Science And The Social Good

This book is a collection of reflections by thought leaders at first-mover organizations in the exploding field of "Data Science for Social Good", meant as the application of knowledge from computer science, complex systems and computational social science to challenges such as humanitarian response, public health, sustainable development. The book provides both an overview of scientific approaches to social impact – identifying a social need, targeting an intervention, measuring impact – and the complementary perspective of funders and philanthropies that are pushing forward this new sector. This book will appeal to students and researchers in the rapidly growing field of data science for social impact, to data scientists at companies whose data could be used to generate more public value, and to decision makers at nonprofits, foundations, and agencies that are designing their own agenda around data.

Using biographies of three natural scientists--geologist Clarence King, forester Robert Marshall, and biologist Rachel Carson--Science and the Social Good investigates the links between nature's scientific study and social improvement.

There’s no denying that CI is on its way to change the world as we know it. There are various social domains such as Environment, Education, Information Security, Healthcare, Crisis Response, Human Behavior and Bias, Disaster Management, Industrial management and most recently Epidemics and Outbreaks are highly in need of Intelligent Technologies to address their issues. This book presents the views on how Computational Intelligent and ICT technologies can be applied to ease or solve social problems by sharing examples of research results from studies of social anxiety, environmental issues, mobility of the disabled, and problems in social safety. As with most changes in life, there will be positive and negative impacts on society as artificial intelligence continues to transform the world, we live in. With the idea of future scope in research, the book focuses on the challenges that might be faced (and we should be thinking about how to address them now) as well as several of the positive impacts artificial intelligence will have on society. Explores a number of key themes, including self-organization, complex adaptive systems, and emergent computation for solving socially relevant problems Focuses on Forecasting applications, Human Behavior and Critics response analysis in social forums, Healthcare monitoring Systems, Disaster Management, Industrial management, and most recently, Epidemics and Outbreaks Brings together many different aspects of the current research on intelligence technologies, such as neural networks, support vector machines, fuzzy logic, and evolutionary computation

Bernard Gert's classic work Morality, in which he argues his distinctive and comprehensive moral theory, is now in its sixth edition. Gert argues that morality is an informal system that does not provide answers to every moral question but does always limit the range of morally acceptable options and so explains why some moral questions cannot be resolved. Gert describes the two-step procedure that is used in moral decisions and judgments, and he shows that moral rules cannot be understood independently of the system in which they are embedded. Although his moral theory is sophisticated, it is presented with a clarity that will appeal to undergraduate and graduate students alike, as well as anyone with a general interest in applied ethics. In this new edition, Gert perfects the consistency of his views by presenting his argument in greater detail; he also revises the text in light of a critical book and two symposia dedicated to his theory that have surfaced since the book's last publication. This is the definitive edition to the work that has received so much attention and acclaim.

This book is a collection of reflections by thought leaders at first-mover organizations in the exploding field of "Data Science for Social Good", meant as the application of knowledge from computer science, complex systems and computational social science to challenges such as humanitarian response, public health, sustainable development. The book provides both an overview of scientific approaches to social impact - identifying a social need, targeting an intervention, measuring impact - and the complementary perspective of funders and philanthropies that are pushing forward this new sector. This book will appeal to students and researchers in the rapidly growing field of data science for social impact, to data scientists at companies whose data could be used to generate more public value, and to decision makers at nonprofits, foundations, and agencies that are designing their own agenda around data.

This open access book provides practical guidance for non-profits and community sector organisations about how to get started with data analytics projects using their own organisations’ datasets and open public data. The book shares best practices on collaborative social data projects and methodology. For researchers, the work offers a playbook for partnering with community organisations in data projects for public good and gives worked examples of projects of various sizes and complexity.

This book constitutes the refereed post-conference proceedings of the 7th EAI International Conference on Smart Objects and Technologies for social Good, GOODTECHS 2021, held in September 2021. Due to COVID-19 pandemic the conference was held virtually. The 24 full papers presented were selected from 53 submissions and issue design, implementation, deployment, operation, and evaluation of smart objects and technologies for social good. Social goods are products and services provided through private enterprises, government, or non-profit institutions and are related to healthcare, safety, sports, environment, democracy, computer science, and human rights. The papers are arranged in tracks on machine learning; IoT; social considerations of technology; technology and ageing; healthcare.