Data for Peacebuilding and Prevention Ecosystem Mapping: The State of Play and the Path to Creating a Community of Practice

Branka Panic (AI for Peace) & NYU Center on International Cooperation

Created 11/09/2020

Analysis, Evaluation


data for peacebuilding

How can cutting-edge approaches to data—like advanced data science methods, quantitative methods, predictive analytics, artificial intelligence (AI), machine learning (ML), and natural language processing (NLP)—help inform peacebuilding and conflict prevention?


In 2019 and 2020, the Center on International Cooperation convened researchers and practitioners for a series of workshops on Data for Peace and Security highlighting practical applications of these new approaches in the peacebuilding field. This report, launched at the first virtual dialogue, lays out the state of the field and provides recommendations on how best to grow the field effectively.

The report maps and analyzes the existing global ecosystem in the field of data for peace and prevention. It highlights multiple examples of relevant initiatives throughout the world utilizing big data, data visualization, AI, ML, image recognition, and social media listening. It also discusses technical challenges impacting all actors, such as the lack of data or lack of high-quality data, lack of access due to security reasons, and data colonialism, as well as the ethical considerations brought on by exponential technologies (security, accessibility, transparency, safety, trust, bias, and justice), and some specific challenges for data-driven approaches to peacebuilding.

Click here to access the full report.

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