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The Need for Explainable AI in Industry 5.0
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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: 30
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.ch001
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Abstract
As we enter the era of Industrial Revolution 5.0 (IR 5.0), the role of artificial intelligence (AI) in various domains such as manufacturing, military, healthcare, education, and entertainment is becoming increasingly vital. However, the growing complexity and opacity of AI systems have led to a problem known as the “black box,” which hinders trust and accountability. This is where explainable AI (XAI) comes in, providing a set of processes and methods that enable human users to understand and trust the results and output produced by machine learning algorithms. By describing AI models, their expected impact, and potential biases, XAI helps ensure accuracy, fairness, transparency, and accountability in AI-powered decision making. In this chapter, the authors argue that XAI is indispensable for IR 5.0, as it enables humans to collaborate with AI systems effectively and responsibly. The authors reviewed the current state of XAI research and practice and highlighted the challenges and opportunities for XAI in IR 5.0.
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