Machine learning technologies in legislative activities: analytical and predictive potential

• Sergey Zenin ^[1] ; Osman Izhaev ^[2] ; Dmitry Kuteynikov ^[3] ; Ivan Yapryntsev ^[4]
  1. [1] Kutafin Moscow State Law University, Russia South-Ural state University (National Research University), Russia
  2. [2] Moscow city election commission, Russia
  3. [3] Kutafin Moscow State Law University, Russia
  4. [4] Judge of the Constitutional Court, Russia

  Mostrar afiliaciones +
• Localización: Revista Inclusiones: Revista de Humanidades y Ciencias Sociales, ISSN-e 0719-4706, Vol. 7, Nº. Extra 17 (octubre-diciembre), 2020 (Ejemplar dedicado a: Espacio y Tiempo en el Siglo XXI), págs. 359-371
• Idioma: inglés
• Enlaces
  • Texto completo
• Resumen

  • 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.