Responsible artificial intelligence for disaster risk management: working group summary

This document is intended to help practitioners and project managers working in disaster risk ensure that the deployment of artificial intelligence (AI), and machine learning (ML) in particular, is done in a manner that is both effective and responsible. The content of this report was produced as part of a 6-month interdisciplinary collaboration between experts from intergovernmental organizations, non-profits, academia, and the private sector. This document aims to inform and improve the important work carried about by data scientists, risk modelers, and other technical experts working in disaster risk management (DRM).

In order for machine learning technologies to be deployed in the disaster risk management context in a responsible manner, the community of experts and practitioners working on these tools urgently need to take concerns raised in this document seriously. The authors recommend the following: 

1. Proceed with caution.
2. Draw on the experiences of other fields and domains.
3. Work in a transparent fashion.
4. Recognize the limits of technical approaches to addressing concerns.
5. Diversify project teams.
6. Be aware of trade offs and conflicts.
7. Remember that technology is never neutral.
8. Prinicples are not enough.