Features of Using Neural Networks in Crowdfunding in the Russian Federation: A Legal Status

Introduction: the development of civil society in order to achieve socially oriented goals is not possible without the active participation of representatives of society in it. The dynamics of the development of auxiliary systems for supporting these relationships, in modern conditions, increasingly begin to depend on machine analysis systems for both information and the priorities of participation of subjects in relationships that correspond to the interests of society’s development and are based on neural network programming. The above-mentioned has formed the purpose of the study: to conduct a scientific analysis of the use of machine analysis systems in determining the legal and machine-logical prerequisites for citizens’ participation in crowdfunding of an economic and civil nature. Methods: the methodological framework for the conducted research is the methods of scientific cognition, including such main ones as the methods of consistency, analysis and comparative law and the methods of machine analysis of social relations. Result: the authors have analyzed the legal status of crowdfunding in the Russian Federation, which refers to all forms of collective participation of citizens in the implementation of civil initiatives, both commercial and social, and provided the main positive and negative indicators of the use of neural networks in calculating indicators of participation in civil projects. Conclusions: the use of modern machine analysis systems is acceptable in practice, but it can generate a complex of legal, organizational, interpretative, impartial and ethical problems.

Authors

Institutions

Publication Details

Journal
Legal Concept
Published
2024-12-30
DOI
https://doi.org/10.15688/lc.jvolsu.2024.4.10
Primary Topic
Digital Transformation in Law
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Features of Using Neural Networks in Crowdfunding in the Russian Federation: A Legal Status

Gennady G. Egorov, Tatyana V. Derkacheva
1 links
Legal Concept
Digital Transformation in Law
article

Features of Using Neural Networks in Crowdfunding in the Russian Federation: A Legal Status

Gennady G. Egorov, Tatyana V. Derkacheva
article en

Abstract

Introduction: the development of civil society in order to achieve socially oriented goals is not possible without the active participation of representatives of society in it. The dynamics of the development of auxiliary systems for supporting these relationships, in modern conditions, increasingly begin to depend on machine analysis systems for both information and the priorities of participation of subjects in relationships that correspond to the interests of society’s development and are based on neural network programming. The above-mentioned has formed the purpose of the study: to conduct a scientific analysis of the use of machine analysis systems in determining the legal and machine-logical prerequisites for citizens’ participation in crowdfunding of an economic and civil nature. Methods: the methodological framework for the conducted research is the methods of scientific cognition, including such main ones as the methods of consistency, analysis and comparative law and the methods of machine analysis of social relations. Result: the authors have analyzed the legal status of crowdfunding in the Russian Federation, which refers to all forms of collective participation of citizens in the implementation of civil initiatives, both commercial and social, and provided the main positive and negative indicators of the use of neural networks in calculating indicators of participation in civil projects. Conclusions: the use of modern machine analysis systems is acceptable in practice, but it can generate a complex of legal, organizational, interpretative, impartial and ethical problems.

Legal ConceptVol. 23(4)
Volgograd State University (RU)
Openalex Percentile: Top 49%
Digital Transformation in Law
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.