{"title":"人工智能:发展前景与人性化问题","authors":"O. Digilina, I. Teslenko, Astghik A. Nalbandyan","doi":"10.22363/2313-2329-2023-31-1-170-183","DOIUrl":null,"url":null,"abstract":"The research explores the main problems associated with the development and implementation of artificial intelligence technologies in human activities, as well as with the humanization of these technologies. In a broad sense, artificial intelligence is a set of algorithms and software systems that can solve some problems the way a person would do and differ in that they are amenable to learning. An analysis of the problems of introducing artificial intelligence technologies makes it possible to substantiate the main levers of state policy aimed at the development and integrated use of digital intelligent systems. The success of the introduction and dissemination of artificial intelligence technologies largely depends on the effectiveness of state regulation of this sphere, both at the state and supranational levels. The development of machine learning systems must necessarily include an ethical aspect and some restrictions, otherwise the rapid development of intelligent machines can lead to the collapse of human civilization. To avoid such a development of events, it is necessary to create a supranational system for regulating artificial intelligence. Thus, the object of study of this article is the use of artificial intelligence systems in various fields of human activity. The authors use content analysis, systemic, adaptive and synergistic methods. In addition, the authors apply modern statistics, empirical generalization and grouping.","PeriodicalId":53005,"journal":{"name":"RUDN Journal of Economics","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"The artificial intelligence: Prospects for development and problems of humanization\",\"authors\":\"O. Digilina, I. Teslenko, Astghik A. Nalbandyan\",\"doi\":\"10.22363/2313-2329-2023-31-1-170-183\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The research explores the main problems associated with the development and implementation of artificial intelligence technologies in human activities, as well as with the humanization of these technologies. In a broad sense, artificial intelligence is a set of algorithms and software systems that can solve some problems the way a person would do and differ in that they are amenable to learning. An analysis of the problems of introducing artificial intelligence technologies makes it possible to substantiate the main levers of state policy aimed at the development and integrated use of digital intelligent systems. The success of the introduction and dissemination of artificial intelligence technologies largely depends on the effectiveness of state regulation of this sphere, both at the state and supranational levels. The development of machine learning systems must necessarily include an ethical aspect and some restrictions, otherwise the rapid development of intelligent machines can lead to the collapse of human civilization. To avoid such a development of events, it is necessary to create a supranational system for regulating artificial intelligence. Thus, the object of study of this article is the use of artificial intelligence systems in various fields of human activity. The authors use content analysis, systemic, adaptive and synergistic methods. In addition, the authors apply modern statistics, empirical generalization and grouping.\",\"PeriodicalId\":53005,\"journal\":{\"name\":\"RUDN Journal of Economics\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"RUDN Journal of Economics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.22363/2313-2329-2023-31-1-170-183\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"RUDN Journal of Economics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.22363/2313-2329-2023-31-1-170-183","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The artificial intelligence: Prospects for development and problems of humanization
The research explores the main problems associated with the development and implementation of artificial intelligence technologies in human activities, as well as with the humanization of these technologies. In a broad sense, artificial intelligence is a set of algorithms and software systems that can solve some problems the way a person would do and differ in that they are amenable to learning. An analysis of the problems of introducing artificial intelligence technologies makes it possible to substantiate the main levers of state policy aimed at the development and integrated use of digital intelligent systems. The success of the introduction and dissemination of artificial intelligence technologies largely depends on the effectiveness of state regulation of this sphere, both at the state and supranational levels. The development of machine learning systems must necessarily include an ethical aspect and some restrictions, otherwise the rapid development of intelligent machines can lead to the collapse of human civilization. To avoid such a development of events, it is necessary to create a supranational system for regulating artificial intelligence. Thus, the object of study of this article is the use of artificial intelligence systems in various fields of human activity. The authors use content analysis, systemic, adaptive and synergistic methods. In addition, the authors apply modern statistics, empirical generalization and grouping.