Artificial intelligence (AI) has become a part of our everyday lives from healthcare to law enforcement. AI-related ethical challenges have grown apace ranging from algorithmic bias and data privacy to transparency and accountability. As a direct reaction to these growing ethical concerns, organizations have been publishing their AI principles for ethical practice (over 100 sets and increasing). However, the multiplication of these mostly vaguely formulated principles has not proven to be helpful in guiding practice. Only by operationalizing AI principles for ethical practice can we help computer scientists, developers, and designers to spot and think through ethical issues and recognize when a complex ethical issue requires in-depth expert analysis.