Publications

• Book

  Abashkin V., Abdrakhmanova G., Demidkina O. V. et al.

  Digital Economy: 2026 : Pocket Data Book

  This pocket data book contains the main indicators reflecting the relevance of digital technologies for enterprises and individuals, the activity of ICT sector enterprises, the infrastructure and personnel of the digital economy.

  The data book includes information of the Russian Federal State Statistics Service (Rosstat), Ministry of Digital Development, Communications and Mass Media of the Russian Federation, European Statistical Office (Eurostat), Organisation for Economic Co-operation and Development (OECD), International Telecommunication Union (ITU), UNESCO, UN Department of Economic and Social Affairs, and results of methodological and analytical studies of the HSE Institute for Statistical Studies and Economics of Knowledge.

  In some cases, the presented data specify those published earlier.

  M.: HSE ISSEK, 2026.

• Article

  Veselitskaya N., Malekova D. K.

  Governance logics and foresight functions: European strategic foresight in contrastive perspective

  Foresight methods are often treated as transferable tools whose selection depends mainly on the object of analysis, the time horizon or the available data. This article argues that such a view is incomplete because foresight methods are embedded in governance settings and perform different institutional functions across them. The article does not claim that the context-dependence of foresight methods is new per se. Rather, it contributes by specifying this context-dependence through the lens of governance logics and by showing how the same foresight methods perform different institutional functions across technocratic, market-managerial, networked and anticipatory governance settings. The purpose of the article is to develop a governance-sensitive framework that links foresight methods to institutional functions in public decision-making. Empirically, the article uses a contrastive case design. The European Union is treated as the focal case of institutionalised strategic foresight in a multi-level governance system, while Japan and South Korea serve as secondary contrastive cases. The design does not seek a fully symmetrical country-by-country comparison. Rather, it uses the Japanese and South Korean cases to contrast the EU trajectory with alternative governance settings in which foresight remains more strongly linked to technocratic priority-setting, developmental planning or data-driven policy adjustment. The analysis combines an exploratory bibliometric mapping of Scopus publications, VOSviewer-based semantic analysis of foresight-method terms, manual validation of 68 publications and qualitative case interpretation. The findings suggest that foresight methods are not institutionally neutral. In technocratic settings, they mainly support expert prioritisation and cognitive opening; in market-managerial settings, strategic positioning and performance alignment; in networked governance, stakeholder alignment and legitimacy building; and in datadriven or anticipatory governance, early warning, resilience monitoring and policy adaptation. The EU case shows the most developed combination of networked and anticipatory functions. Strategic Foresight Reports, ESPAS, the EU-wide Foresight Network, the Better Regulation Toolbox, the European Green Deal, Open Strategic Autonomy and resilience dashboards together indicate that EU strategic foresight should be understood as a networked and anticipatory governance infrastructure rather than as a set of isolated forecasting techniques. The article contributes to European futures research by shifting the discussion of foresight-method selection from universal methodological classifications to the institutional design of future-oriented governance. It also introduces the notion of function-sensitive foresight design as a complement to existing method taxonomies in futures studies.

  European Journal of Futures Research. 2026. Vol. 14.

• Book chapter

  Aleksandrova I., Milshina Y.

  Challenges and Risks to the Inclusion of AI for Environmental Applications

  Artificial intelligence is increasingly becoming a valuable tool in environmental science, providing significant benefits in the processing of high-volume datasets, improving predictive models, and better enabling the efficient monitoring of ecosystems. Its ability to identify patterns, automate tedious tasks, and facilitate data-driven decision-making makes it of extreme value in tackling climate change, biodiversity loss, and resource management. Nevertheless, although it promises much, the use of AI also poses a host of problems and threats.

  This chapter discusses in detail the challenges and risks associated with the use of AI, with a special focus on the ethical implications of its use in environmental contexts. Authors emphasize that ethics should not be seen as a secondary consideration, but rather as a fundamental precondition for sustainable innovation. Within this context, the idea of responsible AI is introduced as a guiding concept that includes the principles of fairness, accountability, inclusivity, and environmental integrity. In addition, the chapter points to explainable AI (XAI) as a feasible and essential strategy for enhancing transparency, interpretability, and trust in AI. By making the functioning of AI systems clearer and accountable, XAI can contribute to risk containment and ensure that AI is done for ecological and social benefit.

  In bk.: Artificial Intelligence Enabled Real Time Environmental Monitoring. Springer, 2026. Ch. 10. P. 199-229.

• Working paper

  Shcherbakov R., Privorotskaya S., Vishnevskiy K.

  The Impact Of The Covid-19 Pandemic On Digital Technology Diffusion

  The present paper looks at the COVID-19 external shock impacts on the diffusion of digital technologies for business continuity including videoconferencing, digital logistic services, telehealth services, e-commerce, online entertainment services and cybersecurity. The study reveals that COVID-driven digital trends differ in terms of character of technological diffusion and its dynamics. Some technological areas; i.e. e-commerce and online entertainment diffused only at the late stages of the pandemic while such specialized solution as telehealth have been more impacted by the short-run external shock. Telehealth-related technologies remain less adopted in practice despite significant growth in academic and professional media discussion.

  Science, Technology and Innovation. WP BRP. Высшая школа экономики, 2021. No. 123.