vovrВысшее образование в России (Vysshee obrazovanie v Rossii = Higher Education in Russia)Vysshee Obrazovanie v Rossii = Higher Education in Russia0869-36172072-0459Moscow Polytechnic University10.31992/0869-3617-2023-32-6-19-37vovr-4450Research ArticleВЫСШЕЕ ОБРАЗОВАНИЕ: КРИТИЧЕСКИЙ ДИСКУРСHIGHER EDUCATION: CRITICAL DISCOURSEChatGPT и искусственный интеллект в университетах: какое будущее нам ожидать?ChatGPT and AI in the Universities: An Introduction to the Near Futurehttps://orcid.org/0000-0002-3918-835XРезаевА. В.RezaevA. V.

Резаев Андрей Владимирович – д-р филос. наук, профессор, руководитель Международнойисследовательской лаборатории ТАНДЕМ

191124, г. Санкт-Петербург, ул. Смольного, д. 1/3

Web of Science ResearcherID: K-3472-2013 

Andrey V. Rezaev – Dr. Sci. (Philosophy), Professor, Director of International Research Laboratory TANDEM

1/3, Smolnogo str., 191124, Saint-Petersburg

rezaev@hotmail.comhttps://orcid.org/0000-0003-3259-5566ТрегубоваН. Д.TregubovaN. D.

Трегубова Наталья Дамировна – канд. социол. наук, доцент кафедры сравнительной социологии

Web of Science ResearcherID: K-3487-2013191124, г. Санкт-Петербург, ул. Смольного, д. 1/3

Natalia D. Tregubova – Сand. Sci. (Sociology.), Associate Professor, Chair of Comparative Sociology

1/3, Smolnogo str., 191124, Saint-Petersburg

n.tregubova@spbu.ruСанкт-Петербургский государственный университетРоссияSt. Petersburg State UniversityRussian Federation2023040720233261937Copyright © Резаев А.В., Трегубова Н.Д., 20232023Резаев А.В., Трегубова Н.Д.Rezaev A.V., Tregubova N.D.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://vovr.elpub.ru/jour/article/view/4450

Цель настоящей статьи состоит в том, чтобы представить теоретикометодологические основания анализа применения технологий искусственного интеллекта (ИИ) в высшем образовании в рамках человеко-ориентированного подхода к ИИ (HumanCentered AI) и рассмотреть конкретные направления использования технологий ИИ на примере ChatGPT. В качестве метода выступает критический анализ специальной литературы по проблематике развития технологий ИИ и их внедрения в высшей школе. Авторы начинают с формулировки теоретико-методологических оснований исследования. Затем следует рассмотрение «уроков» пандемии COVID-19 для высшего образования в эпоху развития ИИ и анализ технологий типа ChatGPT, которые имеют потенциал радикально изменить высшее образование в недалёком будущем. После этого авторы переходят к более общим замечаниям о перспективах и проблемах использования технологий ИИ в высшем образовании. Новизна исследования определяется обращением к анализу новейших разработок в области ИИ и определением динамики их влияния на высшее образование. В качестве основных результатов статьи выделяются основные направления, в рамках которых технологии ИИ могут внедряться в высшем образовании – аккредитация и лицензирование университетов, набор студентов, преподавание и обучение, – а также областей, в которых технологии ИИ использоваться не должны. В завершение формулируются две гипотезы, три общих и пять конкретных выводов об использовании технологий ИИ в высшем образовании. 

The paper aims to present the theoretical and methodological foundations for developing and implementing artificial intelligence (AI) instruments in higher education within the HumanCentered AI framework and considers ChatGPT as a specific case. It is oriented toward critically analyzing scholarly literature from various disciplines to support a-disciplinary approach to utilizing AI research in higher education. The authors begin by outlining the foundations of the research, then by analyzing the implications of the “lessons” of the COVID-19 pandemic for the development of higher education in the age of AI. This is followed by an analysis of technologies such as ChatGPT that have the potential to radically change higher education in the near future. After that, the authors move on to general remarks about the prospects and challenges of using AI technologies in higher education. The relevance of the research is characterized by the analysis of the latest developments in the field of AI and their possible impact on higher education. The main results of the paper are characteristics of areas in which AI technologies can be implemented in higher education – accreditation and licensing of universities, student recruitment, teaching and learning – as well as areas in which AI technologies should not be used. In conclusion, two hypotheses are formulated, and three general and five specific conclusions about the use of AI technologies in higher education are made. 

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The authors declare that there are no conflicts of interest present.