Natural language processing in the law-making process

The article outlines the relationship between the introduction of machine learning technology into the legislative process with the need for natural language processing (NLP), which is a necessary element in this process. The formation of databases covering the existing normative array is associated with the need to translate it into a machine-readable form, understandable to the algorithm. Using NLP allows performing such a transformation. The authors describe examples of the use of NLP in the legal field. Taking into account the results of such use, the article assesses the potential for the implementation of NLP in the framework of legislative activity. At the same time, the specificity of legal texts is noted, which predetermines the need for additional requirements for the process of their processing. In conclusion, the authors note some risks associated with the introduction of machine learning into the legislative process, but which can be minimized by using NLP.