A Responsible Artificial Intelligence Framework for Groundwater Modeling
The rapid development and widespread application of artificial intelligence (AI) have sparked intense discussions on how to deploy responsible AI systems in a manner aligned with human values and ethical standards. Compared to fields like healthcare, energy, or finance, the application of AI in groundwater is relatively limited, and research on responsible AI is even more scarce. Taking the middle reaches of the Heihe River Basin as the study area, this paper proposes six Responsible AI principles: transparency, technical robustness, privacy governance, fairness, accountability, and sustainability. LSTM and Transformer time-series models are developed using multi-source hydrometeorologica...
| Authors | Chong Chen, Yulu Zhang, Qingxi Guo et al. |
|---|---|
| Primary category | cs.AI |
| Published | 16 August 2026 |
| Last updated at source | 16 August 2026 |
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