Most of the high-profile cases of real or perceived unethical activity
in data science arenâ t matters of bad intent. Rather, they occur
because the ethics simply arenâ 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 Conceptâ Tim Wilson
- How to Approach Ethical Transparencyâ Rado Kotorov
- Unbiased Fairâ Doug Hague
- Rules and Rationalityâ Christof Wolf Brenner
- The Truth About AI Biasâ Cassie Kozyrkov
- Cautionary Ethics Talesâ Sherrill Hayes
- Fairness in the Age of Algorithmsâ Anna Jacobson
- The Ethical Data Storytellerâ Brent Dykes
- Introducing Ethicizeâ?[, the Fully AI-Driven Cloud-Based Ethics
Solution!â Brian Oâ Neill
- Be Careful with "Decisions of the Heart"â Hugh Watson
- Understanding Passive Versus Proactive Ethicsâ Bill Schmarzo