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News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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AI Implementation by Small Entrepreneurs in Russia: Flowers Grow also on Stones

Central European Business Review. 2026. Vol. 15. No. 2. P. 69–90.
Chepurenko A., Dormidontova Y.

This study examines the individual factors of artificial intelligence (AI) implementation by small and medium-sized enterprise (SME) owners, based on a survey of 499 respondents in Russia. Drawing on Innovation Diffusion Theory, the Technology Acceptance Model (TAM), and stakeholder-oriented sustainability approach, the analysis shows that SME owners who already use AI for private purposes are more likely to implement it in their businesses. Owners who see AI as potentially damaging to their businesses are also more likely to adopt it. Those who believe AI will harm the economy overall are less likely to use it. Younger entrepreneurs are more inclined to adopt AI. Education is not significant. Owners of larger SMEs and those in urban areas are more likely to adopt it. The findings challenge TAM based evidence regarding the role of hedonic motivation: in this post-transitional economy, expected damage to one’s own business emerges as a key driver of AI implementation by SMEs. Implications for Central Eastern European audience: As AI penetration grows in CEE, SME owners with personal AI experience should be more likely to implement AI in business, with younger entrepreneurs expected to lead adoption, similar to Russia. However, unlike Russia, urban-rural differences in CEE may be less pronounced due to a closer distances between cities and rural areas, potentially diminishing the role of settlement in AI adoption. Policies emphasizing practical, experiential learning opportunities may be more effective than formal education, given the limited additional technical skills required for AI implementation in SMEs.

Research target: Sociology (including Demography and Anthropology Economics and Management
Language: English
Full text
DOI
Text on another site
Keywords: small and medium-sized entrepreneurshipInnovation adoptionArtificial intelligence (AI)
Publication based on the results of:
Russian small business under external shocks: dynamics of adaptation (longitudinal study) (2024)
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