Towards Democratized Flood Risk Management: An Advanced AI Assistant
Enabled by GPT-4 for Enhanced Interpretability and Public Engagement
- URL: http://arxiv.org/abs/2403.03188v1
- Date: Tue, 5 Mar 2024 18:24:52 GMT
- Title: Towards Democratized Flood Risk Management: An Advanced AI Assistant
Enabled by GPT-4 for Enhanced Interpretability and Public Engagement
- Authors: Rafaela Martelo, Ruo-Qian Wang (Rutgers University)
- Abstract summary: This study introduces an innovative solution: a customized AI Assistant powered by the GPT-4 Large Language Model.
Our developed prototype integrates real-time flood warnings with flood maps and social vulnerability data.
It also effectively translates complex flood zone information into actionable risk management advice.
- Score: 0.0
- License: http://creativecommons.org/licenses/by-nc-nd/4.0/
- Abstract: Real-time flood forecasting plays a crucial role in enabling timely and
effective emergency responses. However, a significant challenge lies in
bridging the gap between complex numerical flood models and practical
decision-making. Decision-makers often rely on experts to interpret these
models for optimizing flood mitigation strategies. And the public requires
complex techniques to inquiry and understand socio-cultural and institutional
factors, often hinders the public's understanding of flood risks. To overcome
these challenges, our study introduces an innovative solution: a customized AI
Assistant powered by the GPT-4 Large Language Model. This AI Assistant is
designed to facilitate effective communication between decision-makers, the
general public, and flood forecasters, without the requirement of specialized
knowledge. The new framework utilizes GPT-4's advanced natural language
understanding and function calling capabilities to provide immediate flood
alerts and respond to various flood-related inquiries. Our developed prototype
integrates real-time flood warnings with flood maps and social vulnerability
data. It also effectively translates complex flood zone information into
actionable risk management advice. To assess its performance, we evaluated the
prototype using six criteria within three main categories: relevance, error
resilience, and understanding of context. Our research marks a significant step
towards a more accessible and user-friendly approach in flood risk management.
This study highlights the potential of advanced AI tools like GPT-4 in
democratizing information and enhancing public engagement in critical social
and environmental issues.
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