Report

Predict and prevent: overcoming early warning implementation challenges in UN peace operations

Published: 25 Sep 2020
Summary:

The UN has made progress in the adoption of new technologies to predict and prevent local violence. To maintain the momentum, it needs to continue to innovate to be able to serve people in need faster, better, and more efficiently. The UN will need to find a way to analyse the enormous amount of data it produces every day. Machine learning to detect patterns in these data and produce early warnings holds great promise in this regard. However, the use of new technologies is not without risk. Collected data can fall into the wrong hands. With budget cuts missions have been forced to reduce their footprint in the field, increasing the reliance on technology. New technology also requires new types of specialist expertise to manage data, and better understanding among all staff of how data should be managed, vetted and put to use. Some have expressed concerns about the use of technologies being at the expense of face-to-face engagements, ultimately resulting in peacekeeping efforts that are divorced from realities on the ground. From a practical point of view, the UN will also have to resolve an uneasy tension between enabling access to these data in order to conduct data-driven early warning analyses on the one hand and the need to prevent any data breaches on the other hand.

  • Published year: 2020
  • Full version: Read here
  • Publisher: ZIF
  • Page count: 5
  • Language: English
  • Journal: TECHPOPS