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The Current State of Artificial Intelligence in Disaster Recovery: Challenges, Opportunities, and Future Directions
Citation:
Boe, T. The Current State of Artificial Intelligence in Disaster Recovery: Challenges, Opportunities, and Future Directions. U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-23/120, 2023.
Impact/Purpose:
The study explored the potential of artificial intelligence (AI) in disaster response and environmental remediation by providing a historical overview, conducting a meta-analysis of related literature, identifying Natural Language Processing (NLP) and image analysis as key research areas, and presenting conceptual examples of AI's potential applications. The study emphasized the need for further research and development while addressing barriers and challenges to ensure ethical deployment and data privacy. The findings highlighted the significant potential of AI to revolutionize various sectors, including disaster response and environmental remediation.
Description:
This study explored the potential of artificial intelligence (AI) in disaster response and environmental remediation by conducting a meta-analysis of AI-related literature and providing a historical overview of AI. The study identified Natural Language Processing (NLP) and image analysis as two primary research areas that could greatly benefit from AI integration. Conceptual examples were presented, showcasing the potential of NLP in enhancing communications, code writing, interpreting scientific material, and strategy optimization, while image analysis applications included visualizing training scenarios, debris characterization, and design prototyping. The study also discussed emerging developments and potential impediments that may influence the adoption of AI in the public sector. It emphasized the importance of establishing policy frameworks and guidelines to ensure ethical applications and data privacy. The paper highlighted the significant potential of AI to revolutionize various sectors, particularly disaster response and environmental remediation, while also addressing existing barriers and challenges associated with the deployment and utilization of this technology. The research demonstrated the transformative potential of AI in disaster response and environmental remediation, but also underscored the need for further exploration and development of AI applications. By addressing the challenges and barriers surrounding AI deployment, AI has the potential to bring about revolutionary changes across various sectors, including disaster response and environmental remediation.