Аннотация
Technological innovations, globalization, the political and economic environment, as well as socio-cultural features have a noticeable impact on the structure, content and orientation of media communications. Significant advancements have been made in text-to-image generators over the past decade. AI opens up new possibilities, enabling anyone to effortlessly generate visually stunning images without the need for artistic skills. However, it also leads to the creation of more stereotypes when using large amounts of data. Consequently, stereotypes are becoming more prevalent and serious than ever before. The given article is devoted to a comprehensive study of the text-to-image AI model generators influencing the formation of the predominantly negative (prejudicial) and positive stereotypes. The main objective was to investigate the presence of representational cultural, ethnical biases in AI-generated pictures in an Intercultural communication, check them via AI platforms and give a number of recommendations concerning the issue. The research is based on the analysis of theoretical foundations, historical backgrounds, contextual and extralinguistic factors that lead to the generation of stereotypes by AI, as a result they impede, hinder Intercultural communication. Through the following methods as Synthesis, Descriptive analysis, the method of content analysis (qualitative and quantitative), the method of semantic categorization the author determined key trends, issues concerning stereotypes generated by AI.