Explainability, uncertainty & physics
The value of convergence research for developing trustworthy AI for weather, climate, and ocean hazards
In one sentence. Perspective from the AI2ES institute on convergence research for trustworthy AI in weather, climate and coastal hazards, integrating end-user trust assessment into AI development.
Abstract
Abstract Artificial Intelligence applications are rapidly expanding across weather, climate, and natural hazards. AI can be used to assist with forecasting weather and climate risks, including forecasting both the chance that a hazard will occur and the negative impacts from it, which means AI can help protect lives, property, and livelihoods on a global scale in our changing climate. To ensure that we are achieving this goal, the AI must be developed to be trustworthy, which is a complex and multifaceted undertaking. We present our work from the NSF AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES), where we are taking a convergence research approach. Our work deeply integrates across AI, environmental, and risk communication sciences. This involves collaboration with professional end-users to investigate how they assess the trustworthiness and usefulness of AI methods for forecasting natural hazards. In turn, we use this knowledge to develop AI that is more trustworthy. We discuss how and why end-users may trust or distrust AI methods for multiple natural hazards, including winter weather, tropical cyclones, severe storms, and coastal oceanography.
Labels
- Topic
- Explainability, uncertainty & physics, Applications & impacts
- Type
- Position or perspective paper
- Domain
- Global
- Data
- Other
- Status
- Research
- Identifiers
- DOI:10.1038/s44304-024-00014-x OpenAlex:W4400207646
- Added
- 2026-10-22
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