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This book presents new trends to optimize e-Government in various contexts. It aims to highlight new methods and approaches that unveil the potential of data for public services. The book also illustrates how public services can be mathematically modeled with many case studies. Then, algorithms are proposed to optimize their functioning and to better contribute to the general interest, such as education, health care, safety, security, or culture. The book also focuses on protecting citizens' personal data and obtaining their explicit consent.The book is suitable for students and academics aiming to build up their background on the usage of data and algorithms through various techniques, including artificial intelligence. The book is used as a reference book for teaching a graduate course on e-Government, Process Modeling, or Artificial Intelligence. Besides its use in academia, this book is used by civil servants of every domain and citizens who aim to understand theongoing modernization of public services.
This book presents an overview and several applications of explainable artificial intelligence (XAI). It covers different aspects related to explainable artificial intelligence, such as the need to make the AI models interpretable, how black box machine/deep learning models can be understood using various XAI methods, different evaluation metrics for XAI, human-centered explainable AI, and applications of explainable AI in health care, security surveillance, transportation, among other areas.The book is suitable for students and academics aiming to build up their background on explainable AI and can guide them in making machine/deep learning models more transparent. The book can be used as a reference book for teaching a graduate course on artificial intelligence, applied machine learning, or neural networks. Researchers working in the area of AI can use this book to discover the recent developments in XAI. Besides its use in academia, this book could be used by practitioners in AI industries, healthcare industries, medicine, autonomous vehicles, and security surveillance, who would like to develop AI techniques and applications with explanations.
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