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News
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.
October 6, 2026
International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod Brings Together Scientists from Russia and Serbia
The International N5 Symposium ‘Neural Networks and Nonlinearity in Nizhny Novgorod’ was held at the Nizhny Novgorod House of Scientists from September 23 to 26. The event was organised by HSE University–Nizhny Novgorod and the Nizhny Novgorod House of Scientists, with the participation of Sberbank and the Institute of Physics Belgrade. The symposium was held for the second time: the first conference took place in 2025 and attracted considerable interest from the academic community.

 

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Risks and the image of the future in the study of AI technologies prospects

Futures. 2026. Vol. 183. P. 1–22.
Snegirev A., Sychev S.

This study addresses the systemic identification and categorization of risks associated with AI development, arising from tensions between technological evolution and institutional, infrastructural, and economic contexts. Drawing on a constructionist methodology, we interpret technological risks as constitutive elements of expert communities' images of the future. Through in-depth interviews with 100 AI experts, proportionally representing corporate, research, and regulatory segments of the AI innovation ecosystem we identify and code 16 distinct risks. The study operationalizes the Polak matrix to map technological risks along two dimensions: essence (the perception of AI development processes) and influence (the role of professional agency). Applying the matrix, the risks are categorized into four groups: Disappointing AI, AI Winter, Biased AI, and Absolute AI, each exhibiting distinct managerial properties and contributing to the scenario space of AI development. The proposed framework reveals the ambivalent nature of technological risk, distinguishing between causal ambivalence (process vs. environmental attribution) and evaluative ambivalence (varying threat intensity estimates). The authors further demonstrate how the resulting risk matrix can improve strategic planning by projecting risk data onto a modified SWOT framework, offering actionable pathways to navigate the socio-technical complexity of AI governance.

Research target: Computer Science Economics and Management
Language: English
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Text on another site
Keywords: risktechnological developmentSocial construct artificial intelligencePolak matrixSWOT
Publication based on the results of:
Trends and factors of sustainable science and technology development (2025)
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