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About this paper
Aman Raj, Lakshit Arora, Sanjay Surendranath Girija, Shashank Kapoor, Dipen Pradhan, Ankit Shetgaonkar
Researchers at Google compiled the first comprehensive survey of Generative AI (GenAI) techniques, examining their diverse applications in disaster damage assessment and response across various natural calamities. The survey details GenAI's capabilities in processing multimodal data and simulating scenarios, while also identifying critical challenges related to misinformation, privacy, and ethical deployment.
Key insights
- GenAI offers transformative potential by synthesizing realistic scenarios, augmenting scarce data, and integrating complex information for faster and more accurate disaster assessment.
- The dual nature of GenAI necessitates robust strategies for detecting and mitigating misinformation and adversarial attacks, which can generate hyper-realistic fake media.
- Ethical considerations, including bias mitigation, explainable AI (XAI), and secure, privacy-preserving deployment, are crucial for building trust and ensuring responsible GenAI systems in high-stakes disaster contexts.
Summary by alphaXiv.
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