LAUSR

The article discusses the functioning of human-like consciousness and the potential for developing a chatbot based on human-like consciousness. The proposed approach was verified experimentally using a sociological method and by attracting a cohort of student volunteers. The chatbot population was created on the back of our complex neural network architecture design. The volunteers were asked to identify their interlocutor, which was either a human agent or a chatbot. For integrity, the conversations between bots and people were organized randomly so that each volunteer could interact several times with all bots in the population and with all participants in the sample. The article discusses the results of the study, the details of the proposed approach. The article explains the features of the functioning and self-reconfiguration of the neural network that provide high reliability of chatbot replicas and high speed of responses to replicas of human users so that the delay time does not raise suspicion of human users. The main idea of the authors’ approach is an attempt to model human self-awareness and self-reflection. The results prove the proposed neural network architecture design successful in terms of real-time self-learning.