Abstract: A system and method detect bias and to perform debiasing of an item including data, ideas, and processes, by determining a fairness ratio, from model scores from a recommendation model, sorting the model scores into an ordered list of scores, determining that a sorted score is within a range of predetermined upper and lower thresholds, adjusting the sorted score, recomputing the fairness ratio from the adjusted sorted score, and in the case that the recomputed fairness ratio is not within the range, further adjusting the sorted score until a corresponding fairness ratio of the adjusted sorted score is within the range. In the case that the recomputed fairness ratio is within the range, the system and method generate and output a message with the adjusted sorted score to a recommendation engine, which generates and outputs a recommendation based on the adjusted sorted score.

Abstract: A system and method may identify the best matching entities using artificial intelligence, by for example determining, from a set of features describing a number of entities, a subset of features which when input to a machine learning module allow the machine learning module to match a pair of entities based on the ability of the second entity in the pair to successfully take over responsibilities handled by the first entity in the pair; training a machine learning module using the determined features; and for a first entity described by the determined set of features, using the machine learning module to determine a list of entities matching the first entity, each entity in the list of entities associated with a matching score.

Abstract: A system and method may identify the best matching entities using artificial intelligence, by for example determining, from a set of features describing a number of entities, a subset of features which when input to a machine learning module allow the machine learning module to match a pair of entities based on the ability of the second entity in the pair to successfully take over responsibilities handled by the first entity in the pair; training a machine learning module using the determined features; and for a first entity described by the determined set of features, using the machine learning module to determine a list of entities matching the first entity, each entity in the list of entities associated with a matching score.

Abstract: A system and method detect bias and to perform debiasing of an item including data, ideas, and processes, by determining a fairness ratio, from model scores from a recommendation model, sorting the model scores into an ordered list of scores, determining that a sorted score is within a range of predetermined upper and lower thresholds, adjusting the sorted score, recomputing the fairness ratio from the adjusted sorted score, and in the case that the recomputed fairness ratio is not within the range, further adjusting the sorted score until a corresponding fairness ratio of the adjusted sorted score is within the range. In the case that the recomputed fairness ratio is within the range, the system and method generate and output a message with the adjusted sorted score to a recommendation engine, which generates and outputs a recommendation based on the adjusted sorted score.