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 WilsonHow to Approach Ethical Transparency—Rado KotorovUnbiased ≠ Fair—Doug HagueRules and Rationality—Christof Wolf BrennerThe Truth About AI Bias—Cassie KozyrkovCautionary Ethics Tales—Sherrill HayesFairness in the Age of Algorithms—Anna JacobsonThe Ethical Data Storyteller—Brent DykesIntroducing Ethicize™, the Fully AI-Driven Cloud-Based Ethics Solution!—Brian O’NeillBe Careful with "Decisions of the Heart"—Hugh WatsonUnderstanding Passive Versus Proactive Ethics—Bill Schmarzo
