97 Things about Ethics Everyone in Data Science Should Know

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.

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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 include:

Ethics Is Not a Binary Concept—Tim Wilson
How to Approach Ethical Transparency—Rado Kotorov
Unbiased ≠ Fair—Doug Hague
Rules and Rationality—Christof Wolf Brenner
The Truth About AI Bias—Cassie Kozyrkov
Cautionary Ethics Tales—Sherrill Hayes
Fairness in the Age of Algorithms—Anna Jacobson
The Ethical Data Storyteller—Brent Dykes
Introducing Ethicize™, the Fully AI-Driven Cloud-Based Ethics Solution!—Brian O’Neill
Be Careful with "Decisions of the Heart"—Hugh Watson
Understanding Passive Versus Proactive Ethics—Bill Schmarzo