On the challenges of preparing teachers for artificial intelligence technologies

in connection with the changes taking place in society, connected with the construction of a new technological mode, caused by new information technologies in the first place, connected with the development of artificial intellect, there is a need to train highly qualified teachers competent in this field. This implies changes in the content of teacher training as the experience of informatization of teachers of mathematics and informatics shows. Analysis of curricula for training such teachers within the framework of bachelor's degree shows that fundamental training is difficult since AI is now a set of different semi-empirical models operating on many different sections of mathematics. At the same time, teachers need to be trained to use AI systems as a tool in their work. The authors propose to focus on the sections of AI related to the use of neural networks, as this direction is currently the most effective, while defining a unified approach to their description, based on the classical sections of mathematical and functional analysis. In this case, it is possible to present tools for creating and training neural networks in the form of a constructor consisting of the necessary software with clear interrelationships between them. Unfortunately, due to sanctions, there may be and are problems related to access to big data, to libraries of algorithms, to international resources where AI problems are discussed and due to possible “bookmarks”, there may be problems with information security. This forces us to switch to Russian software. In spite of the complexity of the problems we are facing, the authors consider it necessary to maintain the trend towards fundamentalization of mathematical training of teachers of mathematics and computer science. In this case, AI will be a tool in the hands of the teacher, and the teacher will not become an application for artificial intellect.

mathematics, artificial intelligence systems, information technology, neural networks, machine learning