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August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
August 12, 2026
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Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
August 11, 2026
‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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Цифровые следы в пространстве университета

Цифровой ученый: лаборатория философа. 2021. Т. 4. № 2. С. 52–72.
Khusyainov T.

This work considers the use of digital traces in the educational environment and the specifics of their collection and analysis at the university. One way or another, all participants in the educational process, as well as those who can potentially become them, for example, applicants, leave digital traces in the digital environments of the university and the Global Network in general, and these traces can be analyzed. At the same time, even the university itself as an organization leaves a certain digital footprint on the Internet. At the moment, most researchers are very optimistic, contemplating on what positive changes can be brought by the analysis of digital traces of applicants, students and teachers for the development of the university itself, the educational process, and the formation of individual learning paths.

In contrast to this, the author identifies a number of possible prospects for the analysis of Big Data and the use of Artificial Intelligence for education at the university of the future. Attention is focused on how this can affect the safety of the environment and conflict with ethical standards. Participants in the educational process, falling under the analysis of their digital traces, can both suffer because of them, even if their activities have not been in any way connected with the university, and begin to hide their true digital identity, creating «false» digital traces and becoming anonymous. The author assumes that an increase in such control covering actions, thoughts and emotions naturally results in the emergence of the concept of a «Dark» University, which distances itself as much as possible from such methods of analyzing personal data

Research target: Philosophy, Ethics, and Religious Studies Social Sciences
Language: Russian
Full text
DOI
Keywords: высшее образованиеобразовательная траекторияанализ данныхdata analysisбольшие данныеонлайн-образованиеeducational trajectorybig dataonline educationhigher educationцифровой университетdigital universityЦифровой следdigital footprintsuniversity spaceSmart University“Dark” Universityуниверситетское пространствоУмный университет«Темный» университет
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