Tag Archives: Explainable

Explainable Human-AI Interaction: A Planning Perspective (Paperback or Softback)

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Explainable Human-AI Interaction: A Planning Perspective (Paperback or Softback)

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Are you looking to deepen your understanding of human-AI interaction from a planning perspective? Look no further than the groundbreaking book “Explainable Human-AI Interaction: A Planning Perspective.”

In this comprehensive guide, authors delve into the intricate relationship between humans and artificial intelligence, focusing on how planning plays a crucial role in facilitating communication and collaboration between the two entities. Through a series of case studies and theoretical frameworks, readers will gain valuable insights into how AI systems can be designed to be more transparent, interpretable, and accountable to human users.

Whether you’re a researcher, developer, or simply curious about the future of AI technology, this book is a must-read for anyone interested in the evolving landscape of human-AI interaction. Pick up your copy today in paperback or softback and embark on a journey to uncover the potential of explainable AI.
#Explainable #HumanAI #Interaction #Planning #Perspective #Paperback #Softback

Responsible AI in the Enterprise: Practical AI risk management for explainable,

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Responsible AI in the Enterprise: Practical AI risk management for explainable,

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transparent, and ethical AI deployment.

In today’s rapidly evolving digital landscape, the use of artificial intelligence (AI) in enterprises is becoming increasingly prevalent. While AI offers a plethora of benefits, such as increased efficiency, improved decision-making, and enhanced customer experiences, it also comes with its fair share of risks. To ensure that AI is deployed responsibly and ethically within an organization, it is crucial to implement effective AI risk management strategies.

One key aspect of responsible AI in the enterprise is the concept of explainability. In order to build trust with stakeholders and ensure transparency in decision-making processes, it is essential that AI systems are able to provide explanations for their recommendations and actions. This not only helps to mitigate the risk of bias or errors in AI algorithms but also enables organizations to better understand and interpret the outcomes of AI-driven decisions.

Another important consideration in AI risk management is the need for ethical AI deployment. This involves ensuring that AI systems are designed and implemented in a way that upholds ethical principles, such as fairness, accountability, and privacy. By embedding ethical considerations into the development and deployment of AI solutions, organizations can mitigate the risk of unintended consequences and ensure that AI is used in a responsible manner.

Ultimately, responsible AI in the enterprise requires a holistic approach to AI risk management that takes into account the technical, ethical, and societal implications of AI deployment. By prioritizing explainability, transparency, and ethical considerations in AI development and deployment, organizations can harness the full potential of AI while minimizing the associated risks.
#Responsible #Enterprise #Practical #risk #management #explainable

Explainable AI Within the Digital Transformation and Cyber Physical – ACCEPTABLE

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Explainable AI Within the Digital Transformation and Cyber Physical – ACCEPTABLE

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Explainable AI: Bridging the Gap in Digital Transformation and Cyber-Physical Systems

In today’s rapidly evolving technological landscape, the integration of artificial intelligence (AI) has become increasingly prevalent in various industries. From healthcare to finance, AI-powered solutions are driving digital transformation and revolutionizing the way organizations operate. However, the lack of transparency and interpretability in AI models has raised concerns about their trustworthiness and reliability.

Explainable AI (XAI) is a paradigm that aims to address this issue by providing insights into how AI algorithms make decisions. By enabling users to understand the reasoning behind AI-driven outcomes, XAI enhances the trust and adoption of AI technologies in critical applications such as cyber-physical systems.

In the context of digital transformation, XAI plays a crucial role in enabling organizations to effectively leverage AI capabilities while maintaining transparency and accountability. By providing explanations for AI-generated insights and recommendations, XAI helps decision-makers better understand the rationale behind AI-driven decisions and take appropriate actions.

In cyber-physical systems, where AI algorithms interact with physical infrastructure and devices, the importance of explainability cannot be overstated. Ensuring that AI models can be interpreted and validated is essential for building safe and reliable systems that can be trusted to operate in dynamic and complex environments.

Overall, XAI serves as a bridge between AI technologies and human users, enabling effective collaboration and communication in the digital transformation and cyber-physical domains. By promoting transparency, accountability, and trust in AI systems, XAI paves the way for the responsible and ethical deployment of AI technologies in critical applications.

In conclusion, the integration of explainable AI within the digital transformation and cyber-physical systems is not only acceptable but necessary for ensuring the success and sustainability of AI-driven initiatives. As organizations continue to harness the power of AI technologies, it is essential to prioritize transparency and interpretability to build trust and confidence in AI systems.
#Explainable #Digital #Transformation #Cyber #Physical #ACCEPTABLE

P. Paramasivan Explainable AI Applications for Human Beha (Hardback) (UK IMPORT)

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P. Paramasivan Explainable AI Applications for Human Beha (Hardback) (UK IMPORT)

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“Unlocking the Potential of Explainable AI in Understanding Human Behavior: P. Paramasivan’s Groundbreaking Book Now Available in the UK!”

In his latest hardback release, renowned AI researcher P. Paramasivan delves deep into the realm of Explainable AI and its applications in deciphering human behavior. This UK-imported book offers a comprehensive insight into how advanced AI algorithms can help us make sense of the complexities of human actions and decision-making processes.

From predicting consumer behavior to analyzing social media interactions, Paramasivan’s cutting-edge research sheds light on the potential of Explainable AI to revolutionize the way we understand and interpret human behavior. Whether you’re a tech enthusiast, a psychology buff, or simply curious about the intersection of AI and human nature, this book is a must-read for anyone interested in the future of technology and its impact on society.

Don’t miss out on this groundbreaking exploration of Explainable AI applications – order your copy of P. Paramasivan’s latest book today and embark on a journey towards a deeper understanding of human behavior in the digital age.
#Paramasivan #Explainable #Applications #Human #Beha #Hardback #IMPORT

Wojciech Samek Explainable AI: Interpreting, Explaining (Paperback) (UK IMPORT)

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Wojciech Samek Explainable AI: Interpreting, Explaining (Paperback) (UK IMPORT)

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“Unraveling the Mysteries of Artificial Intelligence: Wojciech Samek’s ‘Explainable AI'”

In today’s world, the use of artificial intelligence has become increasingly prevalent, influencing various aspects of our daily lives. However, the black-box nature of AI algorithms often leaves users questioning how decisions are made and why certain outcomes are predicted. Enter Wojciech Samek, a leading expert in the field of Explainable AI.

In his groundbreaking book, “Explainable AI: Interpreting, Explaining,” Samek delves into the intricacies of AI algorithms and offers a comprehensive guide to understanding and interpreting their decision-making processes. Through his research, Samek aims to demystify the inner workings of AI systems and provide users with the tools to comprehend and trust the outcomes they produce.

This UK-imported paperback is a must-read for anyone seeking to gain a deeper understanding of AI technologies and their implications. Whether you’re a seasoned AI professional or a curious novice, Samek’s insights are sure to enlighten and inspire. Don’t miss out on this invaluable resource – order your copy today!
#Wojciech #Samek #Explainable #Interpreting #Explaining #Paperback #IMPORT

The Operational Excellence Library; Mastering Explainable AI

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Price: $89.97 - $81.18
(as of Dec 25,2024 14:35:40 UTC – Details)



In today’s rapidly evolving business landscape, the need for operational excellence has never been greater. With the rise of artificial intelligence and machine learning, organizations are increasingly turning to these technologies to drive efficiency and productivity. However, as AI becomes more prevalent in business operations, the concept of explainability has become a critical issue.

Explainable AI, or XAI, refers to the ability of AI systems to provide clear and understandable explanations for their decisions and actions. This is especially important in industries such as healthcare, finance, and law, where the stakes are high and decisions must be transparent and accountable.

To help businesses master the concept of explainable AI and achieve operational excellence, we have curated a selection of resources in our Operational Excellence Library. From whitepapers and case studies to webinars and training modules, our library is designed to provide organizations with the tools and knowledge they need to implement XAI successfully.

By mastering explainable AI, businesses can enhance decision-making processes, increase trust in AI systems, and ultimately drive better business outcomes. Visit our Operational Excellence Library today to start your journey towards mastering explainable AI.
#Operational #Excellence #Library #Mastering #Explainable

Explainable AI in Healthcare and Medicine HARDCOVER 2020 by Arash Shaban-Nejad

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Explainable AI in Healthcare and Medicine HARDCOVER 2020 by Arash Shaban-Nejad

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Explainable AI in Healthcare and Medicine HARDCOVER 2020 by Arash Shaban-Nejad: A Comprehensive Guide

In the rapidly evolving field of healthcare and medicine, artificial intelligence (AI) has become an indispensable tool for diagnosing diseases, predicting outcomes, and optimizing treatment plans. However, the black box nature of AI algorithms has raised concerns about their transparency, accountability, and interpretability.

In his groundbreaking book, “Explainable AI in Healthcare and Medicine,” renowned researcher Arash Shaban-Nejad provides a comprehensive guide to understanding and implementing explainable AI in healthcare settings. Drawing on his extensive experience in the field, Shaban-Nejad explores the importance of transparency and interpretability in AI systems, and offers practical strategies for developing and evaluating explainable AI models.

From explaining the basics of AI and machine learning to discussing the latest advances in healthcare AI applications, Shaban-Nejad covers a wide range of topics in this must-read book. Whether you are a healthcare provider, researcher, policymaker, or AI enthusiast, this book will provide you with valuable insights and practical tools for harnessing the power of AI in healthcare while ensuring transparency and accountability.

Don’t miss out on this essential resource for anyone interested in the intersection of AI, healthcare, and medicine. Order your copy of “Explainable AI in Healthcare and Medicine HARDCOVER 2020” by Arash Shaban-Nejad today!
#Explainable #Healthcare #Medicine #HARDCOVER #Arash #ShabanNejad

Explainable Artificial Intelligence and Solar Energy Integration

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Price: $435.00
(as of Dec 25,2024 13:18:25 UTC – Details)




ASIN ‏ : ‎ B0DK7VW9PQ
Publisher ‏ : ‎ IGI Global (October 16, 2024)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 506 pages
ISBN-13 ‏ : ‎ 979-8369378229
Item Weight ‏ : ‎ 2.4 pounds
Dimensions ‏ : ‎ 7 x 1.13 x 10 inches


Explainable Artificial Intelligence (XAI) and Solar Energy Integration: A Bright Future Ahead

As the world continues to shift towards renewable energy sources, the integration of solar energy into our everyday lives has become increasingly important. One of the key technologies driving this integration is Explainable Artificial Intelligence (XAI).

XAI is a subset of artificial intelligence that focuses on making AI systems more transparent and understandable to humans. This is crucial when it comes to the integration of solar energy systems, as it allows users to better understand how the technology works and how it can be optimized for maximum efficiency.

By using XAI algorithms, solar energy systems can provide real-time data on energy production, consumption, and storage. This information can then be used to make informed decisions on how to best utilize solar energy resources, ultimately leading to cost savings and reduced environmental impact.

Additionally, XAI can help identify potential issues with solar energy systems before they become major problems, allowing for proactive maintenance and improved system reliability.

Overall, the integration of XAI with solar energy systems holds great promise for the future of renewable energy. By making these systems more transparent and understandable, we can better harness the power of the sun and move towards a more sustainable energy future.
#Explainable #Artificial #Intelligence #Solar #Energy #Integration

Interpretable AI: Building explainable machine learning systems

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Interpretable AI: Building explainable machine learning systems

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Interpretable AI: Building explainable machine learning systems

In recent years, artificial intelligence and machine learning technologies have made significant advancements, with algorithms becoming more complex and powerful. However, as these algorithms become more sophisticated, they also become less interpretable and harder to understand for humans.

This lack of interpretability has raised concerns about the potential biases and errors that may be embedded in these machine learning systems, as well as the ethical implications of using opaque algorithms to make decisions that can have a significant impact on people’s lives.

To address these concerns, researchers and practitioners are now focusing on building interpretable AI systems that are transparent and explainable. These systems not only provide accurate predictions but also offer insights into how these predictions were made, allowing users to understand and trust the decisions made by the AI.

There are several approaches to building interpretable AI systems, including using simpler models that are easier to interpret, incorporating human feedback into the learning process, and developing visualization tools that help users understand the inner workings of the algorithms.

By building explainable machine learning systems, we can ensure that AI technologies are used ethically and responsibly, and that they are accountable for the decisions they make. Interpretable AI is not just about creating more transparent algorithms, but also about fostering trust and understanding between humans and machines.
#Interpretable #Building #explainable #machine #learning #systems

Explainable AI and Blockchain for Secure and Agile Supply Chains: Enhancing Transparency, Traceability, and Accountability

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Price: $150.00
(as of Dec 25,2024 12:38:50 UTC – Details)




Publisher ‏ : ‎ Chapman and Hall/CRC; 1st edition (May 22, 2025)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 248 pages
ISBN-10 ‏ : ‎ 1032803746
ISBN-13 ‏ : ‎ 978-1032803746
Item Weight ‏ : ‎ 15.8 ounces


In today’s fast-paced and interconnected world, supply chains play a critical role in ensuring the smooth flow of goods and services. However, the increasing complexity and global nature of supply chains have also introduced new challenges, such as ensuring transparency, traceability, and accountability throughout the supply chain.

To address these challenges, many organizations are turning to technologies such as Explainable AI and Blockchain. Explainable AI refers to artificial intelligence systems that are designed to provide clear explanations of their decisions and actions, allowing users to understand and trust the algorithms behind them. This is crucial for supply chain management, as it can help identify potential risks, optimize processes, and improve decision-making.

On the other hand, Blockchain technology offers a secure and immutable way to record and track transactions across a network of computers. By using Blockchain in supply chains, organizations can create a transparent and tamper-proof record of every transaction, from the sourcing of raw materials to the delivery of the final product. This not only enhances traceability but also helps ensure accountability throughout the supply chain.

By combining Explainable AI and Blockchain, organizations can create a more secure and agile supply chain that is better equipped to handle the challenges of today’s global marketplace. These technologies can help enhance transparency, traceability, and accountability, ultimately improving efficiency, reducing risks, and building trust among all stakeholders in the supply chain.

In conclusion, Explainable AI and Blockchain have the potential to revolutionize supply chain management by providing greater visibility and control over every aspect of the supply chain. By leveraging these technologies, organizations can enhance transparency, traceability, and accountability, leading to a more secure and agile supply chain that can adapt to the demands of the modern marketplace.
#Explainable #Blockchain #Secure #Agile #Supply #Chains #Enhancing #Transparency #Traceability #Accountability