Policy by the Numbers: Data-driven peacebuilding

Data-driven peacebuilding

Wednesday, May 9, 2012

The very nature of peace negotiations has fundamentally changed. Once an art involving a select few and practiced behind closed doors, negotiations are now broader social conversations that include the voices of diaspora. Except for cases of the most draconian censorship, high-level stakeholders in peace negotiations have very little control over this social hubbub, out of which vital concerns, critiques, ideas, and alternatives can emerge. Indeed, the very agenda of official negotiations can now be contested and debated in real time on the web. Thanks to reams of official texts, a plethora of social media updates, and mainstream media coverage, today’s peacebuilding and peacekeeping efforts generate, respond to, and are informed by massive amounts of data. We must forgive the negotiator or peacekeeper trained in traditional methods for feeling helpless and confused. This is a complex new world for peacebuilding, and one that is in constant flux. As more data becomes available, new insights threaten and even overturn staid assumptions. For example, an August 2011 Fast Company story reports on the US Department of Defense’s plans for the Empirical Studies of Conflict (ESOC) archive, funded by an $8.6 million grant from DoD. ESOC’s mission is to make available to academics previously hard-to-access data on global conflict. Fast Company reports, “ESOC discovered a previously unnoticed—and counterintuitive—correlation between unemployment rates and politically motivated violence,” where higher unemployment was associated with less politically motivated violence.

Sanjana Hattouwa's TED talk on citizen journalism.Contentious as it may seem, using data analysis to challenge assumptions and even predict outcomes is a growing trend. For example, The Grill’s computer modeling has been used globally to predict the outcomes of conflict. The PAX initiative “plans to launch a global digital system to give early warning of wars and genocide.” And the non-profit organization Benetech has been contracted by the likes of Amnesty International and Human Rights Watch to address controversial geopolitical issues via data science. Of note, in an exhaustive analysis of over 80 million documents from the secret files of Guatemala’s National Police, Benetech’s scientists employed random sampling to confirm that genocide was committed against the Mayan population during the country’s civil conflict, which lasted from 1960 to 1996. Image analysis is another area with potential data-intensive peacebuilding applications. The LRA Crisis Tracker combines images with a number of sources, including on-the-ground and situation reports from the UN system, to present a temporal and geospatial representation of one of the world’s most brutal terrorist groups in one of the world’s most unstable regions. The visual impact of this representation compels the viewer to investigate the conflict and ways to help, which may lead to meaningful and early intervention in crimes against humanity. All of these early examples hint at data’s potential to meaningfully impact the domain of peacebuilding and peacekeeping, but we cannot simply assume that predictive modeling, random sampling, and other “Big Data” applications are automatic, easy solutions. Figuring out how to effectively leverage massive amounts of data to save lives and build peace is going to be a challenge—but it is one worth taking on. Sanjana Hattotuwa is a TED Fellow and Special Advisor with the ICT4Peace Foundation.

Policy by the Numbers

Data-driven peacebuilding

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