INTEGRATION OF ARTIFICIAL INTELLIGENCE IN DISASTER MANAGEMENT: A SYSTEMATIC LITERATURE REVIEW ON ETHICAL AND SOCIAL IMPLICATIONS

Abstract

The increasing global frequency and intensity of natural disasters, driven by climate change, have highlighted the urgent need for more effective disaster management approaches. Artificial intelligence (AI) has emerged as a transformative technology with the potential to enhance preparedness, response, and recovery through its predictive and analytical capabilities. However, despite well-documented technical benefits, the ethical and social implications of implementing AI in this vulnerable context remain underexplored. This study aims to fill this gap by conducting a comprehensive Systematic Literature Review (SLR). Through a synthesis of recent literature, this report identifies and deeply analyzes key ethical issues, including algorithmic bias, data privacy and sovereignty challenges, transparency and accountability issues, and the risk of exacerbating the digital divide. The findings indicate that AI is neither an apolitical solution nor a human replacement, and its long-term success hinges on responsible development that prioritizes humanitarian principles, community-centric collaboration, and robust governance frameworks.