level of performance. We next investigated this puzzling result using 31 interviews with 14 employees—2 algorithm developers … algorithm, because of their belief that they understand the inner workings of complex processes better than they actually do …. Second, social proofing the algorithm—including respected peers in the algorithm development and testing process—may make it …

vague information and are defuzzified using a novel algorithm called converting trapezoidal intuitionistic fuzzy numbers …

develop a ML algorithm and compare its performance with that of medical experts in the task of predicting 30-day readmissions … after solid-organ transplantation. We find that our algorithm is not only more accurate in predicting clinical risk but can … also positively influence human judgment. However, its potential impact is mediated by the users’ degree of algorithm …

resort to their use. In an economic experiment, we examine whether the extent of this phenomenon known as algorithm aversion … can be reduced by granting decision-makers the possibility to exert an influence on the configuration of the algorithm (an … algorithm aversion recedes significantly if the subjects can subsequently change the results of the algorithm-and even if this …

an efficient Monte Carlo algorithm based on an implicit hierarchical structure of permutations of players. Our algorithm … outputs a vector of power indices preserving the monotonicity, with respect to the voting weights. We show that our algorithm … reduces the required number of samples, compared with the naive algorithm. …