Data Science Ethics (Oxford University Press)
Friday, 15 July 2022

This book looks at data science ethics - all about what is right and wrong when conducting data science. David Martens looks at the ethical considerations that come from data science, and highlights different concepts and techniques that aid understanding, ranging from k-anonymity and differential privacy to homomorphic encryption and zero-knowledge proofs to address privacy concerns, techniques to remove discrimination against sensitive groups, and various explainable AI techniques.

<ASIN:0192847279>

Real-life cautionary tales further illustrate the importance and potential impact of data science ethics, including tales of racist bots, search censoring, government backdoors, and face recognition. The book is punctuated with structured exercises that provide hypothetical scenarios and ethical dilemmas for reflection that teach readers how to balance the ethical concerns and the utility of data.

Author: David Martens
Publisher: Oxford University Press
Date: June 2022
Pages: 272
ISBN: 978-0192847270
Print:0192847279
Audience: General
Level: Intermediate
Category: Data Science

dataethic

For recommendations of Big Data books see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

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Programming with Rust

Author:  Donis Marshall
Publisher: Addison-Wesley
Pages: 400
ISBN: 978-0137889655
Print: 0137889658
Kindle: B0CLL1TGVT
Audience: Programmers wanting to learn Rust
Rating: 3
Reviewer: Mike James
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Author: Andrew Glassner
Publisher: No Starch Press
Date: July 2021
Pages: 750
ISBN: 978-1718500723
Print: 1718500726
Kindle: ‎ B085BVWXNS
Audience: Developers interested in deep learning
Rating: Mike James
Reviewer: 5
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