‘Economic Growth Without the AI Factor Is No Longer Possible’
The International Summer Institute on AI in Education has opened in Shanghai. The event is organised by the HSE Institute of Education in partnership with East China Normal University (ECNU). More than 50 participants and key speakers from over ten countries across Asia, Europe, North and South America have gathered to discuss the use of AI technologies in education and beyond.
At the opening session of the Summer Institute, Prof. Meng Yu and Xu Fei, Vice Dean of the School of Computer Science and Technology at ECNU, emphasised that the rapid development of AI technologies demands international cooperation and interdisciplinary research. ‘We are delighted to join forces with the HSE Institute of Education and are confident that this week in Shanghai will serve as a starting point for long-term joint projects,’ said Meng Yu and Xu Fei.
Evgeniy Terentev, Director of the Institute of Education, noted that research alliances between Russian and Chinese universities are gaining strategic importance and opening up new horizons for cooperation. He also presented the findings of one of the institute's latest studies—a typology of how Russian universities are responding to generative AI, ranging from prohibition to active adoption. The analysis showed that most universities remain in a grey area, without formalising rules on the use of new technologies.
In his keynote speech, Yaroslav Kuzminov, Academic Supervisor of HSE University, outlined five key areas in which AI is already transforming higher education. First is the need to change teaching practices and educational routines. Second is the evolving role of human cognitive skills. Third is the potential to overcome academic underachievement by establishing mechanisms for personalised feedback. In addition, there are new learning formats (including game-based ones). The fifth area concerns new mechanisms of labour market integration based on real skills rather than the ability to perform routine tasks.
He also highlighted potential avenues for using AI to empower and strengthen individuals. ‘Effective and competent integration of AI in education—guided by transparent rules, encouraging students to tackle more complex tasks with AI than without it, and supported by personalised recommendations—can reduce academic failure and unlock economic potential. This in turn fosters equal opportunities for developing a competitive workforce and ensures sustainable development. We must therefore move towards future literacy and AI literacy, recognising that economic development without AI is no longer feasible—but regression is quite possible if the technology is used carelessly or ineptly,’ Yaroslav Kuzminov concluded.
Ekaterina Kruchinskaia, Senior Lecturer at the HSE Department of Higher Mathematics, supported that idea and presented the results of a survey conducted among students from ten selective (top-tier) Russian universities. The survey revealed that students most commonly use generative models for summarising texts, data analysis, and programming. However, the time savings remain minimal due to the need to verify the outputs. Moreover, usage practices are still unstructured, and students tend to use AI mainly to free up more time for rest rather than to take advantage of generative models to tackle more complex and creative tasks.
‘The risks associated with generative AI will be significantly reduced once usage practices become more institutionalised, and students are motivated not to imitate, but to improve their actual performance,’ Ekaterina Kruchinskaia concluded.
Prof. Okan Bulut of the University of Alberta (Canada) also gave a lecture on challenges of applying artificial intelligence in education. He highlighted the main difficulties in assessing AI use and discussed how the technology could be harnessed to enhance learning. Continuing the topic, Assistant Professor Mick Fanguy from the Education University of Hong Kong spoke about the evolving understanding of computer-supported collaborative learning. He explained that, whereas in the past technology was seen merely as a tool for student-to-student interaction, today AI tools themselves are becoming full participants in the learning process. Using an example of group work with a text, Assistant Professor Fanguy highlighted new risks of free-riding—cases where students use AI primarily to save time rather than to deepen collaborative engagement—and proposed a research agenda focused on the behaviour of individual participants.
The first day concluded with an academic ‘speed-dating’ session, during which participants exchanged ideas about their projects and identified the challenges they would work on over the course of the week in Shanghai. Ahead lies a programme of lectures, masterclasses, and workshops on research methods. At the end of the Summer Institute, each participant will present their research project, incorporating feedback and recommendations received from experts at the HSE Institute of Education and ECNU.
See also:
The Future of Cardiogenetics Lies in Artificial Intelligence
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a program capable of analysing regions of the human genome that were previously inaccessible for accurate interpretation in genetic testing. The program adapts large generative AI (GenAI) models for cardiogenetics to predict how specific mutations affect the function of individual genes.
HSE and Yandex Propose Method to Speed Up Neural Networks for Image Generation
A team of scientists at HSE FCS and Yandex Research has proposed a method that reduces computational costs and accelerates text-to-image generation in diffusion models without compromising quality. These models currently set the standard for text-to-image generation, but their use is limited by high computational loads, the company said in a statement.
A Trap for the Advanced Student: How to Break the Habit of Blindly Trusting Neural Networks
Andrei Ternikov, Associate Professor at the St Petersburg School of Economics and Management at HSE University–St Petersburg, has developed a method for conducting online exams that significantly limits students’ ability to use ChatGPT and other AI models to obtain correct answers. Andrei Ternikov spoke to the HSE News Service about his approach—which won the HSE University Autumn Educational Innovation Competition, received an Alfa Future grant, and was presented at an international conference in Japan.
HSE Researchers Train Neural Network to Predict Protein–Protein Interactions More Accurately
Scientists at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a model capable of predicting protein–protein interactions with 95% accuracy. GSMFormer-PPI integrates three types of protein data (including information about protein surface properties) to analyse relationships between proteins, rather than simply combining datasets as in previous models. The solution could accelerate the discovery of disease molecular mechanisms, biomarkers, and potential therapeutic targets. The paper has been published in Scientific Reports.
Human Intuition Proves Stronger than Algorithms: Game Theory Tournament Held at HSE University in Perm
Researchers from the International Laboratory of Intangible-driven Economy (Perm) and the HSE Laboratory of Sports Studies, together with mathematician and science populariser Alexey Savvateev, organised a game theory tournament entitled ‘The Election Race.’ Participants competed both against one another and against artificial intelligence. For now, humans have managed to gain the upper hand and propose more effective strategies.
Educational Programmes on Robotics and Neural Network Technologies Launch at HSE University’s Faculty of Computer Science
Every year, in response to IT industry demands, the Higher School of Economics Faculty of Computer Science launches new educational programmes while updating existing ones. In 2026, the faculty introduced Bachelor’s and Master’s degree programmes in robotics for the first time.
‘Policymakers Should Prioritise Investing in AI for Climate Adaptation’
Michael Appiah, from Ghana, is a Postdoctoral Fellow at the International Laboratory of Intangible-Driven Economy (IDLab) at HSE University–Perm. He recently spoke at the seminar ‘Artificial Intelligence, Digitalization, and Climate Vulnerability: Evidence from Heterogeneous Panel Models’ about his research on ‘the interplay between artificial intelligence, digitalisation, and climate vulnerability.’ Michael told the HSE News Service about the academic journey that led him to HSE University, his early impressions of Perm, and how AI can be utilised to combat climate change.
AI Overestimates How Smart People Are, According to HSE Economists
Scientists at HSE University have found that current AI models, including ChatGPT and Claude, tend to overestimate the rationality of their human opponents—whether first-year undergraduate students or experienced scientists—in strategic thinking games, such as the Keynesian beauty contest. While these models attempt to predict human behaviour, they often end up playing 'too smart' and losing because they assume a higher level of logic in people than is actually present. The study has been published in the Journal of Economic Behavior & Organization.
HSE Scientists Develop DeepGQ: AI-based 'Google Maps' for G-Quadruplexes
Researchers at the HSE AI Research Centre have developed an AI model that opens up new possibilities for the diagnosis and treatment of serious diseases, including brain cancer and neurodegenerative disorders. Using artificial intelligence, the team studied G-quadruplexes—structures that play a crucial role in cellular function and in the development of organs and tissues. The findings have been published in Scientific Reports.
HSE Strategic Technological Projects in 2025
In 2025, HSE University continued its participation in the Priority 2030 Strategic Academic Leadership Programme, maintaining a strong focus on technological leadership in line with the programme’s updated framework. A key element of the university’s technological leadership strategy is its Strategic Technological Projects (STPs), aimed at creating in-demand, knowledge-intensive products and services.