The essence of economic complexity is that some of the biggest social problems of our time begin to make sense only if we look at the systemic interactions that give rise to them. As an example of a systematic interaction, it is suggested that we look at the unemployment rate. Analyzing economic complexity offers a broad framework that can be applied to many social indicators. On issues related to social employment, the hypothesis of a relationship between a country's economic complexity and the unemployment rate is born. The discussion begins by examining how humans have been able to compartmentalize the process of knowledge production and organize complex interdependencies that in turn create extraordinary technologies. The purpose of this study is to prove or disprove the hypothesized relationship between the economic complexity index and the unemployment rate. Using the correlation and regression model, it was possible to identify an indirect relationship between the two indicators under study, thereby confirming the above hypothesis. Economic complexity offers a potentially powerful paradigm for understanding the key social issues and challenges of our time. Growth, development, technological change, income inequality and even unemployment are the visible results of hidden systemic interactions. Understanding the structure of these interactions and how they shape different socio-economic processes is therefore important in the study of economic complexity. The findings shed new light on the potential of economic complexity to track and predict the innovation potential of countries and interpret temporal dynamics. Economic growth could possibly pave the way for better and more unemployed populations.