REVISTA DE HUMANIDADES Y CIENCIAS SOCIALES

MACHINE LEARNING TECHNOLOGIES IN LEGISLATIVE ACTIVITIES: ANALYTICAL AND PREDICTIVE POTENTIAL

Autores/as

  • Ph. D. (c) Sergey Zenin
  • Ph. D. (c) Osman Izhaev
  • Ph. D. (c) Dmitry Kuteynikov
  • Ph. D. (c) Ivan Yapryntsev

Palabras clave:

Legislative activity, Machine learning technology, Machine learning algorith, Discrimination

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.

Publicado

11-05-2020

Cómo citar

Zenin, Sergey, Osman Izhaev, Dmitry Kuteynikov, y Ivan Yapryntsev. 2020. «MACHINE LEARNING TECHNOLOGIES IN LEGISLATIVE ACTIVITIES: ANALYTICAL AND PREDICTIVE POTENTIAL». Revista Inclusiones, mayo, 359-71. https://revistainclusiones.org/index.php/inclu/article/view/1513.

Artículos más leídos del mismo autor/a