Roadmap Towards Responsible AI in Crisis Resilience Management
Cheng-Chun Lee, Tina Comes, Megan Finn, Ali Mostafavi

TL;DR
This paper proposes a comprehensive responsible AI roadmap tailored for crisis resilience management, emphasizing ethical data practices, transparency, and stakeholder engagement to mitigate risks and protect vulnerable groups.
Contribution
It introduces the first detailed roadmap integrating responsible AI principles into crisis resilience management, addressing key challenges and considerations across multiple stakeholders.
Findings
Identifies critical challenges in responsible AI for crises
Proposes six key propositions for ethical AI practices
Highlights the importance of transparency and stakeholder engagement
Abstract
Novel data sensing and AI technologies are finding practical use in the analysis of crisis resilience, revealing the need to consider how responsible artificial intelligence (AI) practices can mitigate harmful outcomes and protect vulnerable populations. In this paper, we present a responsible AI roadmap that is embedded in the Crisis Information Management Circle. This roadmap includes six propositions to highlight and address important challenges and considerations specifically related to responsible AI for crisis resilience management. We cover a wide spectrum of interwoven challenges and considerations pertaining to the responsible collection, analysis, sharing, and use of information such as equity, fairness, biases, explainability and transparency, accountability, privacy and security, inter-organizational coordination, and public engagement. Through examining issues around AI…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsDisaster Management and Resilience
