The prolific deployment of Artificial Intelligence (AI) across different applications has introduced novel challenges for AI developers and researchers. AI is permeating decision making for the masses, from self-driving automobiles to financial loan approvals.  With AI making decisions that have ethical implications, responsibilities are now being pushed to AI designers who may be far-removed from how, where, and when the ethical decisions occur. Ethical Computing for Engineers, Operators, and AI Designers: Key Performance Parameters for Ethical Artificial Intelligence provides audiences with a catalogue of methodologies and perspectives from the most current research in ethical computing, integrating philosophical frameworks and computational approaches to ethical reasoning in the current artificial intelligence landscape, with a specific focus on approaches for developing metrics. Written for AI researchers, ethicists, computer scientists, software engineers, operations researchers, and autonomous systems designers and developers, this will be a welcome reference for those who wish to better understand metrics and measurements related to ethical reasoning in autonomous systems and related computational aspects.