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This document discusses developing an ethical framework for machine learning. It proposes combining intellectual quotient with emotional and spiritual quotients when designing machine learning algorithms. This would create four types of algorithms: mechanical learner, cognitive learner, ethical learner, and ethical master. The framework is aimed at minimizing bias in algorithms and making ethical future decisions. It provides implementation strategies at the national, organizational, and design levels, and suggests collaborations, guidelines, and monitoring to help ensure quality of values in machine learning.