Artificial intelligence (AI) has emerged as a powerful tool in geophysics, revolutionizing data analysis, modeling, and prediction capabilities as well as having the potential to revolutionize weather impact-based decision support services and risk communication. However, the adoption of AI in geophysical research and applications raises critical questions about trustworthiness and ethics and how systems are trusted (or not) to provide decision support services. While Policies are being established to mandate trustworthy and ethical AI, such as the U.S. Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence, there is little clarity on what this means for scientists, developers, and how users will trust AI for decision support. This session will explore the multifaceted aspects of trustworthy and ethical AI through the uses of AI for decision support.

• Integration of Weather Data and Impact Models: How can we leverage AI to integrate weather models and forecasts with impact models to provide tailored decision support services that account for local conditions and vulnerabilities? What advancements have been made in coupling weather forecasts with socioeconomic data and models to assess the potential impacts of extreme weather events on various sectors, such as emergency resource management, agriculture, transportation, and public health?
• Personalized Decision Support Services: How can AI be used to personalize IDSS and risk communication based on individual or community-specific needs, preferences, and vulnerabilities? What approaches and algorithms can be employed to tailor weather-related recommendations, warnings, and mitigation strategies to diverse user groups, including vulnerable populations and decision-makers in different sectors?
• Innovations in AI Risk Communication: What innovative tools, technologies, and communication strategies are being utilized to improve the creation and dissemination of warnings and risk information? How can we use AI to leverage social media, mobile apps, citizen science, and other digital platforms to reach diverse audiences and facilitate real-time communication during weather emergencies and feedback that provides for continuous improvement of services?
• Case Studies and Best Practices: What real-world examples and case studies demonstrate the successful integration of AI into IDSS and risk communication efforts? What lessons learned and best practices can be derived from these experiences to guide future implementation and deployment of AI technologies in weather forecasting, emergency response, and public communication?

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