Humanity Driven AI: Productivity, Well-being, Sustainability and Partnership

by Fang Chen (Editor), Jianlong Zhou (Editor)

Overview

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 humanity 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 on humanity drivenAI, establishing state-of-the-art research, and providing a ground-breaking book for graduate students, research professionals, and AI practitioners.

Product Details

ISBN-13:	9783030721886
Publisher:	Springer-Verlag New York, LLC
Publication date:	12/01/2021
Sold by:	Barnes & Noble
Format:	eBook
File size:	53 MB
Note:	This product may take a few minutes to download.

About the Author

Dr Chen is a prominent leader in data science with an international reputation and industrial recognitions. She has created many innovative research and solutions, transforming industries that utilise data science.​Dr Chen and her team  won the 2018 Australian leading science prize Australian Museum Eureka Prize for Excellence in Data Science. 
Dr. Zhou is a leading senior researcher in trustworthy and transparent machine learning, and has done pioneering research in the area of linking human and machine learning. He also works with industries in advanced data analytics for transforming data into actionable operations particularly by incorporating human user aspects into machine learning and translate machine learning into impacts in real world applications.

Table of Contents

Part I AI and Humanity .- Towards Humanity-in-The-Loop in AI Lifecycle.- AI and Ethics - Operationalising Responsible AI.- Part II 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.- Part III AI for Wellbeing.- 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.- Part IV 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.