Explainable Human Ai Interaction
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Explainable Human Ai Interaction
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Author : Sarath Sreedharan
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2022-01-24
Explainable Human Ai Interaction written by Sarath Sreedharan and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-24 with Computers categories.
From its inception, artificial intelligence (AI) has had a rather ambivalent relationship with humans—swinging between their augmentation and replacement. Now, as AI technologies enter our everyday lives at an ever-increasing pace, there is a greater need for AI systems to work synergistically with humans. One critical requirement for such synergistic human‒AI interaction is that the AI systems' behavior be explainable to the humans in the loop. To do this effectively, AI agents need to go beyond planning with their own models of the world, and take into account the mental model of the human in the loop. At a minimum, AI agents need approximations of the human's task and goal models, as well as the human's model of the AI agent's task and goal models. The former will guide the agent to anticipate and manage the needs, desires and attention of the humans in the loop, and the latter allow it to act in ways that are interpretable to humans (by conforming to their mental models of it), and be ready to provide customized explanations when needed. The authors draw from several years of research in their lab to discuss how an AI agent can use these mental models to either conform to human expectations or change those expectations through explanatory communication. While the focus of the book is on cooperative scenarios, it also covers how the same mental models can be used for obfuscation and deception. The book also describes several real-world application systems for collaborative decision-making that are based on the framework and techniques developed here. Although primarily driven by the authors' own research in these areas, every chapter will provide ample connections to relevant research from the wider literature. The technical topics covered in the book are self-contained and are accessible to readers with a basic background in AI.
Explainable Agency In Artificial Intelligence
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Author : Silvia Tulli
language : en
Publisher: CRC Press
Release Date : 2024-01-22
Explainable Agency In Artificial Intelligence written by Silvia Tulli and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-22 with Computers categories.
This book focuses on a subtopic of explainable AI (XAI) called explainable agency (EA), which involves producing records of decisions made during an agent’s reasoning, summarizing its behavior in human-accessible terms, and providing answers to questions about specific choices and the reasons for them. We distinguish explainable agency from interpretable machine learning (IML), another branch of XAI that focuses on providing insight (typically, for an ML expert) concerning a learned model and its decisions. In contrast, explainable agency typically involves a broader set of AI-enabled techniques, systems, and stakeholders (e.g., end users), where the explanations provided by EA agents are best evaluated in the context of human subject studies. The chapters of this book explore the concept of endowing intelligent agents with explainable agency, which is crucial for agents to be trusted by humans in critical domains such as finance, self-driving vehicles, and military operations. This book presents the work of researchers from a variety of perspectives and describes challenges, recent research results, lessons learned from applications, and recommendations for future research directions in EA. The historical perspectives of explainable agency and the importance of interactivity in explainable systems are also discussed. Ultimately, this book aims to contribute to the successful partnership between humans and AI systems. Features: Contributes to the topic of explainable artificial intelligence (XAI) Focuses on the XAI subtopic of explainable agency Includes an introductory chapter, a survey, and five other original contributions
Design Of Human Ai Interactions With Explainable Artificial Intelligence
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Author : Kilian Kluge
language : en
Publisher:
Release Date : 2021
Design Of Human Ai Interactions With Explainable Artificial Intelligence written by Kilian Kluge and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Artificial intelligence categories.
The Impact Of Explainable Ai On Knowledge In Human Ai Interactions
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Author : Philipp Spitzer
language : en
Publisher:
Release Date : 2025
The Impact Of Explainable Ai On Knowledge In Human Ai Interactions written by Philipp Spitzer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with categories.
Data Analytics And Artificial Intelligence For Predictive Maintenance In Smart Manufacturing
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Author : Amit Kumar Tyagi
language : en
Publisher: CRC Press
Release Date : 2024-10-23
Data Analytics And Artificial Intelligence For Predictive Maintenance In Smart Manufacturing written by Amit Kumar Tyagi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-23 with Computers categories.
Today, in this smart era, data analytics and artificial intelligence (AI) play an important role in predictive maintenance (PdM) within the manufacturing industry. This innovative approach aims to optimize maintenance strategies by predicting when equipment or machinery is likely to fail so that maintenance can be performed just in time to prevent costly breakdowns. This book contains up-to-date information on predictive maintenance and the latest advancements, trends, and tools required to reduce costs and save time for manufacturers and industries. Data Analytics and Artificial Intelligence for Predictive Maintenance in Smart Manufacturing provides an extensive and in-depth exploration of the intersection of data analytics, artificial intelligence, and predictive maintenance in the manufacturing industry and covers fundamental concepts, advanced techniques, case studies, and practical applications. Using a multidisciplinary approach, this book recognizes that predictive maintenance in manufacturing requires collaboration among engineers, data scientists, and business professionals and includes case studies from various manufacturing sectors showcasing successful applications of predictive maintenance. The real-world examples explain the useful benefits and ROI achieved by organizations. The emphasis is on scalability, making it suitable for both small and large manufacturing operations, and readers will learn how to adapt predictive maintenance strategies to different scales and industries. This book presents resources and references to keep readers updated on the latest advancements, tools, and trends, ensuring continuous learning. Serving as a reference guide, this book focuses on the latest advancements, trends, and tools relevant to predictive maintenance and can also serve as an educational resource for students studying manufacturing, data science, or related fields.
Human Ai Interaction
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Author : Readyai
language : en
Publisher:
Release Date : 2021-01-25
Human Ai Interaction written by Readyai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-25 with Juvenile Nonfiction categories.
This picture book for kids talks about the interaction between Artificial Intelligence & humans.
Artificial Intelligence In Hci
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Author : Helmut Degen
language : en
Publisher: Springer Nature
Release Date : 2024-05-31
Artificial Intelligence In Hci written by Helmut Degen and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-31 with Computers categories.
The three-volume book set LNAI 14734, 14735, and 14736 constitutes the refereed proceedings of 5th International Conference on Artificial Intelligence in HCI, AI-HCI 2024, held as part of the 26th International Conference, HCI International 2024, which took place in Washington, DC, USA, during June 29-July 4, 2024. The total of 1271 papers and 309 posters included in the HCII 2024 proceedings was carefully reviewed and selected from 5108 submissions. The AI-HCI 2024 proceedings were organized in the following topical sections: Part I: Human-centered artificial intelligence; explainability and transparency; AI systems and frameworks in HCI; Part II: Ethical considerations and trust in AI; enhancing user experience through AI-driven technologies; AI in industry and operations; Part III: Large language models for enhanced interaction; advancing human-robot interaction through AI; AI applications for social impact and human wellbeing.
Human Computer Interaction
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Author : Gavriel Salvendy
language : en
Publisher:
Release Date : 1993
Human Computer Interaction written by Gavriel Salvendy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993 with Computer software categories.
Human Ai Interaction And Collaboration
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Author : Dan Wu
language : en
Publisher: Cambridge University Press
Release Date : 2025-10-31
Human Ai Interaction And Collaboration written by Dan Wu and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-31 with Computers categories.
The integration of AI into information systems will affect the way users interface with these systems. This exploration of the interaction and collaboration between humans and AI reveals its potential and challenges, covering issues such as data privacy, credibility of results, misinformation, and search interactions. Later chapters delve into application domains such as healthcare and scientific discovery. In addition to providing new perspectives on and methods for developing AI technology and designing more humane and efficient artificial intelligence systems, the book also reveals the shortcomings of artificial intelligence technologies through case studies and puts forward corresponding countermeasures and suggestions. This book is ideal for researchers, students, and industry practitioners interested in enhancing human-centered AI systems and insights for future research.
Towards Useful Ai Interpretability For Humans Via Interactive Ai Explanations
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Author : Hua Shen
language : en
Publisher:
Release Date : 2023
Towards Useful Ai Interpretability For Humans Via Interactive Ai Explanations written by Hua Shen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Advancements in deep learning have revolutionized AI systems, enabling collaboration between humans and AI to enhance performance in specific tasks. AI explanations play a crucial role in aiding human understanding, control, and improvement of AI systems regarding various criteria such as fairness, safety, and trustworthiness. Despite the proliferation of eXplainable AI (XAI) approaches, the practical usefulness of AI explanations in human-AI collaborative systems remains underexplored. This doctoral research aims to evaluate and enhance the usefulness of AI explanations for humans in practical human-AI collaboration. I break down the research goal of investigating and improving human-centered useful AI explanations into three research questions: RQ1: Are cutting-edge AI explanations useful for humans in practice (Part I)? RQ2: What's the disparity between AI explanations and practical user demands (Part II)? RQ3: How to empower useful AI explanations with human-AI interaction (Part III)? We examined the three research questions by conducting four projects. To answer RQ1, we deployed two real-world human evaluation studies on analyzing computer vision AI model errors with post-hoc explanations and simulating NLP AI model predictions with inherent explanations, respectively. The two studies unveil that, surprisingly, AI explanations are not always useful for humans to analyze AI predictions in practice. This motivates our research for RQ2 -- gaining insights into disparities between the status quo of AI explanations and practical user needs. By surveying over 200 AI explanation papers and comparing with summarized real-world user demands, we observe two dominating findings: i) humans request diverse XAI questions across the AI pipeline to gain a global view of AI system, whereas existing XAI approaches commonly display a single AI explanation that can not satisfy diverse XAI user needs; ii) humans are widely interested in understanding what AI systems can not achieve, which might lead to the need of interactive AI explanations that enable humans to specify the counterfactual predictions. In light of these findings, we deeply deem that, instead of designating user demands by XAI researchers during AI system development, empowering users to communicate with AI systems for their practical XAI demands is critical to unleashing useful AI explanations (RQ3). To this end, we developed an interactive XAI system via conversations that improved the usefulness of AI explanations in terms of human-perceived performance in AI-assisted writing tasks. Overall, we summarize this doctoral research by discussing the limitations and challenges of human-centered useful AI explanations.