Human Centered Ai Crowd Computing

Many data-intensive applications that use machine learning or artificial intelligence techniques depend on humans providing the initial dataset, enabling algorithms to process the rest or for other humans to evaluate the performance of such algorithms. Not only can labeled data for training and evaluation be collected faster, cheaper, and easier than ever before, but we now see the emergence of hybrid human-machine software that combines computations performed by humans and machines in conjunction. There are, however, real-world practical issues with the adoption of human computation and crowdsourcing. Building systems and data processing pipelines that require crowd computing remains difficult. In this book, we present practical considerations for designing and implementing tasks that require the use of humans and machines in combination with the goal of producing high-quality labels.

Embark on a captivating exploration of human-centered computing and AI, where the convergence of technology and human interaction unveils a world of endless possibilities. In the age of wireless communication, pervasive computing, and the Internet of Things, the synergy between humans and machines has never been more profound. This book delves deep into the heart of this symbiotic relationship, shedding light on the intricate dynamics that define our digital landscape. From the humble human-computer communications, via simple interaction points, to the complex web of virtual networks, every aspect of this journey is meticulously examined. Through a lens of innovation and insight, we navigate within the complex terrain of user actions, individual differences, and algorithmic computations. At the core of our exploration lies a quest for understanding—a quest that transcends the boundaries of traditional research and ventures into the realm of cutting-edge technology. Special emphasis is placed on promoting original insights and paradigms, incorporating aspects derived from psychological theory and individual differences in adaptive computational systems and recommenders. Our goal is simple yet ambitious: by enhancing explainability, fairness, transparency, and decreasing bias during interactions, to empower users with greater control and understanding of the technologies that shape their lives. Through a blend of visual storytelling and specialized textual contributions, we invite you to join us on this extraordinary journey. Whether you're a researcher, practitioner, or enthusiast in the field of AI and human-computer interaction, this book offers valuable insights and perspectives. Prepare to be inspired, enlightened, and empowered through this transformative journey as we unlock the true potential of technology in service of humanity.

The rise of the Internet of Things (IoT) and Artificial Intelligence (AI) leads to the emergence of edge computing systems that push the training and deployment of AI models to the edge of networks for reduced bandwidth cost, improved responsiveness, and better privacy protection, allowing for the ubiquitous AI that can happen anywhere and anytime. Motivated by the above trend, this book introduces a new computing paradigm, the Social Edge Computing (SEC), that empowers human-centric edge intelligent applications by revolutionizing the computing, intelligence, and the training of the AI models at the edge. The SEC paradigm introduces a set of critical human-centric challenges such as the rational nature of edge device owners, pronounced heterogeneity of the edge devices, real-time AI at the edge, human and AI interaction, and the privacy of the edge users. The book addresses these challenges by presenting a series of principled models and systems that enable the confluence of the computing capabilities of devices and the domain knowledge of the people, while explicitly addressing the unique concerns and constraints from humans. Compared to existing books in the field of edge computing, the vision of this book is unique: we focus on the social edge computing (SEC), an emerging paradigm at the intersection of edge computing, AI, and social computing. This book discusses the unique vision, challenges and applications in SEC. To our knowledge, keeping humans in the loop of edge intelligence has not been systematically reviewed and studied in an existing book. The SEC vision generalizes the current machine-to-machine interactions in edge computing (e.g., mobile edge computing literature), and machine-to-AI interactions (e.g., edge intelligence literature) into a holistic human-machine-AI ecosystem.

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.

This book covers user experience methods and tools in designing user‐friendly products and servicesby encompassing widely utilized successful methods, including elicitation, analysis and establishment of requirements, collaborative idea generation with design teams and intended users, prototype testing and evaluation of the user experience through empirical and non‐empirical means. This book • Provides methods and tools tailored for each stage of the design process. • Discusses methods for the active involvement of users in the human‐centered design process. • Equips readers with an effective toolset for use throughout the design process, ensuring that what is created aligns with user needs and desires. • Covers a wide array of research and evaluation methods employed in HCI, from the initiation of the human‐centered development cycle to its culmination. This book is a fascinating read for individuals interested in Human-Computer Interaction research and applications.

Hybrid Human-Machine Information Systems leverage novel architectures that make systematic use of Human Computation by means of crowdsourcing. These architectures are capable of scaling over large amounts of data and simultaneously maintain high-quality data processing levels by introducing humans into the loop. Such hybrid systems have been developed to tackle a variety of problems and come with inter-disciplinary challenges. They need to deal with the full spectrum of challenges from the social science standpoint, such as understanding crowd workers behavior and motivations when performing tasks. These systems also need to overcome highly technical challenges like constraint optimization and resource allocation based on limited budgets and deadlines to be met. In this paper, we introduce the area of Human Computation and present an overview of different applications for which Hybrid Human- Machine Information Systems have already been used in the realms of data management, information retrieval, natural language processing, semantic web, machine learning, and multimedia to better solve existing problems. Finally, we discuss current research directions, opportunities for the future development of such systems and their application in practice.

These 2 volumes constitute the selected papers of the 7th International Conference, CHIRA 2023, held Rome, Italy, during November 16–17, 2023. The 14 full papers and the 29 short papers presented in these books were carefully reviewed and selected from 69 submissions. The papers selected contribute to the advancement of research and practical applications of human-technology and human-computer interaction. Different aspects of Computer-Human Interaction were covered in four parallel tracks: human factors for interactive systems, research, and applications; interactive devices; interaction design; and adaptive and intelligent systems.

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

Medical Decision Making provides clinicians with a powerful framework for helping patients make decisions that increase the likelihood that they will have the outcomes that are most consistent with their preferences. This new edition provides a thorough understanding of the key decision making infrastructure of clinical practice and explains the principles of medical decision making both for individual patients and the wider health care arena. It shows how to make the best clinical decisions based on the available evidence and how to use clinical guidelines and decision support systems in electronic medical records to shape practice guidelines and policies. Medical Decision Making is a valuable resource for all experienced and learning clinicians who wish to fully understand and apply decision modelling, enhance their practice and improve patient outcomes. “There is little doubt that in the future many clinical analyses will be based on the methods described in Medical Decision Making, and the book provides a basis for a critical appraisal of such policies.” - Jerome P. Kassirer M.D., Distinguished Professor, Tufts University School of Medicine, US and Visiting Professor, Stanford Medical School, US