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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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STS et Intelligence Artificielle: une rencontre manquée

Zilsel. Science, Technique, Société . 2019. No. 5. P. 151–160.
Kirtchik Olessia

Les percées récentes de « l’apprentissage profond » (deep learning) favorisées par les investissements des géants du numérique transnationaux ont contribué, dans la seconde moitié des années 2010, à faire passer l’intelligence artificielle (IA) du statut d’objet de science-fiction à celui de problème public. L’ensemble des techniques, des architectures et des algorithmes, connu sous ce nom, semble enfin réaliser les promesses de « la vieille IA » (faites à partir de la fin des années cinquante) d’apprendre aux machines des tâches telles que les jeux d’échecs, la reconnaissance de l’image et de la parole, la traduction et la gestion de l’information – objets de référence de l’IA, mais a aussi rendu possible de nouvelles applications telles que la prédiction comportementale et la data analyticscomme outil d’extraction des connaissances quasi-universel. Ces avancées techniques (et surtout ce qu’elles promettent à l’avenir) sont actuellement très prisées par des entreprises privées les plus diverses et par des gouvernements comme un enjeu majeur dans la concurrence internationale pour le pouvoir économique et politique.

Research target: Sociology (including Demography and Anthropology
Priority areas: sociology
Language: French
Full text
DOI
Text on another site
Keywords: искусственный интеллектsociology of science and technologyсоциология науки и техникиartificial intelligence
Publication based on the results of:
Spatial Factor in Theoretical Field of Humanities and Social Sciences (2019)
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