Digital encoding of concepts

The tasks of encoding concepts of human knowledge in the digital medium of computers and networks are of particular relevance in connection with the widespread use of artificial intelligence systems in the world. In the process of expanding the scope of their applications, the range of categories of encoded concepts is increasing. In addition to conventional concepts, which have stable forms of their presentation, for example, by the words of natural languages, it is often necessary to encode personal and collective concepts in the digital medium. Moreover, sometimes, it is necessary to take into account the degree of their socialization (the Wierzbicki&Nakamori's term) and reflect the dynamics of their change over time, as well as the stages of their transformation into conventional concepts. In the time dimension, the spectrum of scales has expanded for describing the dynamics of concepts of human knowledge. If earlier scales were used with units of measuring the dynamics of concepts in hundreds and tens of years (less often scales with accuracy up to a year and a month were used), then for personal and collective concepts, it is necessary to use a scale that fixes their dynamics up to days, and sometimes hours and minutes. The goal of the paper is to describe the asymmetry problem encountered in the encoding process of concepts in the digital medium. The asymmetry significantly complicates the processes of representing human knowledge in artificial intelligence systems. To solve this problem, it is proposed to use at the same time encoding of both concepts of the listed categories and forms of their expression in the digital medium. The proposed approach is illustrated by the example of an intelligent vocabulary system that uses encoding of both concepts and words, which are verbal forms of concept representation.