Big Data for Conflict Prevention

I had the great pleasure of co-authoring the International Peace Institute’s (IPI) unique report on “Big Data for Conflict Prevention” with my two colleagues Emmanuel Letouzé and Patrick Vinck. The study explores how Big Data may help reveal key insights into the drivers, triggers, and early signs of large-scale violence in order to support & improve conflict prevention initiatives.

The main sections of the report include:

• What Do We Mean By Big  Data for Conflict Prevention?
• What Are the Current Uses or Related Techniques in Other Fields?
• How Can Big Data Be Used for Conflict Prevention?
• What Are The Main Challenges and Risks?
• Which Principles/Institutions Should Guide this Field?

The study ties many of my passions together. Prior to Crisis Mapping and Humanitarian Technology, I worked in the field of Conflict Prevention and Conflict Early Warning. So revisiting that field of practice and literature almost 10 years later was quite a thrill given all the technological innovations that have occurred since. At the same time, plus ça change, plus c’est la même chose. The classic “warning-response gap” does not magically disappear with the rise of Big Data. This gap points to the fact that information does not equal action. Response is political. And while evidence may be plentiful, that still does not translate into action. This explains the shift towards people-centered approaches to early warning and response. The purpose of people-centered solutions is to directly empower at-risk communities to get out of harm’s way. Capacity for self-organization is what drives resilience. This means that unless Big Data facilitates disaster preparedness at the community level and real-time self-organization during disasters, the promise of Big Data for Conflict Prevention will remain largely an academic discussion.

Take the 2011 Somalia Famine, for example. “Did, in fact, the famine occur because data from this conflict-affected country were just not available and the famine was impossible to predict? Would more data have driven a better decision making process that could have averted disaster? Unfortunately, this does not appear to be the case. There had, in fact, been eleven months of escalating warnings emanating from the famine early warning systems that monitor Somalia. Somalia was, at the time, one of the most frequently surveyed countries in the world, with detailed data available on malnutrition prevalence, mortality rates, and many other indicators. The evolution of the famine was reported in almost real time, yet there was no adequate scaling up of humanitarian intervention until too late” (1). Our study on Big Data for Conflict Prevention is upfront about these limitations, which explains why a people-centered approach to Big Data is pivotal for the latter is to have meaningful impact on the prevention of violent conflict.

We look forward to your feedback and the conversations that ensue. The suggested hashtag is #ipinst. This thought piece is meant to catalyze a conversation, so your input is important to help crystalize the opportunities and challenges of leveraging Big Data for Conflict Prevention.

See also:

• How to Create Resilience Through Big Data [Link]