相关实验视频

从速度到信任:确保基于人工智能的极端天气预报的透明度

Xuelin Wang¹, Zejia Qin¹

¹School of Information Management, Central China Normal University, Wuhan, China.

Integrated environmental assessment and management

|January 6, 2026

概括

人工智能 (AI) 增强了极端天气预报,但需要对信任和公平的透明度. 实施模型卡等措施确保人工智能预警系统是有效和公平的.

科学领域:

气象学天气学
计算机科学计算机科学
气候科学气候科学

背景情况:

人工智能 (AI) 提供比传统模型更快,更便宜的极端天气预报.
预测中的人工智能在透明度方面带来了挑战,影响了信任,公平和弹性.
当前的人工智能预警系统可能缺乏对高风险应用程序的必要清晰度.

研究的目的:

检查基于人工智能的天气预报的透明度.
评估AI对预测完整性,社会公平性和长期弹性的影响.
认为仅仅是准确性对AI在关键预测环境中是不够的.

主要方法:

对人工智能预测透明度的分析涉及三个方面:预测完整性,社会公平性和长期弹性.
审查气象实践中最近的监管发展.
确定增强人工智能预测透明度的实际措施.

主要成果:

人工智能驱动的预测速度更快,计算效率更高.
人工智能决策缺乏透明度会给信任和公平带来风险.
准确性不是评估AI在高风险预测中的唯一指标.

结论:

透明度对于可靠和公平的人工智能驱动的预警系统至关重要.
建议采取实用措施,如协调标签和模型卡.
融入国际框架对于有效的气象人工智能至关重要.

关键词:

在这里,我们可以看到AIAIAI.长期性长期性预测的完整性预测的完整性社会的公平性社会的公平性

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