Human Centered Ai

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.

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.

Artificial intelligence (AI) permeates our lives in a growing number of ways. Relying solely on traditional, technology-driven approaches won't suffice to develop and deploy that technology in a way that truly enhances human experience. A new concept is desperately needed to reach that goal. That concept is Human-Centered AI (HCAI). With 29 captivating chapters, this book delves deep into the realm of HCAI. In Section I, it demystifies HCAI, exploring cutting-edge trends and approaches in its study, including the moral landscape of Large Language Models. Section II looks at how HCAI is viewed in different institutions—like the justice system, health system, and higher education—and how it could affect them. It examines how crafting HCAI could lead to better work. Section III offers practical insights and successful strategies to transform HCAI from theory to reality, for example, studying how using regulatory sandboxes could ensure the development of age-appropriate AI for kids. Finally, decision-makers and practitioners provide invaluable perspectives throughout the book, showcasing the real-world significance of its articles beyond academia. Authored by experts from a variety of backgrounds, sectors, disciplines, and countries, this engaging book offers a fascinating exploration of Human-Centered AI. Whether you're new to the subject or not, a decision-maker, a practitioner or simply an AI user, this book will help you gain a better understanding of HCAI's impact on our societies, and of why and how AI should really be developed and deployed in a human-centered future.

Human-Centered Artificial Intelligence: Research and Applications presents current theories, fundamentals, techniques and diverse applications of human-centered AI. Sections address the question, "are AI models explainable, interpretable and understandable?, introduce readers to the design and development process, including mind perception and human interfaces, explore various applications of human-centered AI, including human-robot interaction, healthcare and decision-making, and more. As human-centered AI aims to push the boundaries of previously limited AI solutions to bridge the gap between machine and human, this book is an ideal update on the latest advances. Presents extensive research on human-centered AI technology Provides different methods and techniques used to investigate human-AI interaction Discusses open questions and challenges in trust within human-centered AI Explores how human-centered AI changes and operates in human-machine interactions

Research can face artificial intelligence (AI) as an issue of technology development but also as an issue of enacted technology at work. Human-centered design of AI gives emphasis to the expertise and needs of human beings as a starting point of technology development or as an outcome of AI-based work settings. This is an important goal, as expressed, for example, by the international labor organization's call for a "human-centered agenda" for the future of AI and automation collaboration. This Research Topic raises the question of what human-centricity means, i.e. what are the criteria and indicators of human-centered AI and how can they be considered and implemented?

The 18th European Advanced Course on AI (ACAI) took place in Berlin on 11-15 October 2021, organized by the European project Humane-AI Net in collaboration with the European AI Association (EURAI). The school included tutorials on different topics, which were selected through an open call to top European AI researchers. In addition, the school also included 4 invited talks, a student poster presentation, and a mentorship program. This volume contains 21 tutorial chapters organized according to the following themes: human-centered AI; human-centered machine learning; explainable AI; ethics, law, and the societal aspects of AI; argumentation; and social simulation. The contributions include learning objectives, reading lists, and links to further resources.

The integration of artificial intelligence (AI) stands as both a promise and a challenge in the field of healthcare. As technological advancements reshape the industry, academic scholars find themselves at the forefront of a crucial dialogue about the ethical implications and societal repercussions of AI. The accelerating sophistication of AI technologies brings forth a central dilemma: how to maintain the crucial human touch required for compassionate and effective patient care in the face of unprecedented technical progress. This challenge is not only a theoretical concern but a pressing reality as healthcare systems increasingly rely on AI-driven solutions. Approaches to Human-Centered AI in Healthcare emerges as a significant guide, offering a comprehensive exploration of the opportunities and challenges entwined with the integration of AI into healthcare. The book becomes a critical compass, navigating readers through the intricate intersections of AI and patient care. By delving into real-world case studies, cutting-edge research findings, and practical recommendations, it provides a roadmap for scholars to navigate the complexities of healthcare AI. In doing so, it aims not only to inform but to shape the discourse around the responsible integration of AI, ensuring that the fundamental principles of compassionate patient care remain at the forefront.