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.
Tag: disaster risk management
On Saturday, March 6, join GFDRR Labs and OpenDRI for an Open Data Day webinar on the value of open data for understanding disaster risk.
Au Cameroun, les contributions d’un large éventail d’acteurs ont permis d’accroître la disponibilité des données et de produire un Atlas des risques.
The Ngaoundéré City Council (NCC) is using a stakeholder-driven Risk Atlas to inform urban management and planning.
GFDRR supports Open Data Day mini-grants to provide funding for local events showcasing open data in their communities.
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.