On the issue of identifying fake conclusions of forensic medical examinations through the use of artificial intelligence technology (according to the experience of the Republic of Kazakhstan)

Abstract

The article discusses the legal aspects of the use of mathematical statistics and machine learning (hereinafter referred to as artificial intelligence) in forensic activities to identify both expert errors and fake expert opinions. An attempt has been made to establish criteria for evaluating the conclusions of forensic examinations in terms of determining their relevance, admissibility, reliability and objectivity, as well as the objective possibility of distinguishing expert errors from deliberately false and fake expert opinions. A SWOT analysis of the use of artificial intelligence was carried out to solve the issue of its application in the field under consideration, which revealed the advantages and disadvantages of its use. The use of mathematical statistics and machine learning methods is not a universal way to identify fakes in expert opinions. However, given that this method can give both false positive and false negative results, its results should be verified by independent experts. In addition, in order to effectively prevent the facts of falsification, it is concluded that it is necessary to take comprehensive measures, including not only the detection of manipulations, but also the prevention of the possibility of their occurrence, as well as the punishment of the perpetrators. To this end, the authors have proposed a number of amendments and additions to the current legislation of the Republic of Kazakhstan.