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  • Завтра: клиентоцентричность в мире будущего
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July 20, 2026
Scientists Create Open Dataset for Studying Concentration
A team of Russian researchers, including scientists from HSE University–St Petersburg, has developed the first open multimodal dataset containing recordings of brain activity, heart function, and video observations to help researchers understand what happens in the human brain during deep concentration. In the future, the dataset could accelerate the development of neural interfaces, rehabilitation technologies, and AI systems. The article has been published in Scientific Data.
July 20, 2026
‘Science Is Universal-It Knows No Borders
Fuad Aleskerov, Tenured Professor and Director of the International Centre of Decision Choice and Analysis at HSE University, together with his colleagues, has developed methods of network analysis in bibliometrics that have made it possible to identify patterns in the appearance and citation of publications in academic journals, as well as their influence on each other. When one or a number of studies are frequently cited by a wide range of journals, this is an indicator that the research is of high quality. By contrast, extensive cross-citation within a limited group of journals increases the likelihood of identifying a network of predatory publications.
July 20, 2026
Scientists Propose Method for More Efficient Resource Use in Machine Learning
An international group of researchers, including mathematicians from the AI and Digital Science Institute at the HSE Faculty of Computer Science, has provided a theoretical justification for a simple and computationally efficient method of estimating uncertainty in Stochastic Gradient Descent (SGD). The paper has been published on the scientific preprint server arXiv.org and presented at AISTATS 2026.

 

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?

Завтра: клиентоцентричность в мире будущего

Гл. 3. С. 143–200.
Староверова И. И., Кубанцева Е. В., Selskiy A., Snegirev A.

The third chapter of the monograph explores the future prospects of customer centricity in a world shaped by rapid advances in artificial intelligence, quantum computing, and related technologies. The authors analyze the shift from traditional linear customer journey models to dynamic, adaptive trajectories generated in real time by AI algorithms. Special attention is given to two breakthrough technological phenomena — digital twins of customers and autonomous digital agents.

Digital twins of customers are presented as an evolution of marketing "personas," representing dynamic models capable not only of predicting behavior but also of actively influencing it, enabling hyper-personalization and management of hybrid customer experience. Autonomous digital agents are examined within the context of emerging B2A (business-to-agent) and A2A (agent-to-agent) interaction models, where algorithms representing individuals and organizations become subjects of market relations. The chapter presents case studies from leading companies (Allianz, Amazon, McDonald’s, Sber) illustrating both successful and unsuccessful attempts at implementing these technologies.

A dedicated section addresses customer centricity in the future public sector, highlighting trends such as "people-less" public services, universal inter-agency integration, background services based on AI agents, and data-driven governance with co-creation elements. The final part systematizes ethical, legal, and regulatory risks associated with hyper-personalization, algorithmic bias, privacy loss, and liability distribution in AI product value chains. It is emphasized that sustainable development of customer centricity in the digital era requires a balance between technological innovation, user rights protection, and building trust in AI systems.

Language: Russian
Full text
Keywords: цифровые государственные услугиdigital public servicesalgorithmic biasалгоритмическая предвзятостьэтика ИИAI ethicsAI AgentsИИ-агентыtrust in AIдоверие к ИИhyper-personalizationгиперперсонализацияdynamic customer journeydigital twin of a customerautonomous digital agentB2AA2Aдинамический клиентский путьцифровой двойник клиентаавтономный цифровой агентB2AA2A

In book

Цифровая клиентоцентричность. Как современные технологии помогают компаниям и государству сделать шаг навстречу потребителям
Цифровая клиентоцентричность. Как современные технологии помогают компаниям и государству сделать шаг навстречу потребителям
Колбин Е. И., Кубанцева Е. В., Selskiy A., Snegirev A., Староверова И. И., Chernogortseva S. М.: ИСИЭЗ ВШЭ, 2026.
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