INVESTMENT ARTIFICIAL INTELLIGENCE IN DECISION-MAKING PROCESSES IN THE JORDANIAN MINISTRY OF INTERIOR

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Mohammad Ali Alqudah

Abstract

This research paper is part of a larger study on Jordan's artificial intelligence strategy and its role in changing government service delivery mechanisms, leading to a comprehensive data analysis using the most up-to-date artificial intelligence techniques and their applications in various fields of work The purpose of the study was to discuss Jordan's decision-making process and the application of artificial intelligence. The issue was presented in two demands using the descriptive-analytical approach. The conversations revealed that Jordan's artificial intelligence policy aims to reduce accidents and operational expenses in various key areas of the country, including transportation. Reduce the proportion of chronic and serious diseases in the health sector. Facilities management and smart consumption in the energy sector. The education sector, by lowering costs and encouraging the desire to learn, and the technology sector, by improving the rate of production and assisting in public investment. By increasing the proportion of forestation and planting appropriate plants, the environment sector will benefit. The sector of Transportation Develops preventative techniques, such as the ability to foresee accidents and traffic congestion, as well as better traffic policies. The presence of infrastructure and knowledge in the success of artificial intelligence recruitment in Jordan's Ministry of Interior.

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How to Cite
Mohammad Ali Alqudah. (2021). INVESTMENT ARTIFICIAL INTELLIGENCE IN DECISION-MAKING PROCESSES IN THE JORDANIAN MINISTRY OF INTERIOR. International Journal of Innovations in Engineering Research and Technology, 8(10), 40-53. https://doi.org/10.17605/OSF.IO/5D7KZ
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How to Cite

Mohammad Ali Alqudah. (2021). INVESTMENT ARTIFICIAL INTELLIGENCE IN DECISION-MAKING PROCESSES IN THE JORDANIAN MINISTRY OF INTERIOR. International Journal of Innovations in Engineering Research and Technology, 8(10), 40-53. https://doi.org/10.17605/OSF.IO/5D7KZ

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