With the introduction of automation in various industries including the nuclear field, its side effect, referred to as the Out-of-the-Loop (OOTL) problem, has emerged as a critical issue that needs to be addressed. Many studies have been attempted to analyze and solve the OOTL problem, but this issue still needs a clear solution to provide criteria for introducing automation. Therefore, a quantitative estimation method for identifying negative effects of automation is proposed in this paper. The representative aspect of the OOTL problem in nuclear power plants (NPPs) is that human operators in automated operations are given less information than human operators in manual operations. In other words, human operators have less opportunity to obtain needed information as automation is introduced. From this point of view, the degree of difficulty in obtaining information from automated systems is defined as the Level of Ostracism (LOO). Using the LOO and information theory, we propose the ostracism rate, which is a new estimation method that expresses how much automation interrupts human operators' situation awareness. We applied production rules to describe the human operators' thinking processes, Bayesian inference to describe the production rules mathematically, and information theory to calculate the amount of information that human operators receive through observations. The validity of the suggested method was proven by conducting an experiment. The results show that the ostracism rate was significantly related to the accuracy of human operators' situation awareness, and that the calculation of the amount of information that human operators receive is useful as a measure of the ostracism rate.