Utilizing Artificial Intelligence for Enhanced Emergency Notifications and Warnings
In a groundbreaking study conducted at the Chair of Medical Informatics, led by Prof. Dr. Hans-Ulrich, the feasibility of using artificial intelligence (AI) as an AI-driven Alert Assistant was explored. The primary objective was to aid alert originators in crafting effective and timely warning messages.
The study focused on best practices for crafting emergency messages, addressing the challenges emergency managers face, such as generating messages under stress, with limited information, and competing priorities. To achieve this, the AI model was "taught" using a series of refining prompts and a feedback loop.
The AI model was trained with local hazard data, allowing it to generate messages specific to the hazards in St. Mary's County, Maryland. This localized approach proved to be a significant advantage, as the model understood common natural hazards in the area and could recognise when a hazard was uncommon.
One of the key findings of the study was that AI can quickly generate alert messages, significantly reducing the time needed to respond to emergencies. This speed and efficiency enhancement was evident in the model's ability to accurately convert messages into multiple languages, enabling the dissemination of alerts in multiple languages simultaneously.
The AI consistently followed strict adherence to character limits and guidelines outlined in the Warning Lexicon, ensuring that each generated message included all necessary components, such as the source, hazard, location, guidance, and timing.
AI can also tailor messages to specific audiences based on geographic location, demographics, and language preferences. This personalization aspect of the AI-driven Alert Assistant was found to be approximately 98% accurate, as confirmed by a native Spanish speaker who reviewed the translations.
However, it is crucial to implement comprehensive training programs for emergency personnel on the proper use and risks of AI tools and to update policies and procedures to include AI-driven solutions. Integrating AI technologies effectively in emergency management can improve the efficiency and effectiveness of emergency responses.
The study results indicate that AI models can play a significant role in enhancing the speed, personalization, translation, and consistency of emergency alert messaging. The overarching finding is that AI-driven Alert Assistants have the potential to revolutionize emergency communication processes, making them more efficient, effective, and inclusive.
