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Open Challenges and Research Issues of XAI in Modern Smart Cities
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Author(s): Azeem Khan (University Islam Sultan Sharif Ali, Brunei), Noor Zaman Jhanjhi (Taylor's University, Malaysia), Dayang Hajah Tiawa Binti Awang Haji Hamid (University Islam Sultan Sharif Ali, Brunei)and Haji Abdul Hafidz bin Haji Omar (University Islam Sultan Sharif Ali, Brunei)
Copyright: 2024
Pages: 20
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.ch008
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Abstract
The increasing use of AI in modern smart cities calls for explainable artificial intelligence (XAI) systems that can improve the efficiency and effectiveness of city operations while being transparent, interpretable, and trustworthy. Developing a unified framework for XAI that can handle the heterogeneity of data and systems in smart cities is the first challenge, considering the need to incorporate human factors and preferences in AI systems. The second challenge is developing new XAI methods that can handle the complexity and scale of smart city data. Addressing ethical and legal aspects is also critical, including ensuring that AI systems are fair and unbiased, protecting citizens' privacy and security, and establishing legal frameworks. Evaluating the effectiveness and usability of XAI systems is also crucial in improving city operations and stakeholder trust apart from XAI research for smart cities: improved visualization, human feedback, integration.
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