Data Science Ethics

Description

This book examines a variety of different concepts related to data science ethics and techniques that can help with, or lead to, ethical concerns, whilst featuring cautionary tales that illustrate the importance and potential impact of data science ethics.

• Provides training and guidance in understanding ethical considerations, concepts, and techniques, for data scientists and professionals at data-driven companies
• Discusses real-life cautionary tales to illustrate the dangers of neglecting or misapplying data science ethics
• Features structured exercises that provide hypothetical scenarios and ethical dilemmas useful for teaching and reflection, showing readers how to balance ethical concerns and data utility

About the Author(s)

David Martens, Professor of Data Science, University of Antwerp, Belgium

David Martens is Professor of Data Science at the Department of Engineering Management, University of Antwerp, Belgium. He teaches data mining and data science and ethics to postgraduate students studying business economics and business engineering. In his work, David has collaborated with large banks, insurance companies and telco companies, as well as with various technology startups. His research has been published in high-impact journals and has received several awards.

Table of Contents

Foreword, Foster Provost
Preface
1:Introduction to Data Science Ethics
2:Ethical Data Gathering
3:Ethical Data Preprocessing
4:Ethical Modelling
5:Ethical Evaluation
6:Ethical Deployment
7:Conclusion

Reviews

"An excellent reading with both depth and breadth on some of the most important challenges and risks data scientists, businesses, governments and societies face today as Artificial Intelligence adoption grows. These are topics everyone needs to be aware of, and this is one of the very few must read books on these issues " - Theodoros Evgeniou, Professor of Decision Sciences and Technology Management at INSEAD, France

"This is an important and timely book for data scientists, written in a clear and engaging way. Motivated by many relevant examples, the author successfully de-mystifies data ethics lingo and presents a comprehensive view of ethical considerations during the entire data science lifecycle. " - Galit Shmueli, Tsing Hua Distinguished Professor, Institute of Service Science and Institute Director, College of Technology Management, National Tsing Hua University, Taiwan