97 Things About Ethics Everyone in Data Science Should Know: Collective Wisdom from the Experts

by Bill Franks

Most of the high-profile cases of real or perceived unethical activity in data science aren't matters of bad intent. Rather, they occur because the ethics simply aren't thought through well enough. Being ethical takes constant diligence, and in many situations identifying the right choice can be difficult. In this in-depth book, contributors from top companies in technology, finance, and other industries share experiences and lessons learned from collecting, managing, and analyzing data ethically. Data science professionals, managers, and tech leaders will gain a better understanding of ethics through powerful, real-world best practices. Articles

346 pages, Paperback

Published September 15, 2020

About the author

Bill Franks has spent his career focusing on analytics, data science, AI, and big data. He began his career in hands-on roles coding and building models, and then advanced to hold Chief Analytics Officer positions in both large, public company and small, private organization environments.

Franks is also the author of the books Taming The Big Data Tidal Wave, The Analytics Revolution, and 97 Things About Ethics Everyone In Data Science Should Know. He is a sought after speaker and frequent blogger who has been ranked in multiple global influencer lists tied to big data, analytics, and AI, and was an inaugural inductee into the Analytics Hall of Fame.

Bill's work has spanned clients in a variety of industries for companies ranging in size from Fortune 100 companies to small non-profit organizations.

You can learn more at http://www.bill-franks.com.

Reviews

[Eva Jascurova · Rating 1 out of 5]

This book is a collection of independent and somewhat repetitive answers/opinions on various aspects of data science. It my opinion, the book fails to summarise the issue and potential solutions in a way that would be practically applicable and useful and that would help practitioners to get a better understanding of its complexity. The book seemed very promising but it was difficult to finish it.

[Tiffanie changing to Storygraph - TifCochran · Rating 4 out of 5]

Great reading on ethics in data science. Read for my MSBA and decided to read all not just the selected readings.

[Yesi Days · Rating 3 out of 5]

Comparten experiencias e ideas desde la perspectiva de diversos autores, algunos temas me parecieron repetitivos.

[José Angel · Rating 2 out of 5]

It is nice to have a book that directly addresses the important topics on ethics and AI/Data Science/Machine Learning. Unfortunately, since it is a compilation of ~97 independent writers, it is quite repetitive and very hard (boring) to read from cover to cover. It is a nice book to have as a reference, but certainly, there could be a better synthesis on the issues as it feels right now that they just compiled a bunch of blogposts without any centralized editorial behind it that could allow for deeper reflections on these issues.