peacebuilding, its effectiveness is constrained by five structural dilemmas: the potential for surveillance, institutional inertia, the gap between early warning and action, dependence on private technology companies, and the marginalization of local knowledge. The authors argue that these tensions reflect underlying questions of power, governance, and accountability rather than technical shortcomings, and contend that PeaceTech should be understood as a political and ethical field. Among other recommendations, the authors call for embedding digital tools in locally grounded peacebuilding processes, strengthening community ownership of data, and improving algorithmic accountability.
Table from “Structural Dilemmas of PeaceTech: AI, Power, and Peacebuilding in the Digital Age,” Peacebuilding (2026) summarizing five recurring tradeoffs in PeaceTech.
Cross-Cutting Takeaways
A few key takeaways across these readings:
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AI is opening new opportunities for peacebuilding, but more evidence is needed to understand its long-term impact: Several readings examine how AI and machine learning are being applied to conflict forecasting, early warning, mapping, mediation, and humanitarian response. At the same time, many applications remain in pilot or experimental stages, highlighting the need for stronger evidence of what works and what does not work in practice as well as how to ensure it is applied responsibly.
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Strong governance models are critical: The readings emphasize that technology alone does not create peace. The design, governance, and deployment of PeaceTech, including transparency, accountability, privacy protections, community participation, and local ownership, shape whether technologies strengthen peacebuilding or reinforce surveillance, bias, exclusion, or unequal power dynamics.
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Access and transparency shape who benefits from PeaceTech: Several readings highlight barriers that determine who can use technologies and data for peacebuilding, including restrictive licensing, unequal access to data and technical capacity, limited transparency, and dependence on private technology providers. Expanding access to peace technologies while establishing local agency over clear rules for data ownership, accountability, and responsible use is integral to building a more inclusive PeaceTech ecosystem.