Explainable Ai Foundations Methodologies And Applications
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Explainable Ai Foundations Methodologies And Applications
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Author : Mayuri Mehta
language : en
Publisher: Springer Nature
Release Date : 2022-10-19
Explainable Ai Foundations Methodologies And Applications written by Mayuri Mehta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-19 with Technology & Engineering categories.
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.
Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges
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Author : Ilaria Tiddi
language : en
Publisher:
Release Date : 2020
Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges written by Ilaria Tiddi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Artificial intelligence categories.
The latest advances in Artificial Intelligence and (deep) Machine Learning in particular revealed a major drawback of modern intelligent systems, namely the inability to explain their decisions in a way that humans can easily understand. While eXplainable AI rapidly became an active area of research in response to this need for improved understandability and trustworthiness, the field of Knowledge Representation and Reasoning (KRR) has on the other hand a long-standing tradition in managing information in a symbolic, human-understandable form. This book provides the first comprehensive collection of research contributions on the role of knowledge graphs for eXplainable AI (KG4XAI), and the papers included here present academic and industrial research focused on the theory, methods and implementations of AI systems that use structured knowledge to generate reliable explanations. Introductory material on knowledge graphs is included for those readers with only a minimal background in the field, as well as specific chapters devoted to advanced methods, applications and case-studies that use knowledge graphs as a part of knowledge-based, explainable systems (KBX-systems). The final chapters explore current challenges and future research directions in the area of knowledge graphs for eXplainable AI. The book not only provides a scholarly, state-of-the-art overview of research in this subject area, but also fosters the hybrid combination of symbolic and subsymbolic AI methods, and will be of interest to all those working in the field.
Explainable Ai With Python
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Author : Leonida Gianfagna
language : en
Publisher: Springer Nature
Release Date : 2021-04-28
Explainable Ai With Python written by Leonida Gianfagna and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-28 with Computers categories.
This book provides a full presentation of the current concepts and available techniques to make “machine learning” systems more explainable. The approaches presented can be applied to almost all the current “machine learning” models: linear and logistic regression, deep learning neural networks, natural language processing and image recognition, among the others. Progress in Machine Learning is increasing the use of artificial agents to perform critical tasks previously handled by humans (healthcare, legal and finance, among others). While the principles that guide the design of these agents are understood, most of the current deep-learning models are "opaque" to human understanding. Explainable AI with Python fills the current gap in literature on this emerging topic by taking both a theoretical and a practical perspective, making the reader quickly capable of working with tools and code for Explainable AI. Beginning with examples of what Explainable AI (XAI) is and why it is needed in the field, the book details different approaches to XAI depending on specific context and need. Hands-on work on interpretable models with specific examples leveraging Python are then presented, showing how intrinsic interpretable models can be interpreted and how to produce “human understandable” explanations. Model-agnostic methods for XAI are shown to produce explanations without relying on ML models internals that are “opaque.” Using examples from Computer Vision, the authors then look at explainable models for Deep Learning and prospective methods for the future. Taking a practical perspective, the authors demonstrate how to effectively use ML and XAI in science. The final chapter explains Adversarial Machine Learning and how to do XAI with adversarial examples.
Towards Ethical And Socially Responsible Explainable Ai
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Author : Mohammad Amir Khusru Akhtar
language : en
Publisher: Springer Nature
Release Date : 2024-08-30
Towards Ethical And Socially Responsible Explainable Ai written by Mohammad Amir Khusru Akhtar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-30 with Technology & Engineering categories.
"Dive deep into the evolving landscape of AI with 'Towards Ethical and Socially Responsible Explainable AI'. This transformative book explores the profound impact of AI on society, emphasizing transparency, accountability, and fairness in decision-making processes. It offers invaluable insights into creating AI systems that not only perform effectively but also uphold ethical standards and foster trust. Essential reading for technologists, policymakers, and all stakeholders invested in shaping a responsible AI future."
Explainable Ai In Health Informatics
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Author : Rajanikanth Aluvalu
language : en
Publisher: Springer Nature
Release Date : 2024-07-07
Explainable Ai In Health Informatics written by Rajanikanth Aluvalu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-07 with Computers categories.
This book provides a comprehensive review of the latest research in the area of explainable artificial intelligence (XAI) in health informatics. It focuses on how explainable AI models can work together with humans to assist them in decision-making, leading to improved diagnosis and prognosis in healthcare. This book includes a collection of techniques and systems of XAI in health informatics and gives a wider perspective about the impact created by them. The book covers the different aspects, such as robotics, informatics, drugs, patients, etc., related to XAI in healthcare. The book is suitable for both beginners and advanced AI practitioners, including students, academicians, researchers, and industry professionals. It serves as an excellent reference for undergraduate and graduate-level courses on AI for medicine/healthcare or XAI for medicine/healthcare. Medical institutions can also utilize this book as reference material and provide tutorials to medical professionals on how the XAI techniques can contribute to trustworthy diagnosis and prediction of the diseases.
Future Research Opportunities For Artificial Intelligence In Industry 4 0 And 5 0
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Author : Jayesh Rane
language : en
Publisher: Deep Science Publishing
Release Date : 2024-10-14
Future Research Opportunities For Artificial Intelligence In Industry 4 0 And 5 0 written by Jayesh Rane and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-14 with Computers categories.
Artificial intelligence (AI), machine learning (ML) and other emerging technologies such as cloud, edge and quantum computing are converging to rewrite the landscape of modern industries and society as a whole. Comprehensive in scope, the book offers a detailed account of these inter-related domains current trends and future possibilities. Chapter 1: We begin by setting the stage with an overview on various trends, problems proposed to solve and road ahead provided by AI, Machine Learning and Deep learning from cloud, edge and quantum computing perspectives. The same is a comprehensive summary to provide perspective on the implications as one continuous stream of technology. It then discusses scalable and adaptive deep learning algorithms, which work in modern machine learning systems where there is a deluge of data. These algorithms sufficiently prepare AI technologies to face the challenges of increasing data as well as expansion of computational capabilities. Chapter three is Federated learning for Edge AI further makes privacy / personalization and security stronger. The amalgamation of blockchain emphasizes the robust and distributed nature of edge intelligence in modern IoT ecosystems. One of the most pressing issues in today's ethical landscape is that of Explainable Artificial Intelligence (XAI), and so the fourth chapter deals with some recent advances in explaining black-box models, providing a way to better understand -and thus potentially trust- AI-driven decision-making processes. This study explores the application of Automated Machine Learning (AutoML) in the contexts of Industry 4.0 and Society 5.0 giving insights on how automation can bring efficiency and innovation in different sectors. It also presents information on the challenges and opportunities that AutoML faces. In conclusion, the book discusses Artificial General Intelligence (AGI), which is a new topic that presents an ambitious view of what AI may be capable of in the future and some points to digest over how the concept might relate to our understanding on what industry may look like in the next stage of human evolution. Individually, these chapters offer a slice of the overall picture of where AI technologies are headed to keep pace with an advancing world.
Sustainable Development Using Private Ai
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Author : Uma Maheswari V
language : en
Publisher: CRC Press
Release Date : 2024-08-27
Sustainable Development Using Private Ai written by Uma Maheswari V and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-27 with Computers categories.
This book covers the fundamental concepts of private AI and its applications. It also covers fusion of Private AI with cutting-edge technologies like cloud computing, federated learning and computer vision. Security Models and Applications for Sustainable Development Using Private AI reviews various encryption algorithms used for providing security in private AI. It discusses the role of training machine learning and Deep learning technologies in private AI. The book provides case studies of using private AI in various application areas such as purchasing, education, entertainment, medical diagnosis, predictive care, conversational personal assistants, wellness apps, early disease detection, and recommendation systems. The authors provide additional knowledge to handling the customer’s data securely and efficiently. It also provides multi-model dataset storage approaches along with the traditional approaches like anonymization of data and differential privacy mechanisms. The target audience includes undergraduate and postgraduate students in Computer Science, Information technology, Electronics and Communication Engineering and related disciplines. This book is also a one stop reference point for professionals, security researchers, scholars, various government agencies and security practitioners, and experts working in the cybersecurity Industry specifically in the R & D division.
Artificial Intelligence And Machine Learning For Business
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Author : Namita Mishra
language : en
Publisher: CRC Press
Release Date : 2025-04-15
Artificial Intelligence And Machine Learning For Business written by Namita Mishra and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-15 with Computers categories.
Artificial intelligence and machine learning are integral parts of every business today, in areas ranging from finance, strategic decision-making, HR operations, and sales and marketing to manufacturing and more. This new book demonstrates how artificial intelligence and machine learning can be used in every aspect of business and as a foundation for complex decision-making. The volume covers such topics as the use of AI in employee training, in stock market prediction, in traffic detection, in opinion mining, in fraud detection, for retail purchase predictions, in online customer support interactions, and more, proving the diverse ways AI can be used in many facets of a business. The use of AI is also explored in fields such as garbage systems, agriculture, precious metals, banking, HR hiring, and so on.
Socio Economic Impact Of Artificial Intelligence
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Author : G. Roberto Marseglia
language : en
Publisher: Springer Nature
Release Date : 2025-01-29
Socio Economic Impact Of Artificial Intelligence written by G. Roberto Marseglia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-29 with Business & Economics categories.
This edited volume discusses ethical issues raised by the use of artificial intelligence (AI) in business. Written by academics and practitioners across Europe, this volume provides a regional management perspective on the consequences of AI, including potential effects on the business models of companies, strategic considerations regarding the construction of data-literate companies and workforces, and the limits and opportunities of proposed EU regulations. Providing a forum to hypothesise solutions for accelerating technology adoption while guaranteeing human dignity, this book will be valuable for researchers and students interested in management, AI, fintech, information systems, and sustainable business as well as managers and practitioners navigating the challenges of a data-driven future.
Advances In Computational Intelligence Micai 2024 International Workshops
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Author : Lourdes Martínez-Villaseñor
language : en
Publisher: Springer Nature
Release Date : 2025-03-07
Advances In Computational Intelligence Micai 2024 International Workshops written by Lourdes Martínez-Villaseñor and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-07 with Computers categories.
This book constitutes the revised selected papers of several workshops which were held in conjunction with the MICAI 2024 International Workshops on Advances in Computational Intelligence, MICAI 2024, held in Tonantzintla, Mexico, during October 21–25, 2024. The 38 revised full papers presented in this book were carefully reviewed and selected from 58 submissions. The papers presented in this volume stem from the following workshops: – 17th Workshop of Hybrid Intelligent Systems (HIS 2024) – 17th Workshop on Intelligent Learning Environments (WILE 2024) – 6th Workshop on New Trends in Computational Intelligence and Applications (CIAPP 2024).