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Overview of XAI for the Development and Modernization of Smart Cities: Explainable Artificial Intelligence
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Author(s): Azeem Khan (Faculty of Islamic Technology, University Islam Sultan Sharif Ali, Brunei), NZ Jhanjhi (School of Computer Science, Taylor's University, Malaysia), Dayang Hajah Tiawa Binti Awang Haji Hamid (Faculty of Islamic Technology, University Islam Sultan Sharif Ali, Brunei)and Haji Abdul Hafidz bin Haji Omar (Faculty of Islamic Technology, University Islam Sultan Sharif Ali, Brunei)
Copyright: 2024
Pages: 22
Source title:
Advances in Explainable AI Applications for Smart Cities
Source Author(s)/Editor(s): Mangesh M. Ghonge (Sandip Institute of Technology and Research Centre, India), Nijalingappa Pradeep (Bapuji Institute of Engineering and Technology, India), Noor Zaman Jhanjhi (School of Computer Science, Faculty of Innovation and Technology, Taylor’s University, Malaysia)and Praveen M. Kulkarni (Karnatak Law Society's Institute of Management Education and Research (KLS IMER), Belagavi, India)
DOI: 10.4018/978-1-6684-6361-1.ch006
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Abstract
AI systems are integral to the development of smart cities, but their complexity can make decision-making processes opaque, leading to concerns about accountability and transparency. Explainable AI (XAI) aims to address this by designing algorithms that can explain decisions in a way that humans can understand. XAI can increase transparency and accountability in smart cities, promote trust between residents and officials, and enhance the adoption and acceptance of smart city technologies. However, there are still challenges to overcome, and continued research is necessary to fully realize the potential benefits of XAI.
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