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  • Почему нейросети иногда мешают нам меняться? Феномен ИИ-потакания как искусственная забота: разработка и психометрическая проверка Шкалы идиотского сочувствия
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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Почему нейросети иногда мешают нам меняться? Феномен ИИ-потакания как искусственная забота: разработка и психометрическая проверка Шкалы идиотского сочувствия

Экология человека. 2026.
Maksimenko A.
In press

The rapid proliferation of generative neural networks, increasingly used for emotional support and personal advice, raises the problem of algorithmic indulgence – the systematic avoidance of confrontation by neural networks, the substitution of constructive feedback with consolation, and the prioritization of the user's immediate comfort over their long-term development. This phenomenon, rooted in the Buddhist concept of "idiot compassion", acquires new risks in the context of AI interaction, associated with the "compassion illusion". The aim of the study was to develop and psychometrically validate the Idiot Compassion Scale (ICS) – a tool for measuring users' perception of AI-indulgence patterns in neural networks. A sample of 522 respondents (mean age 39.0 years, 55.9% female) underwent factor analysis, reliability assessment, and correlation analysis. Factor analysis (principal component analysis with Varimax rotation) revealed a two-factor structure: "Avoidance of Confrontation and Indulgence" (α = 0.812) and "Prioritize Emotional Comfort over Honesty" (α = 0.764). Significant positive correlations were found between both subscales and medical mistrust, intolerance of uncertainty, and satisfaction with AI use, as well as negative correlations with frequency of AI use and age. The ICS can be used to assess the risks of emotional dependence on AI in vulnerable groups of users (with high levels of intolerance of uncertainty, avoidant attachment style, medical mistrust), as well as for empirical evaluation of the quality of user interaction with neural networks in research and clinical contexts.

Research target: Psychology Health Studies Computer Science
Language: Russian
Keywords: neural networksпсихометрическая проверканейросетиразработка шкалыScale development artificial intelligencePsychometric validation искусственный интеллектidiot compassionAI-indulgenceavoidance of confrontationemotional comfortидиотское сочувствиеИИ-потаканиеизбегание конфронтацииэмоциональный комфорт
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