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: Jim Wilson
- How to Approach Ethical Transparency: Rado Kotorov
- Unbiased & Fair: Doug Hague
- Rules and Rational:: Christof Wolf Brenner
- The Truth About AI: Cassie Kozyrkov
- Cautionary Ethics Tales: Sherrill Hayes
- Fairness in the Age of Algorithms: Anna Jacobson
- The Ethical Data Storyteller: Brent Dykes
- Introducing Ethics: 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