Chen Fang, Zhou Jianlong (eds.) Humanity Driven AI: Productivity, Well-being, Sustainability and Partnership

Springer, 2022. — 806 p. — ISBN: 978-3-030-72188-6.Artificial Intelligence (AI) is changing the world around us, and it is changing the way people are living, working, and entertaining. As a result, demands for understanding how AI functions to achieve and enhance human goals from basic needs to high-level well-being (whilst maintaining human health) are increasing. This edited book systematically investigates how AI facilitates enhancing human needs in the digital age, and reports on the state-of-the-art advances in theories, techniques, and applications of humanity-driven AI. Consisting of five parts, it covers the fundamentals of AI and humanity, AI for productivity, AI for well-being, AI for sustainability, and human-AI partnership. Humanity Driven AI creates an important opportunity to not only promote AI techniques from a human perspective but also to invent novel AI applications to benefit humanity. It aims to serve as the dedicated source for the theories, methodologies, and applications of humanity-driven AI, establishing state-of-the-art research, and providing a ground-breaking book for graduate students, research professionals, and AI practitioners.AI and Humanity
Towards Humanity-in-the-Loop in AI Lifecycle
AI and Ethics — Operationalizing​ Responsible AI
AI for Productivity
Machine Learning for Efficient Water Infrastructure Management
AI for Real-Time Bus Travel Time Prediction in Traffic Congestion Management
The Future of Transportation:​ How to Improve Railway Operation Performance via Advanced AI Techniques
AI for Well-being
Federated Learning for Privacy-Preserving Open Innovation Future on Digital Health
AI-Enhanced 3D Biomedical Data Analytics for Neuronal Structure Reconstruction
Artificial Intelligence for Fighting the COVID-19 Pandemic
AI for Sustainability
Sewer Corrosion Prediction for Sewer Network Sustainability
AI Applied to Air Pollution and Environmental Health:​ A Case Study on Hypothesis Generation
SharkSpotter:​ Shark Detection with Drones for Human Safety and Environmental Protection
AI + Human Partnership
Learner Engagement Examination Via Computer Usage Behaviors
Virtual Teaching Assistants:​ Technologies, Applications, and Challenges
Artificial Intelligence and People with Disabilities:​ a Reflection on Human–AI Partnerships
Towards a Taxonomy for Explainable AI in Computational Pathology