The UN is becoming increasingly data-driven. Until recently, data-driven initiatives have mainly been led by individual UN field missions, but with Antonio Guterres, the new Secretary-General, a more centralized approach is being embarked on. With a trend towards the use of data to support the work of UN staff, the UN is likely to soon rely on systematic data analysis to draw patterns from the information that is gathered in and across UN field missions. This paper is based on UN peacekeeping data from the Joint Mission Analysis Centre (JMAC) in Darfur, and draws on interviews conducted in New York, Mali and Sudan. It will explore the practical and ethical implications of systematic data analysis in UN field missions. Systematic data analysis can help the leadership of field missions to decide where to deploy troops to protect civilians, guide conflict prevention efforts and help preempt threats to the mission itself. However, predictive analysis in UN peace operations will only be beneficial if it also leads to early action. Finally, predictive peacekeeping will not only be demanding of resources, it will also include ethical challenges on issues such as data privacy and the risk of reidentification of informants or other potentially vulnerable people.

中文翻译：

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预测性维和：加强联合国和平行动的预测性分析

联合国正变得越来越受数据驱动。直到最近，数据驱动的举措主要由联合国外地特派团领导，但随着新任秘书长安东尼奥·古特雷斯（Antonio Guterres）的加入，正在开始采取更加集中的方法。随着使用数据支持联合国工作人员工作的趋势，联合国可能很快就会依靠系统的数据分析来从在联合国外地特派团内和跨外地特派团收集的信息中提取模式。本文基于达尔富尔联合任务分析中心 (JMAC) 的联合国维和数据，并借鉴了在纽约、马里和苏丹进行的采访。它将探讨系统数据分析在联合国外地特派团中的实际和道德影响。系统的数据分析可以帮助外地特派团的领导层决定在何处部署部队以保护平民，指导冲突预防工作并帮助预防对特派团本身的威胁。然而，联合国和平行动中的预测分析只有在它也导致及早采取行动的情况下才会有益。最后，预测性维和不仅需要资源，还包括在数据隐私和重新识别线人或其他潜在弱势人群的风险等问题上的道德挑战。