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  • ВЗАИМОДЕЙСТВИЕ ГОСУДАРСТВА И БИЗНЕСА В ОБЛАСТИ РАЗВИТИЯ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА
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News
July 16, 2026
Team Success: Aligning Means with Objectives
In corporations, sports, and academia, people often face challenges they cannot handle alone. In such cases, selecting the right team is crucial. Tatiana Mayskaya, Associate Professor at the HSE Faculty of Economic Sciences and the International College of Economics and Finance, together with colleagues from foreign universities, examined team characteristics and found that less diverse teams are better suited to objectives where a high average performance is important, whereas more diverse teams are preferable when avoiding failure is critical. The paper has been published in Economic Theory.
July 15, 2026
Economists Propose More Effective Approach to Reducing Smoking
Economists at HSE University have examined how smokers respond to changes in cigarette prices. When tobacco prices increase, cigarette consumption does not always decline. In fact, spending on tobacco may even rise: according to the researchers, a 1% decrease in cigarette affordability leads to a 0.28% increase in per capita tobacco expenditure. The findings suggest that to reduce smoking rates, tobacco prices must rise faster than household incomes. The study has been published in Voprosy Statistiki.
July 15, 2026
HSE MIEM Students to Develop Two Satellites from Scratch for Orbital Experiments
The devices, created by student teams, will conduct space research on the properties of promising solar cells, on-board energy storage systems, and serial electronics for student satellites.

 

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ВЗАИМОДЕЙСТВИЕ ГОСУДАРСТВА И БИЗНЕСА В ОБЛАСТИ РАЗВИТИЯ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА

Бизнес. Общество. Власть. 2025. № 3 (57). С. 129–143.
Алексеев М. Ю., Гребенюк Е. А., Лукашевич А. И., Николаев П. В., Холодная М. А.

This article examines the models of government–business interaction in the advancement of artificial intelligence in the United States, China, and Russia. The analysis demonstrates that the U.S. venture-grant model, China’s state-corporate model, and Russia’s cross-sector model facilitate AI deployment in different ways, each with distinct advantages and limitations. The findings clarify how national AI strategies can be optimized.

Language: Russian
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Keywords: инновационная политикаискусственный интеллектinternational experiencepublic–private partnershipцифровая трансформация artificial intelligence
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