Artificial Intelligence can help with geospatial data collection — and those data can save lives. But AI can also have unintended consequences for marginalized groups. That’s where Responsible AI comes in.
Tag: Machine Learning
The Open Cities AI Challenge, put on by GFDRR with Azavea and DrivenData, recently concluded with over 1,100 participants, 2,100 submissions and $15,000 in total prizes awarded. Along two competition tracks, the Challenge produced global public goods — open-source data, code, research, and know-how — that will support mapping efforts for disaster resilience. This includes: Increasing… Read more »
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 »
Segment buildings in African cities from aerial imagery and advance Responsible AI ideas for disaster risk management
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.
OpenDRI and GFDRR invite you to participate in our mapping event in the World Bank Headquarters on Wednesday, November 14 from 11:00 am – 2:00 pm. This Mapathon seeks to bring attention to the numerous benefits of using geospatial data in providing solutions to development and disaster risk reduction (DRR) initiatives. Organized as part of… Read more »
OpenDRI is in Dar es Salaam, Tanzania this week for the annual conference of Free and Open Source Software for Geospatial (FOSS4G 2018). With over 1000 expected attendees, this large gathering of geospatial enthusiasts is a prime opportunity to learn and share about the latest technology in mapping. Part of the pre-conference program, Tuesday morning… Read more »