ABSTRACT
Purpose: This chapter aims to study the modelling of conflict in the labour market in the conditions of automatization based on robots, Big Data and artificial intelligence (AI) from the position of countries' inequality and conflict management. Design/Methodology/Approach: It is determined that scientific literature has not formed the sufficient scientific and practical basis for determining the level of technological inequality of countries in the labour market in the conditions of automatization based on robots, Big Data and AI. The research objects are countries with the highest level of technological inequality from the position of automatization based on robots, Big Data and AI. Findings: This chapter performs an overview of the factors of technological inequality of countries, which leads to the global conflict on the labour market in the conditions of automatization based on robots, Big Data and AI. It is supposed that using the technology and methods of the system of engineer-ing knowledge within conflict management it is possible to find a non-stand-ard solution, which ensures better optimization. A complex technical method proves its rationality and opens the perspectives for further development of the methodology and integration of the systems of knowledge on conflict manage-ment;still, from the position of conflict in the labour market in the conditions of automatization, there are not enough means of conflict management that could neutralize or partially solve such global conflict. Originality/Value: It is proved that full automatization is a price paid by humans for prospering, while it is expected that new technologies will increase productivity and income. This will lead to the dismissal of certain employees and bankruptcy of the existing companies and productions, which is not that important for many large employers. For most employees, this is a conflict against the background of automatization, which leads to worse consequences for them. © 2022 by Konstantin V. Vodenko, Irina S. Bagdasaryan, Daria O. Tyurina and Galina B. Vlasova.