Data analysis with the help of artificial intelligence aimed at preventing extraordinary occurrences

Abstract

In this study, I examine the question of whether the frequency of extraordinary occurrences (hereinafter: EO) can be specifically prognosticated for a prison or a person (inmate), and whether a continuously operating, automated analysis and evaluation system utilizing artificial intelligence (hereinafter: AI) can be created for this task. I answer the questions rising form the above mentioned hypothesis in four steps, by providing the necessary background information to assess them. Within the framework of the thought experiment, based on professional experience of the Intelligence Department (hereinafter: Department) I introduce a theoretical model at first, whose elements and their building on one another result in the development of EOs. In the following, I present the patterns created and utilized during the professional work of the Department. Finally, I outline the benefits and possibilities to implement AI applications in term of recognizing patterns created based on the model.