Tag Archives: explainable AI

AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI by Batarseh

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AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI by Batarseh

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AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI by Batarseh

In the rapidly evolving field of artificial intelligence (AI), ensuring that AI systems are trustworthy, explainable, safe, and ethical is of utmost importance. As AI systems become more integrated into our daily lives, it is essential that we can trust them to make decisions that are fair, reliable, and in alignment with our values.

In his groundbreaking work, Dr. Sameh Batarseh explores the concept of AI assurance, which encompasses a set of principles and practices aimed at ensuring that AI systems meet the highest standards of trustworthiness, explainability, safety, and ethicality.

Trustworthiness is a key aspect of AI assurance, as it involves ensuring that AI systems are reliable, accurate, and free from bias. By employing rigorous testing and validation processes, AI developers can ensure that their systems perform as intended and can be trusted to make decisions in a wide range of scenarios.

Explainability is another crucial component of AI assurance, as it involves ensuring that AI systems can provide clear and understandable explanations for their decisions and actions. By designing AI systems with built-in transparency and interpretability, developers can empower users to understand and trust the decisions made by AI systems.

Safety is also a critical consideration in AI assurance, as it involves ensuring that AI systems are designed to operate safely and securely in a wide range of environments. By implementing robust security measures and safety protocols, AI developers can minimize the risk of harm and ensure the safe operation of AI systems.

Finally, ethicality is a fundamental aspect of AI assurance, as it involves ensuring that AI systems are designed and deployed in a manner that is consistent with our values and ethical principles. By incorporating ethical guidelines and standards into the design and development of AI systems, developers can ensure that their systems uphold the highest standards of ethical conduct.

In conclusion, AI assurance is essential for ensuring that AI systems are trustworthy, explainable, safe, and ethical. By following the principles and practices outlined by Dr. Sameh Batarseh, AI developers can build AI systems that meet the highest standards of performance, reliability, and ethicality, and can be trusted to make decisions that benefit society as a whole.
#Assurance #Trustworthy #Explainable #Safe #Ethical #Batarseh

Explainable Artificial Intelligence : First World Conference, Xai 2023, Lisbo…

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Explainable Artificial Intelligence : First World Conference, Xai 2023, Lisbo…

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The field of artificial intelligence has seen tremendous growth in recent years, with new advancements being made constantly. One area that has gained increasing importance is explainable artificial intelligence (XAI), which aims to make AI systems more transparent and understandable to humans.

To address this growing need, the first World Conference on Explainable Artificial Intelligence (XAI) will be held in Lisbon in 2023. The conference will bring together experts from academia, industry, and government to discuss the latest research and developments in the field of XAI.

Topics to be covered at the conference include:

– Techniques for making AI systems more interpretable and explainable
– The ethical implications of using AI in decision-making processes
– Tools and frameworks for explaining AI algorithms to non-experts
– Case studies of successful applications of XAI in various industries

Attendees can look forward to keynote speeches from leading experts in the field, panel discussions, workshops, and networking opportunities. The conference aims to foster collaboration and knowledge sharing among researchers and practitioners working in the field of XAI.

Don’t miss this opportunity to be a part of the inaugural World Conference on Explainable Artificial Intelligence in Lisbon in 2023. Stay tuned for more details on registration and call for papers!
#Explainable #Artificial #Intelligence #World #Conference #Xai #Lisbo..

Antonio Di Cecco – Explainable AI with Python – New Paperback – T555z

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Antonio Di Cecco – Explainable AI with Python – New Paperback – T555z

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Antonio Di Cecco – Explainable AI with Python – New Paperback – T555z

Exciting news for all AI enthusiasts and Python developers! Antonio Di Cecco has released a new paperback book titled “Explainable AI with Python” that delves into the world of interpretable and transparent AI models.

In this book, Di Cecco explores the importance of understanding how AI models make decisions and provides readers with practical techniques for making these models more explainable. By using Python, readers will learn how to implement various interpretability methods and tools to gain insights into the inner workings of their AI systems.

Whether you are a seasoned data scientist or a beginner in the field of AI, this book is the perfect resource for anyone looking to demystify the black box of machine learning models. With Di Cecco’s clear and concise explanations, readers will be able to enhance the transparency and trustworthiness of their AI systems.

Don’t miss out on the opportunity to learn from one of the leading experts in the field of explainable AI. Get your hands on “Explainable AI with Python” today and take your AI projects to the next level!
#Antonio #Cecco #Explainable #Python #Paperback #T555z

Explainable, Interpretable, and Transparent AI Systems by B.K. Tripathy Hardcove

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Explainable, Interpretable, and Transparent AI Systems by B.K. Tripathy Hardcove

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In the book “Explainable, Interpretable, and Transparent AI Systems” by B.K. Tripathy, readers are taken on a journey into the world of artificial intelligence and the importance of creating systems that are not only powerful and efficient, but also understandable and accountable.

Tripathy delves into the complexities of AI systems and the potential risks and challenges they pose if they are not transparent and interpretable. He emphasizes the need for AI systems to be explainable in order for users to trust and rely on them, as well as to comply with regulations and ethical standards.

Through practical examples and case studies, Tripathy illustrates the benefits of implementing explainable AI systems, such as improved decision-making, increased user trust, and enhanced accountability. He also discusses various techniques and methods for making AI systems more interpretable, such as feature importance analysis, model explanation tools, and transparency frameworks.

Overall, “Explainable, Interpretable, and Transparent AI Systems” serves as a comprehensive guide for developers, researchers, and policymakers looking to design AI systems that prioritize transparency and accountability. It is a must-read for anyone interested in the future of AI and the ethical implications of its widespread adoption.
#Explainable #Interpretable #Transparent #Systems #B.K #Tripathy #Hardcove

Explainable Artificial Intelligence in the Digital Sustainability Administration

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Explainable Artificial Intelligence in the Digital Sustainability Administration

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Explainable Artificial Intelligence (XAI) is a crucial aspect of the Digital Sustainability Administration, as it provides transparency and accountability in the decision-making process of AI systems.

In the context of sustainability, XAI ensures that the decisions made by AI algorithms are not only accurate and efficient but also understandable and explainable to humans. This is important because it allows stakeholders to trust the AI systems and make informed decisions based on the insights provided by these systems.

By incorporating XAI into the Digital Sustainability Administration, organizations can ensure that their AI systems are not only effective in achieving sustainability goals but also transparent in how they reach those goals. This transparency is essential for building trust with stakeholders and ensuring that AI systems are used responsibly and ethically.

Overall, XAI plays a crucial role in the Digital Sustainability Administration by providing transparency, accountability, and trust in the decision-making process of AI systems. It allows organizations to harness the power of AI for sustainability while ensuring that these systems are used in a responsible and ethical manner.
#Explainable #Artificial #Intelligence #Digital #Sustainability #Administration

Role of Explainable Artificial Intelligence in E-commerce, Hardcover by Gaur,…

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Role of Explainable Artificial Intelligence in E-commerce, Hardcover by Gaur,…

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The Role of Explainable Artificial Intelligence in E-commerce: A Comprehensive Guide by Gaur, Hardcover Edition

In today’s rapidly evolving digital landscape, e-commerce businesses are constantly seeking ways to enhance customer experience, increase sales, and streamline operations. One technology that is revolutionizing the e-commerce industry is Explainable Artificial Intelligence (XAI).

In his latest book, “The Role of Explainable Artificial Intelligence in E-commerce,” renowned expert Gaur delves into the significance of XAI in the e-commerce sector. This comprehensive guide offers a deep dive into how XAI is reshaping the way businesses operate, make decisions, and interact with customers.

From personalized product recommendations and targeted marketing strategies to fraud detection and inventory management, XAI plays a crucial role in optimizing various aspects of e-commerce operations. By providing transparency and insights into the decision-making process of AI algorithms, XAI helps businesses build trust with customers and regulators, ultimately leading to better outcomes.

Whether you are a business owner, marketer, or AI enthusiast, this hardcover edition is a must-read for anyone looking to stay ahead of the curve in the e-commerce industry. Get your hands on a copy today and unlock the potential of Explainable Artificial Intelligence in driving success for your e-commerce business.
#Role #Explainable #Artificial #Intelligence #Ecommerce #Hardcover #Gaur..

Explainable Deep Learning AI: Methods and Challenges by Jenny Benois-Pineau (Eng

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Explainable Deep Learning AI: Methods and Challenges by Jenny Benois-Pineau (Eng

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In her recent paper, “Explainable Deep Learning AI: Methods and Challenges,” Jenny Benois-Pineau delves into the complexities of creating AI systems that are not only accurate but also transparent and interpretable. The rise of deep learning has revolutionized the field of artificial intelligence, but the “black box” nature of many deep learning models has raised concerns about their reliability and trustworthiness.

Benois-Pineau highlights the importance of explainability in AI systems, especially in high-stakes applications such as healthcare, finance, and autonomous vehicles. She introduces several methods for making deep learning models more explainable, including feature visualization, attention mechanisms, and model-agnostic techniques like LIME and SHAP.

However, Benois-Pineau also acknowledges the challenges of creating explainable deep learning AI. These challenges include the trade-off between model complexity and interpretability, the need for domain-specific knowledge to interpret model outputs, and the potential for adversarial attacks to undermine the reliability of explainable AI systems.

Overall, Benois-Pineau’s paper provides a comprehensive overview of the methods and challenges of creating explainable deep learning AI. By addressing these challenges, researchers and practitioners can build AI systems that are not only accurate but also transparent and trustworthy, paving the way for safer and more ethical applications of artificial intelligence.
#Explainable #Deep #Learning #Methods #Challenges #Jenny #BenoisPineau #Eng

Angewandte Data Science: Projekte | Methoden | Prozesse (German Edition)

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Price: $37.99 - $7.08
(as of Dec 27,2024 04:25:19 UTC – Details)




Publisher ‏ : ‎ Springer Vieweg; 1. Aufl. 2023 edition (June 27, 2023)
Language ‏ : ‎ German
Paperback ‏ : ‎ 312 pages
ISBN-10 ‏ : ‎ 3658396245
ISBN-13 ‏ : ‎ 978-3658396244
Item Weight ‏ : ‎ 1.17 pounds
Dimensions ‏ : ‎ 6.61 x 0.71 x 9.45 inches


Angewandte Data Science: Projekte | Methoden | Prozesse (German Edition)

In der Welt der Datenwissenschaft werden Projekte immer komplexer und vielfältiger. Die richtigen Methoden und Prozesse sind entscheidend, um erfolgreich zu sein. In dieser deutschen Ausgabe werden wir uns mit verschiedenen Projekten, Methoden und Prozessen im Bereich der angewandten Datenwissenschaft befassen.

Wir werden uns mit Fallstudien und Praxisbeispielen aus verschiedenen Branchen beschäftigen und untersuchen, wie Data Science dazu beitragen kann, komplexe Probleme zu lösen und fundierte Entscheidungen zu treffen. Wir werden auch verschiedene Methoden und Tools diskutieren, die bei der Durchführung von Datenanalysen und der Entwicklung von Modellen verwendet werden.

Egal, ob Sie ein erfahrener Datenwissenschaftler sind oder gerade erst in das Feld einsteigen, diese deutsche Ausgabe wird Ihnen wertvolle Einblicke und Informationen bieten, um Ihre Fähigkeiten und Kenntnisse im Bereich der angewandten Datenwissenschaft zu erweitern. Bleiben Sie dran für spannende Inhalte und Diskussionen zu diesem faszinierenden Thema!
#Angewandte #Data #Science #Projekte #Methoden #Prozesse #German #Edition

Artificial Intelligence in Pathological Image Analysis

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Price: $96.85 - $84.57
(as of Dec 27,2024 03:53:17 UTC – Details)




Publisher ‏ : ‎ Mdpi AG (October 16, 2024)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 266 pages
ISBN-10 ‏ : ‎ 3725821410
ISBN-13 ‏ : ‎ 978-3725821419
Item Weight ‏ : ‎ 1.7 pounds
Dimensions ‏ : ‎ 6.69 x 0.88 x 9.61 inches


Artificial Intelligence (AI) is revolutionizing the field of pathology by enhancing the accuracy and efficiency of image analysis. Pathologists are tasked with examining tissue samples to diagnose diseases, and AI tools are being developed to assist in this process.

One area where AI is making significant strides is in the analysis of pathological images. These images, such as those obtained from biopsies or imaging scans, contain crucial information that can aid in diagnosing diseases like cancer. AI algorithms can be trained to recognize patterns and abnormalities in these images, allowing for quicker and more accurate diagnoses.

AI can also help pathologists by providing quantitative data and measurements that may be difficult to discern with the naked eye. This can improve the consistency and reliability of pathology reports, leading to better patient outcomes.

Furthermore, AI can facilitate the sharing and collaboration of pathological images, allowing pathologists from around the world to access and analyze cases remotely. This can be particularly beneficial in areas with limited access to expert pathology services.

Overall, AI is proving to be a valuable tool in the field of pathology, improving the accuracy and efficiency of image analysis and ultimately benefiting patients by enabling faster and more accurate diagnoses.
#Artificial #Intelligence #Pathological #Image #Analysis

Sprachmodelle verstehen: Chatbots und generative künstliche Intelligenz im Zusammenhang (German Edition)

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Price: $24.99 - $15.51
(as of Dec 27,2024 03:21:53 UTC – Details)




Publisher ‏ : ‎ Springer; 2024th edition (June 13, 2024)
Language ‏ : ‎ German
Paperback ‏ : ‎ 222 pages
ISBN-10 ‏ : ‎ 3662682796
ISBN-13 ‏ : ‎ 978-3662682791
Item Weight ‏ : ‎ 11.2 ounces
Dimensions ‏ : ‎ 6.14 x 0.47 x 9.21 inches


Sprachmodelle verstehen: Chatbots und generative künstliche Intelligenz im Zusammenhang

In der Welt der künstlichen Intelligenz und Chatbots spielen Sprachmodelle eine entscheidende Rolle. Diese Modelle ermöglichen es Maschinen, menschenähnliche Interaktionen durchzuführen und auf natürliche Sprache zu reagieren. Generative künstliche Intelligenz, wie sie in Chatbots verwendet wird, basiert auf fortschrittlichen Sprachmodellen, die in der Lage sind, menschenähnliche Texte zu generieren.

Chatbots sind Programme, die mit Benutzern über Textnachrichten oder Sprache kommunizieren und ihnen bei verschiedenen Aufgaben helfen können. Sie können in verschiedenen Bereichen eingesetzt werden, wie Kundenservice, Marketing, E-Commerce und mehr. Chatbots verwenden Sprachmodelle, um menschenähnliche Antworten zu generieren und mit Benutzern auf eine natürliche Weise zu interagieren.

Generative künstliche Intelligenz wird oft verwendet, um Chatbots mit fortschrittlichen Fähigkeiten auszustatten, wie zum Beispiel die Fähigkeit, menschenähnliche Texte zu schreiben, Fragen zu beantworten und sogar Gespräche zu führen. Diese Modelle basieren auf großen Mengen von Daten und können lernen, menschenähnliche Sprache zu verstehen und zu generieren.

Insgesamt spielen Sprachmodelle eine entscheidende Rolle bei der Entwicklung von Chatbots und generativer künstlicher Intelligenz. Sie ermöglichen es Maschinen, auf natürliche Sprache zu reagieren und menschenähnliche Interaktionen zu führen. Durch die Weiterentwicklung von Sprachmodellen können Chatbots immer fortschrittlichere Fähigkeiten erlangen und in verschiedenen Bereichen eingesetzt werden.
#Sprachmodelle #verstehen #Chatbots #und #generative #künstliche #Intelligenz #Zusammenhang #German #Edition