Most of the high-profile cases of real or perceived unethical activity in data science arenĂ¢??t matters of bad intent. Rather, they occur because the ethics simply arenĂ¢??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 ConceptĂ¢??Tim Wilson
- How to Approach Ethical TransparencyĂ¢??Rado Kotorov
- Unbiased ≠FairĂ¢??Doug Hague
- Rules and RationalityĂ¢??Christof Wolf Brenner
- The Truth About AI BiasĂ¢??Cassie Kozyrkov
- Cautionary Ethics TalesĂ¢??Sherrill Hayes
- Fairness in the Age of AlgorithmsĂ¢??Anna Jacobson
- The Ethical Data StorytellerĂ¢??Brent Dykes
- Introducing EthicizeĂ¢?¢, the Fully AI-Driven Cloud-Based Ethics Solution!Ă¢??Brian OĂ¢??Neill
- Be Careful with "Decisions of the Heart"Ă¢??Hugh Watson
- Understanding Passive Versus Proactive EthicsĂ¢??Bill Schmarzo
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