Explainable Ai Within The Digital Transformation And Cyber Physical Systems
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Explainable Ai Within The Digital Transformation And Cyber Physical Systems
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Author : Moamar Sayed-Mouchaweh
language : en
Publisher: Springer Nature
Release Date : 2021-10-30
Explainable Ai Within The Digital Transformation And Cyber Physical Systems written by Moamar Sayed-Mouchaweh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-30 with Technology & Engineering categories.
This book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefits and requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions. Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems; Provides a textual scientific description of the use of XAI in order to address the challenges of digital transition and cyber-physical systems; Presents examples and case studies in order to increase transparency and understanding of the methodological concepts.
Explainable Ai Within The Digital Transformation And Cyber Physical Systems
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Author : Moamar Sayed-Mouchaweh
language : en
Publisher:
Release Date : 2021
Explainable Ai Within The Digital Transformation And Cyber Physical Systems written by Moamar Sayed-Mouchaweh and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
This book presents Explainable Artificial Intelligence (XAI), which aims at producing explainable models that enable human users to understand and appropriately trust the obtained results. The authors discuss the challenges involved in making machine learning-based AI explainable. Firstly, that the explanations must be adapted to different stakeholders (end-users, policy makers, industries, utilities etc.) with different levels of technical knowledge (managers, engineers, technicians, etc.) in different application domains. Secondly, that it is important to develop an evaluation framework and standards in order to measure the effectiveness of the provided explanations at the human and the technical levels. This book gathers research contributions aiming at the development and/or the use of XAI techniques in order to address the aforementioned challenges in different applications such as healthcare, finance, cybersecurity, and document summarization. It allows highlighting the benefits and requirements of using explainable models in different application domains in order to provide guidance to readers to select the most adapted models to their specified problem and conditions. Includes recent developments of the use of Explainable Artificial Intelligence (XAI) in order to address the challenges of digital transition and cyber-physical systems; Provides a textual scientific description of the use of XAI in order to address the challenges of digital transition and cyber-physical systems; Presents examples and case studies in order to increase transparency and understanding of the methodological concepts.
Explainable Artificial Intelligence Xai In Manufacturing
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Author : Tin-Chih Toly Chen
language : en
Publisher: Springer Nature
Release Date : 2023-03-16
Explainable Artificial Intelligence Xai In Manufacturing written by Tin-Chih Toly Chen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-16 with Technology & Engineering categories.
This book provides a comprehensive overview of the latest developments in Explainable AI (XAI) and its applications in manufacturing. It covers the various methods, tools, and technologies that are being used to make AI more understandable and communicable for factory workers. With the increasing use of AI in manufacturing, there is a growing need to address the limitations of advanced AI methods that are difficult to understand or explain to those without a background in AI. This book addresses this need by providing a systematic review of the latest research and advancements in XAI specifically tailored for the manufacturing industry. The book includes real-world case studies and examples to illustrate the practical applications of XAI in manufacturing. It is a valuable resource for researchers, engineers, and practitioners working in the field of AI and manufacturing.
Role Of Explainable Artificial Intelligence In E Commerce
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Author : Loveleen Gaur
language : en
Publisher: Springer Nature
Release Date : 2024-04-25
Role Of Explainable Artificial Intelligence In E Commerce written by Loveleen Gaur and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-25 with Business & Economics categories.
The technological boom has provided consumers with endless choices, removing the hindrance of time and place. Understanding the dynamic and competitive business environment, marketers know they need to reinforce indestructible customer experience with the support of algorithmic configurations to minimize human intrusion. World Wide Web (WWW) and online marketing have changed the way of conducting business; with artificial intelligence (AI), business houses can furnish a customized experience to fulfil the perceived expectation of the customer. Artificial intelligence bridges the gap between business and prospective clients, provides enormous amounts of information, prompts grievance redressal system, and further complements the client’s preference. The opportunities online marketing offers with the blend of artificial intelligence tools like chatbots, recommenders, virtual assistance, and interactive voice recognition create improved brand awareness, better customer relationshipmarketing, and personalized product modification. Explainable AI provides the subsequent arena of human–machine collaboration, which will complement and support marketers and people so that they can make better, faster, and more accurate decisions. According to PwC’s report on Explainable AI(XAI), AI will have $15.7 trillion of opportunity by 2030. However, as AI tools become more advanced, more computations are done in a “black box” that humans can hardly comprehend. But the rise of AI in business for actionable insights also poses the following questions: How can marketers know and trust the reasoning behind why an AI system is making recommendations for action? What are the root causes and steering factors? Thus, transparency, trust, and a good understanding of expected business outcomes are increasingly demanded.
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."
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.
Innovations In Cybersecurity And Data Science
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Author : Syed Muzamil Basha
language : en
Publisher: Springer Nature
Release Date : 2024-12-12
Innovations In Cybersecurity And Data Science written by Syed Muzamil Basha and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-12 with Computers categories.
This book features research papers presented at International Conference on Innovations in Cybersecurity and Data Science (ICICDS 2024), held at Reva University, Bengaluru, India during 15 – 16 March 2024. The book presents original research work in the field of computer science, computer applications, information technology, artificial intelligence, and other relevant fields of IoT, big data, data management and analytics, and security. The book is beneficial for readers from both academia and industry.
Artificial Intelligence Ecai 2023 International Workshops
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Author : Sławomir Nowaczyk
language : en
Publisher: Springer Nature
Release Date : 2024-01-20
Artificial Intelligence Ecai 2023 International Workshops written by Sławomir Nowaczyk and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-20 with Computers categories.
This volume constitutes the refereed proceedings presented at the international workshops of the 26th European Conference on Artificial Intelligence, ECAI 2023, which was held in Kraków, Poland, in September-October 2023. The papers in this volume were presented at the following workshops: XAI^3, TACTIFUL, XI-ML, SEDAMI, RAAIT, AI4S, HYDRA, AI4AI.
Diverse Perspectives And State Of The Art Approaches To The Utilization Of Data Driven Clinical Decision Support Systems
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Author : Connolly, Thomas M.
language : en
Publisher: IGI Global
Release Date : 2022-11-11
Diverse Perspectives And State Of The Art Approaches To The Utilization Of Data Driven Clinical Decision Support Systems written by Connolly, Thomas M. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-11 with Business & Economics categories.
The medical domain is home to many critical challenges that stand to be overcome with the use of data-driven clinical decision support systems (CDSS), and there is a growing set of examples of automated diagnosis, prognosis, drug design, and testing. However, the current state of AI in medicine has been summarized as “high on promise and relatively low on data and proof.” If such problems can be addressed, a data-driven approach will be very important to the future of CDSSs as it simplifies the knowledge acquisition and maintenance process, a process that is time-consuming and requires considerable human effort. Diverse Perspectives and State-of-the-Art Approaches to the Utilization of Data-Driven Clinical Decision Support Systems critically reflects on the challenges that data-driven CDSSs must address to become mainstream healthcare systems rather than a small set of exemplars of what might be possible. It further identifies evidence-based, successful data-driven CDSSs. Covering topics such as automated planning, diagnostic systems, and explainable artificial intelligence, this premier reference source is an excellent resource for medical professionals, healthcare administrators, IT managers, pharmacists, students and faculty of higher education, librarians, researchers, and academicians.
Machine Learning And Principles And Practice Of Knowledge Discovery In Databases
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Author : Rosa Meo
language : en
Publisher: Springer Nature
Release Date : 2024-12-31
Machine Learning And Principles And Practice Of Knowledge Discovery In Databases written by Rosa Meo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-31 with Computers categories.
The five-volume set CCIS 2133-2137 constitutes the refereed proceedings of the workshops held in conjunction with the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, during September 18-22, 2023. The 200 full papers presented in these proceedings were carefully reviewed and selected from 515 submissions. The papers have been organized in the following tracks: Part I: Advances in Interpretable Machine Learning and Artificial Intelligence -- Joint Workshop and Tutorial; BIAS 2023 - 3rd Workshop on Bias and Fairness in AI; Biased Data in Conversational Agents; Explainable Artificial Intelligence: From Static to Dynamic; ML, Law and Society; Part II: RKDE 2023: 1st International Tutorial and Workshop on Responsible Knowledge Discovery in Education; SoGood 2023 – 8th Workshop on Data Science for Social Good; Towards Hybrid Human-Machine Learning and Decision Making (HLDM); Uncertainty meets explainability in machine learning; Workshop: Deep Learning and Multimedia Forensics. Combating fake media and misinformation; Part III: XAI-TS: Explainable AI for Time Series: Advances and Applications; XKDD 2023: 5th International Workshop on eXplainable Knowledge Discovery in Data Mining; Deep Learning for Sustainable Precision Agriculture; Knowledge Guided Machine Learning; MACLEAN: MAChine Learning for EArth ObservatioN; MLG: Mining and Learning with Graphs; Neuro Explicit AI and Expert Informed ML for Engineering and Physical Sciences; New Frontiers in Mining Complex Patterns; Part IV: PharML, Machine Learning for Pharma and Healthcare Applications; Simplification, Compression, Efficiency and Frugality for Artificial intelligence; Workshop on Uplift Modeling and Causal Machine Learning for Operational Decision Making; 6th Workshop on AI in Aging, Rehabilitation and Intelligent Assisted Living (ARIAL); Adapting to Change: Reliable Multimodal Learning Across Domains; AI4M: AI for Manufacturing; Part V: Challenges and Opportunities of Large Language Models in Real-World Machine Learning Applications; Deep learning meets Neuromorphic Hardware; Discovery challenge; ITEM: IoT, Edge, and Mobile for Embedded Machine Learning; LIMBO - LearnIng and Mining for BlOckchains; Machine Learning for Cybersecurity (MLCS 2023); MIDAS - The 8th Workshop on MIning DAta for financial applicationS; Workshop on Advancements in Federated Learning.