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Geography of Artificial Intelligence Technologies in Russiaстатья
Статья опубликована в журнале из списка RSCI Web of Science
Статья опубликована в журнале из перечня ВАКСтатья опубликована в журнале из списка Web of Science и/или Scopus
- Автор: Zemtsov S.
- Журнал: Regional Research of Russia
- Том: 14
- Номер: 4
- Год издания: 2024
- Издательство: Pleiades Publishing, Ltd
- Местоположение издательства: Road Town, United Kingdom
- Первая страница: 525
- Последняя страница: 536
- Аннотация: Zemtsov S. Geography of Artificial Intelligence Technologies in Russia // Regional Research of Russia. 2024. Vol. 14. No. 4. P. 525–536 ||| The geography of innovation makes it possible to identify spatial patterns of creation, implementation, and diffusion of new technologies, but with the development of communications, an illusion appeared that space is insignificant. In accordance with the aim of the study, the article shows that creation and implementation of artificial intelligence (AI) as one of the radical innovations cannot be widespread. It will be concentrated in centers with high innovation potential and specialized tacit knowledge, where the intensity of knowledge spillovers is higher. In Russia, an education in AI can be obtained in 21 regions, research is conducted in 35, and technology is being developed in 40. The article proposes a rating of regional potential for AI creating, assessing scientific and technological development and density of the main elements of regional innovation ecosystems. The rating shows a high concentration of potential in the largest agglomeration, Moscow, and several creative cores: Moscow oblast, St. Petersburg, the Republic of Tatarstan, and Novosibirsk oblast. Sixteen centers have been identified capable of both creating and implementing certain AI technologies: Sverdlovsk, Nizhny Novgorod, Chelyabinsk, Samara, Tomsk, and Rostov oblasts, Krasnodar krai, etc.; 23 regions that are predominantly acceptor centers using AI advanced production technologies and 41 regions with minimal potential. Leading regions may receive priority attention and funding by investors. In acceptor regions, public policy priority may be given to supporting production automation, and in lagging regions, preference may be given to increasing the population’s receptivity to digital technologies.
- Добавил в систему: Земцов Степан Петрович
Прикрепленные файлы
| № | Имя | Описание | Имя файла | Размер | Добавлен |
|---|---|---|---|---|---|
| 1. | RERR525.pdf | RERR525.pdf | 1,2 МБ | 25 декабря 2024 [spzemtsov] |