The Responsible AI for DRM report highlights the ethics and responsibility concerns in AI- and ML-supported projects, such as algorithmic bias, transparency and privacy issues, and reduced roles for local participation and expert judgment.
Machine learning (ML) can improve data applications in disaster risk management, especially when coupled with computer vision and geospatial technologies, by providing more accurate, faster, or lower-cost approaches to assessing risk. At the same time, we urgently need to develop a better understanding of the potential for negative or unintended consequences of their use. The… Read more »
This guidance note explains how the World Bank Group uses machine learning algorithms to collect better data, make more informed decisions, and, ultimately, save lives.