Concepts and techniques surrounding data science ethics are the central theme of this study book, written by David Martens. It is intended for professionals and students who want to gain insight into ethical issues within data science. The book covers both theoretical and practical aspects, with attention to privacy, discrimination, and the explainability of models.
Contents
This reference work discusses the core concepts of data science ethics and how different techniques can be used to prevent or reduce ethical problems. Think of k-anonymity, differential privacy, homomorphic encryption, and zero-knowledge proofs for privacy protection. In addition, methods are covered to counter discrimination against sensitive groups and various explainable AI techniques that improve transparency.
Various cautionary tales illustrate the possible negative effects of data science, such as racist bots, censorship in search engines, government backdoors, and facial recognition. Through structured exercises, the reader learns to weigh ethical dilemmas against practical applications.
Product information
- Author: David Martens (Professor of Data Science, University of Antwerp)
- Publisher: Oxford University Press
- Publication date: 24 March 2022
- Number of pages: 272
- ISBN: 9780192847270
- Theme: Digital and information technologies: social and ethical aspects
- BISAC: COMPUTERS / Artificial Intelligence / General