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  • Ты, я и «Алиса»: как мы уживаемся с искусственным интеллектом
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Subject
News
May 25, 2026
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
May 25, 2026
'The Humanities Serve as a Conscience'
Maria Mizernaia studies Soviet literature and the history of book publishing. In this interview for the HSE Young Scientists project, she discusses plans to publish a novel about besieged Leningrad, AI-provoked reflections on what it means to be human, and how novels can help satisfy our dopamine hunger.
May 25, 2026
Is It Possible to Predict a Citys Life Based on the Shape of Its Neighbourhoods?
Is it possible to predict, based on the configuration of streets and buildings, where a café will open or where traffic congestion will occur? Participants in the Spatial Analysis and Modelling of Urban Processes research and study group use open data and machine learning to identify universal patterns. Alexander Sheludkov and Eduard Somov discuss the purpose of comparing cities, the need for new forms of urban statistics, and how open data is transforming approaches to urban studies.

 

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Ты, я и «Алиса»: как мы уживаемся с искусственным интеллектом

Вестник Московского университета. Серия 10: Журналистика. 2024. № 3. С. 186–207.
Shomova S.

The article accumulates the results of one of the facets of a large study conducted in 2023 by the HSE Center for Digital Cultures and Media Literacy. 350 questionnaires received from students, teachers of media specialties and specialists in the creative industries – journalists, advertisers, designers, museum staff, etc. – in five regions of Russia were thematically devoted to the current self-perception of Russians "on the threshold of the neural network revolution"; the article focuses on the emotional spectrum of respondents' interaction with neural networks, which is a particularly interesting issue of modern media relevance. The range of emotions in communication with AI, the expectation of empathy from "smart devices", the problem of "humanizing" gadgets, building a dialogue with them – all these issues are reflected in the study.

Research target: Media and Communications
Language: Russian
Full text
DOI
Text on another site
Keywords: образованиеeducationэмпатияempathyemotionscreative industriesкреативные индустрииантропоморфизмAI (artificial intellence)эмоции человекаИскусственный интеллект anthropomorphism
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