Translartion. Region: Russians Fedetion –
Source: State University Higher School of Economics – State University Higher School of Economics –
The Institute for Statistical Studies and Economics of Knowledge at the National Research University Higher School of Economics, based on statistical data and a specialized survey called “Making Science in Russia,” analyzes the prevalence of practices in scientific organizations and universities in the country that use AI solutions to carry out research and development.
Reference: The “Doing Science in Russia” study is a continuation of the Doing Science project (the first two waves were conducted in 2017 and 2022). As part of the third wave (October-November 2024), representatives of 719 scientific organizations and universities (heads or their deputies for research activities) were asked to rate on a five-point scale the level of provision with AI systems for research and development.
This issue of the series “Artificial Intelligence” was prepared within the framework of the project “Monitoring scientific support for measures to achieve technological leadership of the Russian Federation” of the thematic plan of research work provided for by the State assignment of the National Research University Higher School of Economics.
Modern AI-based technologies are changing the usual way of life in all areas of activity, and science is no exception. SurveyA 2023 Nature study found that more than a quarter of scientists already using AI in their research expect the technology to become an essential tool for their field in the next 10 years, with another 47% believing it will be very useful. Related study Oxford University Press shows that we won’t have to wait that long: 75% of surveyed scientists publishing in leading journals have already used various AI tools in 2024, including machine translation services (49%), chatbots (43%) and search engines (25%). According to respondents, AI-based solutions are useful at all stages of the research cycle and for a wide range of tasks: 41% of respondents used them to search for literature, about 35% – for its generalization and/or editing of text (e.g., an article manuscript), 25% – for idea generation, data collection and/or its analysis.
According to statistics, the implementation of AI solutions in the field of science in Russia is only gaining momentum. In 2023, about 5% of scientific organizations and about 10% of universities used AI for their purposes, but these figures do not fully reflect the real scale of the use of this technology by scientists, since they characterize only the practices of the organizations themselves, and not their employees.
In the future, we should expect the expansion of AI implementation in the field of science and higher education: every second organization sees prospects for further use of relevant tools in their activities here. In addition, almost 25% of scientific organizations and 38% of universities that are already using AI believe that such technologies will radically change internal processes in science in the coming years; many of them consider intelligent decision support technologies to be the most promising for these tasks (33%).
It is obvious that the possibility of realizing these expectations largely depends on the level of development of the necessary digital infrastructure. As shown by a survey of 719 scientific organizations and universities conducted by the HSE ISSEK as part of the Doing Science in Russia project (October-November 2024), access to AI systems for research and development is still difficult. The surveyed executives rated the availability of such foreign-developed systems (ChatGPT, Trinka, Mendeley, Scite, Google Jax, etc.) at 2.71 points out of a possible five, and domestic systems (GigaChat, GitVerse, YaLM, SOVA, RAZUM AI, GOLEM, NeuroMark, AI BAUM PLATFORM, NNWizard, etc.) even lower, at 2.60 points. The situation is somewhat better in universities than in other organizations (Fig. 1).
Against the background of restrained assessments of the current situation, forecasts for the next three years look more optimistic: organizations of all types expect a significant increase in the use of AI systems for research and development. Of course, to ensure such dynamics, it is necessary to remove barriers that hinder the spread of AI in science. Among the most significant of them, universities and scientific organizations note: a shortage of financial resources, a shortage of qualified personnel, an insufficiently developed ICT infrastructure, a shortage/low quality of big data for the implementation of AI. Half of the universities and about 40% of scientific organizations point to the influence of these restraining factors.
Overcoming barriers to the spread of AI in Russian science could be facilitated by a special program that would provide for the development of research standards using AI; grants for young scientists and research teams studying and using AI in their work (with priority given to those areas of science where such technologies are rarely used); support for the development of AI applications for scientific tasks; compensation for the costs of universities and research organizations for the purchase of big data for the purposes of training and development of generative models.
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Suggested citation:
Streltsova E. A., Popov E. V., Gershman M. A. (2025) Artificial Intelligence in Science. Moscow – ISSEK HSE. Access mode: https://issek.hse.ru/news/1015931860.html.
Previous issue series “Artificial Intelligence”:“Big Data for AI”
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