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Author : Bhavya Kailkhura
Publisher : Frontiers Media SA
ISBN 13 : 2889714144
Total Pages : 101 pages
Book Rating : 4.8/5 (897 download)
Download or read book Safe and Trustworthy Machine Learning written by Bhavya Kailkhura and published by Frontiers Media SA. This book was released on 2021-10-29 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yada Pruksachatkun
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 109812023X
Total Pages : 304 pages
Book Rating : 4.0/5 (981 download)
Download or read book Practicing Trustworthy Machine Learning written by Yada Pruksachatkun and published by "O'Reilly Media, Inc.". This book was released on 2023-01-03 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increasing use of AI in high-stakes domains such as medicine, law, and defense, organizations spend a lot of time and money to make ML models trustworthy. Many books on the subject offer deep dives into theories and concepts. This guide provides a practical starting point to help development teams produce models that are secure, more robust, less biased, and more explainable. Authors Yada Pruksachatkun, Matthew McAteer, and Subhabrata Majumdar translate best practices in the academic literature for curating datasets and building models into a blueprint for building industry-grade trusted ML systems. With this book, engineers and data scientists will gain a much-needed foundation for releasing trustworthy ML applications into a noisy, messy, and often hostile world. You'll learn: Methods to explain ML models and their outputs to stakeholders How to recognize and fix fairness concerns and privacy leaks in an ML pipeline How to develop ML systems that are robust and secure against malicious attacks Important systemic considerations, like how to manage trust debt and which ML obstacles require human intervention
Author : Hao Chen
Publisher : Springer Nature
ISBN 13 : 3031395395
Total Pages : 207 pages
Book Rating : 4.0/5 (313 download)
Download or read book Trustworthy Machine Learning for Healthcare written by Hao Chen and published by Springer Nature. This book was released on 2023-07-30 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of First International Workshop, TML4H 2023, held virtually, in May 2023. The 16 full papers included in this volume were carefully reviewed and selected from 30 submissions. The goal of this workshop is to bring together experts from academia, clinic, and industry with an insightful vision of promoting trustworthy machine learning in healthcare in terms of scalability, accountability, and explainability.
Author : Ben Shneiderman
Publisher : Oxford University Press
ISBN 13 : 0192845292
Total Pages : 390 pages
Book Rating : 4.1/5 (928 download)
Download or read book Human-Centered AI written by Ben Shneiderman and published by Oxford University Press. This book was released on 2022 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: The remarkable progress in algorithms for machine and deep learning have opened the doors to new opportunities, and some dark possibilities. However, a bright future awaits those who build on their working methods by including HCAI strategies of design and testing. As many technology companies and thought leaders have argued, the goal is not to replace people, but to empower them by making design choices that give humans control over technology. In Human-Centered AI, Professor Ben Shneiderman offers an optimistic realist's guide to how artificial intelligence can be used to augment and enhance humans' lives. This project bridges the gap between ethical considerations and practical realities to offer a road map for successful, reliable systems. Digital cameras, communications services, and navigation apps are just the beginning. Shneiderman shows how future applications will support health and wellness, improve education, accelerate business, and connect people in reliable, safe, and trustworthy ways that respect human values, rights, justice, and dignity.
Author : Beena Ammanath
Publisher : John Wiley & Sons
ISBN 13 : 1119867959
Total Pages : 230 pages
Book Rating : 4.1/5 (198 download)
Download or read book Trustworthy AI written by Beena Ammanath and published by John Wiley & Sons. This book was released on 2022-03-15 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential resource on artificial intelligence ethics for business leaders In Trustworthy AI, award-winning executive Beena Ammanath offers a practical approach for enterprise leaders to manage business risk in a world where AI is everywhere by understanding the qualities of trustworthy AI and the essential considerations for its ethical use within the organization and in the marketplace. The author draws from her extensive experience across different industries and sectors in data, analytics and AI, the latest research and case studies, and the pressing questions and concerns business leaders have about the ethics of AI. Filled with deep insights and actionable steps for enabling trust across the entire AI lifecycle, the book presents: In-depth investigations of the key characteristics of trustworthy AI, including transparency, fairness, reliability, privacy, safety, robustness, and more A close look at the potential pitfalls, challenges, and stakeholder concerns that impact trust in AI application Best practices, mechanisms, and governance considerations for embedding AI ethics in business processes and decision making Written to inform executives, managers, and other business leaders, Trustworthy AI breaks new ground as an essential resource for all organizations using AI.
Author : Kush R. Vashney
Publisher :
ISBN 13 :
Total Pages : 256 pages
Book Rating : 4.4/5 (119 download)
Download or read book Trustworthy Machine Learning written by Kush R. Vashney and published by . This book was released on 2022 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Yada Pruksachatkun
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098120248
Total Pages : 303 pages
Book Rating : 4.0/5 (981 download)
Download or read book Practicing Trustworthy Machine Learning written by Yada Pruksachatkun and published by "O'Reilly Media, Inc.". This book was released on 2023-01-03 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the increasing use of AI in high-stakes domains such as medicine, law, and defense, organizations spend a lot of time and money to make ML models trustworthy. Many books on the subject offer deep dives into theories and concepts. This guide provides a practical starting point to help development teams produce models that are secure, more robust, less biased, and more explainable. Authors Yada Pruksachatkun, Matthew McAteer, and Subhabrata Majumdar translate best practices in the academic literature for curating datasets and building models into a blueprint for building industry-grade trusted ML systems. With this book, engineers and data scientists will gain a much-needed foundation for releasing trustworthy ML applications into a noisy, messy, and often hostile world. You'll learn: Methods to explain ML models and their outputs to stakeholders How to recognize and fix fairness concerns and privacy leaks in an ML pipeline How to develop ML systems that are robust and secure against malicious attacks Important systemic considerations, like how to manage trust debt and which ML obstacles require human intervention
Author : Fredrik Heintz
Publisher : Springer Nature
ISBN 13 : 3030739597
Total Pages : 278 pages
Book Rating : 4.0/5 (37 download)
Download or read book Trustworthy AI - Integrating Learning, Optimization and Reasoning written by Fredrik Heintz and published by Springer Nature. This book was released on 2021-04-12 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed conference proceedings of the First International Workshop on the Foundation of Trustworthy AI - Integrating Learning, Optimization and Reasoning, TAILOR 2020, held virtually in September 2020, associated with ECAI 2020, the 24th European Conference on Artificial Intelligence. The 11 revised full papers presented together with 6 short papers and 6 position papers were reviewed and selected from 52 submissions. The contributions address various issues for Trustworthiness, Learning, reasoning, and optimization, Deciding and Learning How to Act, AutoAI, and Reasoning and Learning in Social Contexts.
Author : Rachid Guerraoui
Publisher : Springer Nature
ISBN 13 : 9819706882
Total Pages : 180 pages
Book Rating : 4.8/5 (197 download)
Download or read book Robust Machine Learning written by Rachid Guerraoui and published by Springer Nature. This book was released on with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 : 9781728140858
Total Pages : pages
Book Rating : 4.1/5 (48 download)
Download or read book 2020 54th Annual Conference on Information Sciences and Systems (CISS). written by and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Lance Eliot
Publisher :
ISBN 13 : 9780692800614
Total Pages : 210 pages
Book Rating : 4.8/5 (6 download)
Download or read book AI Guardian Angel Bots for Deep AI Trustworthiness written by Lance Eliot and published by . This book was released on 2016-10-24 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI practitioner and noted "AI Insider" thought leader, Dr. Lance Eliot, MBA, PhD, provides ground breaking work on the emergence of AI Guardian Angel Bots. Dr. Eliot points out that with the advent of Deep AI and Machine Learning, there is both great promise and potential peril for consumers. Will people trust their self-driving cars and other smart devices as the Internet of Things (IoT) takes hold? Should they trust these Deep AI enabled systems? One means to bolster trust in Deep AI is to have consumers protect themselves and their safety by making use of AI Guardian Angel Bots. These new Bots are intended to monitor and potentially guide a Deep AI system that the consumer is dependent on. Your AI Guardian Angel Bot will be your guardian or protector when being driven by a self-driving car, and in any other situation that entails a dependency on Deep AI and Machine Learning. Readable by those interested in the latest in AI, this book is intended for business leaders, technology experts, and anyone with an interest in getting an edge on safety in the AI burgeoning world that we live in.
Author : Xiaowei Huang
Publisher : Springer Nature
ISBN 13 : 9811968144
Total Pages : 319 pages
Book Rating : 4.8/5 (119 download)
Download or read book Machine Learning Safety written by Xiaowei Huang and published by Springer Nature. This book was released on 2023-04-28 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning algorithms allow computers to learn without being explicitly programmed. Their application is now spreading to highly sophisticated tasks across multiple domains, such as medical diagnostics or fully autonomous vehicles. While this development holds great potential, it also raises new safety concerns, as machine learning has many specificities that make its behaviour prediction and assessment very different from that for explicitly programmed software systems. This book addresses the main safety concerns with regard to machine learning, including its susceptibility to environmental noise and adversarial attacks. Such vulnerabilities have become a major roadblock to the deployment of machine learning in safety-critical applications. The book presents up-to-date techniques for adversarial attacks, which are used to assess the vulnerabilities of machine learning models; formal verification, which is used to determine if a trained machine learning model is free of vulnerabilities; and adversarial training, which is used to enhance the training process and reduce vulnerabilities. The book aims to improve readers’ awareness of the potential safety issues regarding machine learning models. In addition, it includes up-to-date techniques for dealing with these issues, equipping readers with not only technical knowledge but also hands-on practical skills.
Author : Feras A. Batarseh
Publisher : Academic Press
ISBN 13 : 0323918824
Total Pages : 602 pages
Book Rating : 4.3/5 (239 download)
Download or read book AI Assurance written by Feras A. Batarseh and published by Academic Press. This book was released on 2022-10-12 with total page 602 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI Assurance: Towards Trustworthy, Explainable, Safe, and Ethical AI provides readers with solutions and a foundational understanding of the methods that can be applied to test AI systems and provide assurance. Anyone developing software systems with intelligence, building learning algorithms, or deploying AI to a domain-specific problem (such as allocating cyber breaches, analyzing causation at a smart farm, reducing readmissions at a hospital, ensuring soldiers’ safety in the battlefield, or predicting exports of one country to another) will benefit from the methods presented in this book. As AI assurance is now a major piece in AI and engineering research, this book will serve as a guide for researchers, scientists and students in their studies and experimentation. Moreover, as AI is being increasingly discussed and utilized at government and policymaking venues, the assurance of AI systems—as presented in this book—is at the nexus of such debates. Provides readers with an in-depth understanding of how to develop and apply Artificial Intelligence in a valid, explainable, fair and ethical manner Includes various AI methods, including Deep Learning, Machine Learning, Reinforcement Learning, Computer Vision, Agent-Based Systems, Natural Language Processing, Text Mining, Predictive Analytics, Prescriptive Analytics, Knowledge-Based Systems, and Evolutionary Algorithms Presents techniques for efficient and secure development of intelligent systems in a variety of domains, such as healthcare, cybersecurity, government, energy, education, and more Covers complete example datasets that are associated with the methods and algorithms developed in the book
Author : Gary Marcus
Publisher : Vintage
ISBN 13 : 1524748269
Total Pages : 288 pages
Book Rating : 4.5/5 (247 download)
Download or read book Rebooting AI written by Gary Marcus and published by Vintage. This book was released on 2019-09-10 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust—in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better.
Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 0309131820
Total Pages : 352 pages
Book Rating : 4.3/5 (91 download)
Download or read book Trust in Cyberspace written by National Research Council and published by National Academies Press. This book was released on 1999-02-08 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether or not you use a computer, you probably use a telephone, electric power, and a bank. Although you may not be aware of their presence, networked computer systems are increasingly becoming an integral part of your daily life. Yet, if such systems perform poorly or don't work at all, then they can put life, liberty, and property at tremendous risk. Is the trust that weâ€"as individuals and as a societyâ€"are placing in networked computer systems justified? And if it isn't, what can we do to make such systems more trustworthy? This book provides an assessment of the current state of the art procedures for building trustworthy networked information systems. It proposes directions for research in computer and network security, software technology, and system architecture. In addition, the book assesses current technical and market trends in order to better inform public policy as to where progress is likely and where incentives could help. Trust in Cyberspace offers insights into: The strengths and vulnerabilities of the telephone network and Internet, the two likely building blocks of any networked information system. The interplay between various dimensions of trustworthiness: environmental disruption, operator error, "buggy" software, and hostile attack. The implications for trustworthiness of anticipated developments in hardware and software technology, including the consequences of mobile code. The shifts in security technology and research resulting from replacing centralized mainframes with networks of computers. The heightened concern for integrity and availability where once only secrecy mattered. The way in which federal research funding levels and practices have affected the evolution and current state of the science and technology base in this area. You will want to read this book if your life is touched in any way by computers or telecommunications. But then, whose life isn't?
Author : Alexander Gammerman
Publisher : Springer
ISBN 13 : 331933395X
Total Pages : 229 pages
Book Rating : 4.3/5 (193 download)
Download or read book Conformal and Probabilistic Prediction with Applications written by Alexander Gammerman and published by Springer. This book was released on 2016-04-16 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Symposium on Conformal and Probabilistic Prediction with Applications, COPA 2016, held in Madrid, Spain, in April 2016. The 14 revised full papers presented together with 1 invited paper were carefully reviewed and selected from 23 submissions and cover topics on theory of conformal prediction; applications of conformal prediction; and machine learning.
Author : Clarence Chio
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491979852
Total Pages : 386 pages
Book Rating : 4.4/5 (919 download)
Download or read book Machine Learning and Security written by Clarence Chio and published by "O'Reilly Media, Inc.". This book was released on 2018-01-26 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself! With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions
