Affiliation:
1. University Islam Sultan Sharif Ali, Brunei
2. Taylor's University, Malaysia
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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