Bias and debiasing in data-driven crisis decision-making

Abstract

The United Nations estimates that hundreds of millions of people worldwide are affected by complex crises. Examples are the protracted conflict in Yemen, climate change-induced displacement, and the COVID-19 pandemic. These crises have severe implications for societies. To mitigate crises’ effects, crisis response organizations strive to make data-driven decisions. However, these crises are complex: they involve many actors with different mandates and objectives that face uncertain information as well as decision urgencies. These issues can lead to systematic errors within collected crisis data, i.e., data bias, and challenge decision-makers cognitive information processing capacities by inducing cognitive bias....