Cognitive Tools of Explanatory Artificial Intelligence for Problems of Transport and Educational Logisticsадач транспортной и образовательной логистики

Abstract

In anticipation of the transition to digital logistics systems, there is an exponential growth in the use of artificial intelligence systems. This growth is most noticeable in the area of logistics process analysis. However, with the complication of algorithms, the user’s ability to control decision-making in logistics is significantly reduced, which affects the credibility of the result, which is critical in logistics. The use of explanatory artificial intelligence methods is called upon to increase transparency in the operation of artificial intelligence (AI) systems in the analysis of logistical phenomena. Our study presents one of the cognitive tools in the spectrum of explanatory artificial intelligence methods for analyzing logistics processes, and also considers potentially promising approaches to improving this technology. However, despite the fact that artificial intelligence technologies have great potential, the complication of these systems affects the credibility of the technology. This is especially noticeable in areas where technosphere and logistical security depends on the correctness of the decision. The way out of this difficult situation is the use of explanatory artificial intelligence (eXplainable Artificial Intelligence (XAI)). In this work, as such an explanatory technology, we propose cognitive dynamic SW prediction.