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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.
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.
Language:
Russian
Keywords: neural networksпсихометрическая проверканейросетиразработка шкалыScale development artificial intelligencePsychometric validation искусственный интеллектidiot compassionAI-indulgenceavoidance of confrontationemotional comfortидиотское сочувствиеИИ-потаканиеизбегание конфронтацииэмоциональный комфорт
Joulitov A.K., Lomazova I.A., Proceedings of the Institute for System Programming of the RAS 2026 Vol. 38 No. 4(2) P. 215–224
In process mining, DFG (Directly-Follows Graph) models are popular due to their simplicity and clarity. However, if a process is acyclic but contains concurrent events, standard algorithms for discovering DFG models can generate "fake" cycles that do not actually exist in the event log. These cycles hinder the analysis of information processes, significantly reducing the ...
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Added: September 24, 2026
Festa G., D'Amato A., Palladino R. et al., European Journal of Innovation Management 2026 Vol. 29 No. 3 P. 728–744
Purpose
Artificial intelligence (AI) is vastly impacting the digital transformation of societies, economies, businesses, markets and enterprises, at a very fast pace, mostly after the global success of the generative algorithms. In this respect, this study, with an exploratory intention, aims to provide evidence about the fundamental issues of AI, particularly if generative, when adapted to ...
Added: September 24, 2026
Ivan Bulychev, Savchenko A., AI 2026 Vol. 7 No. 9 Article 380
Recent advances in large language model (LLM) agents have shown promise for autonomous decision-making in recommender systems. However, existing approaches suffer from two fundamental limitations: flat agent memories that conflate different information modalities and prohibitive computational costs that prevent scaling beyond a few hundred users. We propose Hybrid-GraphRAG, a recommender system that integrates hierarchical agent ...
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Added: September 23, 2026
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This study examines how emotional tone shapes user preference in human–large language model (LLM) interaction. Drawing on the Computers as Social Actors framework, we treat conversational AI as a social communicator whose affective cues influence user judgments. Using large-scale pairwise preference data from LMSYS Chatbot Arena, we model emotional tone through the Valence–Arousal–Dominance framework and ...
Added: September 23, 2026
Andrabi U., Wadood E., Ojha S. K. et al., IEEE Access 2026 Vol. 14 P. 103358–103375
The emergence of 5G networks, aimed at accommodating diverse service requirements such as enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communication (URLLC), and massive Machine-Type Communication (mMTC), has presented significant challenges in radio resource management and network slicing. In dynamic heterogeneous network systems, traditional heuristics and mathematical programming methods find it challenging to attain scalable multi-objective ...
Added: September 23, 2026
Paklina S., Parshakov P., Elena Rapoport, Scientometrics 2026 P. 1–26
Generative artificial intelligence has become a routine part of academic writing. While much of the debate has focused on questions of integrity and authorship, less attention has been paid to how AI-assisted writing may affect research evaluation itself. This paper asks a straightforward but important question: does the use of LLMs in academic writing change ...
Added: September 23, 2026
Кузнецова М. П., Klochko O., Современная мировая экономика 2026 Т. 4 № 2 С. 6–25
The article examines the positions of the world’s largest countries in the industrial robotics sector as one of the key areas for the physical artificial intelligence (AI). The aim of the study is to conduct a comparative assessment of the readiness of leading economies to develop physical AI based on an analysis of production, foreign ...
Added: September 23, 2026
Kertesz-Farkas A., Acquaye F. L., Journal of Proteome Research 2026 Vol. 25 P. 3764–3768
Ultimately, most tandem mass spectrometry (MS/MS) proteomics experiments aim to not just detect but also quantify the proteins in a given complex sample. Here, we describe an extension to the Crux MS/MS analysis toolkit to enable label-free quantification of peptides. We demonstrate that Crux’s new quantification command, which is modeled after the algorithms implemented in ...
Added: September 23, 2026
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Added: September 23, 2026
Gorodnicheva Y., Monahhova E., Bekim A. et al., Frontiers in Human Neuroscience 2026 No. 20 Article 1917736
Euphemisms are commonly used in media to soften or obscure the severity of unethical or controversial actions. The present study explored the neural correlates underlying the processing of euphemized vignettes portraying norm violations. We recorded event-related potentials (ERPs) and collected behavioral severity ratings while participants (n = 38) read vignettes describing the same norm-violating events framed with ...
Added: September 23, 2026
Tashkent: -, 2026.
Konferensiya materiallari to‘plamida olimlar, o‘qituvchilar va talabalarning zamonaviy
psixologiya fanining istiqbollari, shaxs psixologiyasi, rivojlanish psixologiyasi, oila psixologiyasi,
ijtimoiy psixologiya va ta’lim psixologiyasi sohasidagi nazariy, tadqiqotchilik hamda amaliy
faoliyati natijalari keltirilgan. Materiallar muallif tahriri asosida chop etilgan. Maqolalarning
mazmuni va ishonchliligi uchun mualliflar javobgardir.
To‘plam mutaxassislar, ilmiy va pedagogik xodimlar, talabalar, shuningdek, barcha
psixologiya fani va sohasiga qiziquvchilar uchun mo‘ljallangan. ...
Added: September 22, 2026
М.: ФНЦ ПМИ, 2026.
Сборник продолжает серию изданий «Экопсихологических исследований», посвященных материалам Российских конференций по экологической психологии. В нем представлены статьи участников 10-й Международной научно-практической конференции по экологической психологии «Экологичность взаимодействий человека с окружающей средой», состоявшейся в Федеральном научном центре психологических и междисциплинарных исследований 7–8 октября 2025 года. Представленные статьи демонстрируют междисциплинарный характер современной экопсихологии и ее интеграцию с ...
Added: September 22, 2026
Ju Y., Matveev M. O., Matveeva E. A. et al., Novosibirsk State Pedagogical University Bulletin 2026 Vol. 16 No. 4 P. 199–222
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Added: September 22, 2026
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Ulyanina O. A., Vikhrova E. N., RUDN Journal of Psychology and Pedagogics 2025 Vol. 22 No. 2 P. 337–360
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This research explores an innovative approach to enhancing the accuracy of detecting small microorganisms in complex microscopic environments. Our study introduces a streamlined, hybrid image pre-processing model specifically designed to address the challenges of identifying diplococci in live microscopy of dynamic samples. By integrating pre-defined filtering techniques with predictive adjustments for optimal applicability, our method ...
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