MACHINE LEARNING TECHNOLOGIES IN LEGISLATIVE ACTIVITIES: ANALYTICAL AND PREDICTIVE POTENTIAL - Zenin, Sergey; Izhaev, Osman; Kuteynikov, Dmitry; Yapryntsev, Ivan (Revista Inclusiones, 2020)
Growing automation in the spheres of public administration predetermines the need to form a doctrinal and applied understanding of its consequences in different manifestations. The introduction of information technologies into legislation is only one direction of forming and developing a digital state, which is among the most important phenomena. This study is based on the dialectical approach and a combination of general and specific scientific methods of cognition and comprehension. The article considers the use of such algorithms in various spheres that are often unrelated to lawmaking.