Algorithms Humans And Interactions
Download Algorithms Humans And Interactions full books in PDF, epub, and Kindle. Read online free Algorithms Humans And Interactions ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
| Author | : Don Donghee Shin |
| Publisher | : Taylor & Francis |
| Total Pages | : 177 |
| Release | : 2023-01-31 |
| Genre | : Computers |
| ISBN | : 1000825388 |
Amidst the rampant use of algorithmization enabled by AI, the common theme of AI systems is the human factor. Humans play an essential role in designing, developing, and operationalizing AI systems. We have a remit to ensure those systems run transparently, perform equitably, value our privacy, and effectively fulfill human needs. This book takes an interdisciplinary approach to contribute to the ongoing development of human–AI interaction with a particular focus on the "human" dimension and provides insights to improve the design of AI that could be genuinely beneficial and effectively used in society. The readers of this book will benefit by gaining insights into various perspectives about how AI has impacted people and society and how it will do so in the future, and understanding how we can design algorithm systems that are beneficial, legitimate, usable by humans, and designed considering and respecting human values. This book provides a horizontal set of guidelines and insight into how humans can be empowered by making choices about AI designs that allow them meaningful control over AI. Designing meaningful AI experiences has garnered great attention to address responsibility gaps and mitigate them by establishing conditions that enable the proper attribution of responsibility to humans. This book helps us understand the possibilities of what AI systems can do and how they can and should be integrated into our society.
| Author | : Flynn Coleman |
| Publisher | : Catapult |
| Total Pages | : 337 |
| Release | : 2020-10-20 |
| Genre | : Computers |
| ISBN | : 1640094288 |
A groundbreaking narrative on the urgency of ethically designed AI and a guidebook to reimagining life in the era of intelligent technology. The Age of Intelligent Machines is upon us, and we are at a reflection point. The proliferation of fast–moving technologies, including forms of artificial intelligence akin to a new species, will cause us to confront profound questions about ourselves. The era of human intellectual superiority is ending, and we need to plan for this monumental shift. A Human Algorithm: How Artificial Intelligence Is Redefining Who We Are examines the immense impact intelligent technology will have on humanity. These machines, while challenging our personal beliefs and our socioeconomic world order, also have the potential to transform our health and well–being, alleviate poverty and suffering, and reveal the mysteries of intelligence and consciousness. International human rights attorney Flynn Coleman deftly argues that it is critical that we instill values, ethics, and morals into our robots, algorithms, and other forms of AI. Equally important, we need to develop and implement laws, policies, and oversight mechanisms to protect us from tech’s insidious threats. To realize AI’s transcendent potential, Coleman advocates for inviting a diverse group of voices to participate in designing our intelligent machines and using our moral imagination to ensure that human rights, empathy, and equity are core principles of emerging technologies. Ultimately, A Human Algorithm is a clarion call for building a more humane future and moving conscientiously into a new frontier of our own design. “[Coleman] argues that the algorithms of machine learning––if they are instilled with human ethics and values––could bring about a new era of enlightenment.” —San Francisco Chronicle
| Author | : Mamta Mittal |
| Publisher | : Academic Press |
| Total Pages | : 420 |
| Release | : 2021-08-13 |
| Genre | : Computers |
| ISBN | : 0323856470 |
Cognitive Computing for Human-Robot Interaction: Principles and Practices explores the efforts that should ultimately enable society to take advantage of the often-heralded potential of robots to provide economical and sustainable computing applications. This book discusses each of these applications, presents working implementations, and combines coherent and original deliberative architecture for human–robot interactions (HRI). Supported by experimental results, it shows how explicit knowledge management promises to be instrumental in building richer and more natural HRI, by pushing for pervasive, human-level semantics within the robot's deliberative system for sustainable computing applications. This book will be of special interest to academics, postgraduate students, and researchers working in the area of artificial intelligence and machine learning. Key features: - Introduces several new contributions to the representation and management of humans in autonomous robotic systems; - Explores the potential of cognitive computing, robots, and HRI to generate a deeper understanding and to provide a better contribution from robots to society; - Engages with the potential repercussions of cognitive computing and HRI in the real world. - Introduces several new contributions to the representation and management of humans in an autonomous robotic system - Explores cognitive computing, robots and HRI, presenting a more in-depth understanding to make robots better for society - Gives a challenging approach to those several repercussions of cognitive computing and HRI in the actual global scenario
| Author | : Ben Shneiderman |
| Publisher | : Oxford University Press |
| Total Pages | : 390 |
| Release | : 2022 |
| Genre | : Computers |
| ISBN | : 0192845292 |
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 | : National Research Council |
| Publisher | : National Academies Press |
| Total Pages | : 191 |
| Release | : 2013-09-03 |
| Genre | : Mathematics |
| ISBN | : 0309287812 |
Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
| Author | : Sandeep Kumar |
| Publisher | : John Wiley & Sons |
| Total Pages | : 400 |
| Release | : 2021-11-23 |
| Genre | : Computers |
| ISBN | : 1119792088 |
COGNITIVE BEHAVIOR AND HUMAN COMPUTER INTERACTION BASED ON MACHINE LEARNING ALGORITHMS The objective of this book is to provide the most relevant information on Human-Computer Interaction to academics, researchers, and students and for those from industry who wish to know more about the real-time application of user interface design. Human-computer interaction (HCI) is the academic discipline, which most of us think of as UI design, that focuses on how human beings and computers interact at ever-increasing levels of both complexity and simplicity. Because of the importance of the subject, this book aims to provide more relevant information that will be useful to students, academics, and researchers in the industry who wish to know more about its real-time application. In addition to providing content on theory, cognition, design, evaluation, and user diversity, this book also explains the underlying causes of the cognitive, social and organizational problems typically devoted to descriptions of rehabilitation methods for specific cognitive processes. Also described are the new modeling algorithms accessible to cognitive scientists from a variety of different areas. This book is inherently interdisciplinary and contains original research in computing, engineering, artificial intelligence, psychology, linguistics, and social and system organization as applied to the design, implementation, application, analysis, and evaluation of interactive systems. Since machine learning research has already been carried out for a decade in various applications, the new learning approach is mainly used in machine learning-based cognitive applications. Since this will direct the future research of scientists and researchers working in neuroscience, neuroimaging, machine learning-based brain mapping, and modeling, etc., this book highlights the framework of a novel robust method for advanced cross-industry HCI technologies. These implementation strategies and future research directions will meet the design and application requirements of several modern and real-time applications for a long time to come. Audience: A wide range of researchers, industry practitioners, and students will be interested in this book including those in artificial intelligence, machine learning, cognition, computer programming and engineering, as well as social sciences such as psychology and linguistics.
| Author | : Robert Munro |
| Publisher | : Simon and Schuster |
| Total Pages | : 422 |
| Release | : 2021-07-20 |
| Genre | : Computers |
| ISBN | : 1617296740 |
Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-loop machine learning lays out methods for humans and machines to work together effectively. You'll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You'll learn to dreate training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows.
| Author | : Kartik Hosanagar |
| Publisher | : Viking Adult |
| Total Pages | : 274 |
| Release | : 2019 |
| Genre | : Business & Economics |
| ISBN | : 0525560882 |
In his new book, Kartik Hosanagar surveys the brave new world of algorithmic decision-making and reveals the potentially dangerous biases they can give rise to as they increasingly run our lives.
| Author | : Michael Kearns |
| Publisher | : |
| Total Pages | : 229 |
| Release | : 2020 |
| Genre | : Business & Economics |
| ISBN | : 0190948205 |
Algorithms have made our lives more efficient and entertaining--but not without a significant cost. Can we design a better future, one in which societial gains brought about by technology are balanced with the rights of citizens? The Ethical Algorithm offers a set of principled solutions based on the emerging and exciting science of socially aware algorithm design.
| Author | : Surbhi Bhatia Khan |
| Publisher | : Elsevier |
| Total Pages | : 342 |
| Release | : 2023-07-22 |
| Genre | : Computers |
| ISBN | : 0323999492 |
Innovations in Artificial Intelligence and Human Computer Interaction in the Digital Era investigates the interaction and growing interdependency of the HCI and AI fields, which are not usually addressed in traditional approaches. Chapters explore how well AI can interact with users based on linguistics and user-centered design processes, especially with the advances of AI and the hype around many applications. Other sections investigate how HCI and AI can mutually benefit from a closer association and the how the AI community can improve their usage of HCI methods like "Wizard of Oz prototyping and "Thinking aloud protocols. Moreover, HCI can further augment human capabilities using new technologies. This book demonstrates how an interdisciplinary team of HCI and AI researchers can develop extraordinary applications, such as improved education systems, smart homes, smart healthcare and map Human Computer Interaction (HCI) for a multidisciplinary field that focuses on the design of computer technology and the interaction between users and computers in different domains. - Presents fundamental concepts of both HCI and AI, addressing a multidisciplinary audience of researchers and engineers working on User Centered Design (UCD), User Interface (UI) design, and User Experience (UX) design - Explores a broad range of case studies from across healthcare, industry, and education - Investigates multiple strategies for designing and developing intelligent user interfaces to solve real-world problems - Outlines research challenges and future directions for the intersection of AI and HCI
