AI can improve catastrophe management. Realizing its benefits requires recognizing and overcoming its limits. Interdisciplinary, multistakeholder, and multinational collaboration is needed to produce implementation standards.
FREMONT, CA: AI and machine learning have reached a level of maturity where they can make accurate predictions and perform identification and classification tasks. National, state, and municipal governments and institutions are addressing how to modernize disaster management approaches to remain competitive.
The Internet of Things (IoT), artificial intelligence (AI), and machine learning can all be profitable. These advances can boost preparedness while reducing human and infrastructure costs and catastrophes. Understanding the advantages of AI in disaster management is a solid starting point.
The potential for AI to aid with disaster resilience is enormous—coordinating relief activities, offering optimal evacuations, and delivering supplies that might benefit tens or even hundreds of millions of people annually.
Despite impediments, a brighter future may be within reach with the right amount of cooperation and teamwork.
Improve Communication: Among Existing Programs: Enhanced communication approaches focus on discrete use cases among a few partners to develop a network of AI-driven catastrophe responses with a greater emphasis on impact.
In data analytics, there is frequently unneeded redundancy, with individuals working on similar use cases that may be simplified. Forming a domain-specific partnership or coalition through which sector and global agencies cooperate with targeted development teams may be considered an alternate option.
Developing Necessary Future Instruments: Rather than investing the majority of the budget on very advanced AI, establish more fundamental data collection and coordination capabilities for different agencies on the ground. This could provide "fuel" for future life-saving algorithms.
Consequently, although more advanced algorithms are being developed, it would be beneficial to commit an equal amount of research effort to these fundamental tools.
Domain-Specific AI Principles Agreements: Additional domain-specific ethical AI standards agreements are urgently required. Numerous efforts have been made by international organizations, including the United Nations and the European Union, to establish rules for the positive use of AI in general.
However, given the project's complexity, this will likely take some time. In the interim, it may be advantageous to coordinate stakeholders in specialized fields, such as disaster response.
Establishing an algorithm review method to ensure that AI solutions meet specified criteria before public release could be a component of this.
