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 »
Critical DRM data gaps remain for Balkans countries. Case studies from government and journalism are an opportunity to explore initiatives and projects addressing these gaps.
By Pierre Chrzanowski, Open Data Specialist at OpenDRI. Co-author: Grace Doherty, Geospatial Consultant at OpenDRI. A few months ago, OpenDRI released the beta version of the OpenDRI Index, a new tool to track and measure the availability of disaster risk data at country level. Today, we are pleased to publish the Global Datasets page, a preliminary list of worldwide or… Read more »
A milestone in the evolution of open data collaboration: Uganda Bureau of Statistics have teamed up with MapUganda to become part of the digital revolution.
RiskInfo was born out of efforts by the Disaster Management Centre and GFDRR to consolidate data for disaster risk management from various partners. It has served as a foundation for building a community of practice around open geospatial data in Sri Lanka.