Employing Artificial Intelligence in Geography: ‎New Opportunities and Existing Challenges | ||
| The Arab Journal of Scientific Research | ||
| Volume 9, Issue 10, 2025, Pages 111-122 PDF (550.19 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/ajsr.2025.422211 | ||
| Author | ||
| ‎ Abdessamad ‎ Khouya | ||
| ‎ Ph.D., Researcher in Physical Geography, Faculty of Arts ‎and Humanities, Saïs, Fez, Morocco | ||
| Abstract | ||
| In recent decades, Artificial Intelligence (AI) has become an essential part of various scientific and industrial fields, including geography, where this technology has brought about significant transformations. AI provides powerful analytical tools that help process vast amounts of geographical data quickly and accurately, enhancing the understanding of spatial patterns, predicting environmental changes, and improving urban planning. Its applications include satellite image analysis, climate change forecasting, natural resource management, and the development of smart cities. Despite its numerous advantages, AI in geography faces several challenges, including privacy issues, data bias, and the high costs associated with developing these technologies. The main concern is how to balance the benefits with the challenges and identify possible solutions to ensure the effective and sustainable application of this technology in analyzing and understanding geographical phenomena. The advantages include improved climate and environmental forecasting, natural resource management, enhancement of Geographic Information Systems (GIS), detection and monitoring of environmental changes, and support for decision-making and policy formulation. However, the challenges involve data bias, ethical and privacy concerns, high costs, and technical complexity. To overcome these challenges, it is necessary to develop unbiased models, adopt privacy protection protocols, and encourage collaboration between academia, the private sector, and public institutions. The successful integration of AI in geography requires effectively addressing these challenges to maximize its potential in improving our understanding and management of the geographical world. | ||
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