Neural network as a mirror of social attitudes: analysis of distortions in generative images
The article is devoted to the consideration of neural network generative technologies as a marker of social stereotypes and attitudes. The aim of the research – approbation of generative artificial intelligence (hereinafter referred to as AI) as a method of sociological research of social stereotype...
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| Format: | Article |
| Language: | Russian |
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State University of Management
2025-01-01
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| Series: | Цифровая социология |
| Subjects: | |
| Online Access: | https://digitalsociology.guu.ru/jour/article/view/343 |
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| author | A. G. Tertyshnikova U. O. Pavlova M. D. Starovoytova |
| author_facet | A. G. Tertyshnikova U. O. Pavlova M. D. Starovoytova |
| author_sort | A. G. Tertyshnikova |
| collection | DOAJ |
| description | The article is devoted to the consideration of neural network generative technologies as a marker of social stereotypes and attitudes. The aim of the research – approbation of generative artificial intelligence (hereinafter referred to as AI) as a method of sociological research of social stereotypes contained in big data. To realise this goal, the essence of AI, the legal framework of application and the spread to date are initially considered. The results of approbation show that the information returned by AI contains social stereotypes, primarily related to gender and age, which means that AI can indeed be used as a tool for studying social stereotypes. The source of shifts in data towards stereotypical images is contained in the data on which AI is trained, as well as in the code of the program itself, that is in the attitudes and worldview of developers, which in one way or another influence the process of program development. In most cases (more than 80% of all generated information), the AI returns young people, predominantly men, for queries related to high-paying professions, which is true for both gendered and non-gendered query formulations. AI is also characterised by attributing certain traits to different social groups, such as slovenliness and disorganisation, representing them in connection with a certain style of dress, and using several recurring markers to denote status or wealth. |
| format | Article |
| id | doaj-art-83244a9d6e3c41f18694d5f1346ae6b6 |
| institution | Kabale University |
| issn | 2658-347X 2713-1653 |
| language | Russian |
| publishDate | 2025-01-01 |
| publisher | State University of Management |
| record_format | Article |
| series | Цифровая социология |
| spelling | doaj-art-83244a9d6e3c41f18694d5f1346ae6b62025-02-04T16:32:35ZrusState University of ManagementЦифровая социология2658-347X2713-16532025-01-0174132110.26425/2658-347X-2024-7-4-13-21212Neural network as a mirror of social attitudes: analysis of distortions in generative imagesA. G. Tertyshnikova0U. O. Pavlova1M. D. Starovoytova2Peoples’ Friendship University of Russia named after Patrice LumumbaPeoples’ Friendship University of Russia named after Patrice LumumbaPeoples’ Friendship University of Russia named after Patrice LumumbaThe article is devoted to the consideration of neural network generative technologies as a marker of social stereotypes and attitudes. The aim of the research – approbation of generative artificial intelligence (hereinafter referred to as AI) as a method of sociological research of social stereotypes contained in big data. To realise this goal, the essence of AI, the legal framework of application and the spread to date are initially considered. The results of approbation show that the information returned by AI contains social stereotypes, primarily related to gender and age, which means that AI can indeed be used as a tool for studying social stereotypes. The source of shifts in data towards stereotypical images is contained in the data on which AI is trained, as well as in the code of the program itself, that is in the attitudes and worldview of developers, which in one way or another influence the process of program development. In most cases (more than 80% of all generated information), the AI returns young people, predominantly men, for queries related to high-paying professions, which is true for both gendered and non-gendered query formulations. AI is also characterised by attributing certain traits to different social groups, such as slovenliness and disorganisation, representing them in connection with a certain style of dress, and using several recurring markers to denote status or wealth.https://digitalsociology.guu.ru/jour/article/view/343artificial intelligencegenerative technologiesstereotypical biasdate-analysissocial stereotypesgender stereotypesexclusionbiasprofession |
| spellingShingle | A. G. Tertyshnikova U. O. Pavlova M. D. Starovoytova Neural network as a mirror of social attitudes: analysis of distortions in generative images Цифровая социология artificial intelligence generative technologies stereotypical bias date-analysis social stereotypes gender stereotypes exclusion bias profession |
| title | Neural network as a mirror of social attitudes: analysis of distortions in generative images |
| title_full | Neural network as a mirror of social attitudes: analysis of distortions in generative images |
| title_fullStr | Neural network as a mirror of social attitudes: analysis of distortions in generative images |
| title_full_unstemmed | Neural network as a mirror of social attitudes: analysis of distortions in generative images |
| title_short | Neural network as a mirror of social attitudes: analysis of distortions in generative images |
| title_sort | neural network as a mirror of social attitudes analysis of distortions in generative images |
| topic | artificial intelligence generative technologies stereotypical bias date-analysis social stereotypes gender stereotypes exclusion bias profession |
| url | https://digitalsociology.guu.ru/jour/article/view/343 |
| work_keys_str_mv | AT agtertyshnikova neuralnetworkasamirrorofsocialattitudesanalysisofdistortionsingenerativeimages AT uopavlova neuralnetworkasamirrorofsocialattitudesanalysisofdistortionsingenerativeimages AT mdstarovoytova neuralnetworkasamirrorofsocialattitudesanalysisofdistortionsingenerativeimages |