Foresight and STI Governance

A Universal Core and National Specificity: A Typology of Technological Priorities in National Strategies

Dina Malekova — 2026-08-04

Technological development dynamics underscore the relevance of a comparative analysis of national priorities in science and innovation. Thsi article identifies and typologizes promising technologies enshrined in the development strategies of 19 countries: the technological leaders—the United States, Japan, Germany, the United Kingdom, South Korea, Canada, Australia, Spain, and Italy — and the countries of the Global South — Brazil, India, China, South Africa, the United Arab Emirates, Egypt, Ethiopia, Indonesia, Iran, and Saudi Arabia. It tests two hypotheses: whether a universal “core” of promising technologies exists and whether stable groups of countries with similar innovation profiles emerge. The empirical base comprises two to five strategic documents for each country, dating from 2018 to 2026. The analysis employs frequency, semantic, and content analysis; the calculation of the Revealed Comparative Advantage (RCA) index across 12 thematic sections and 86 subsections; and k-means clustering. The analysis confirmed both hypotheses: despite a shared core of priorities, countries differ in their modes of strategic concentration, forming several types of profiles. Although the study is limited to declared rather than actual outcomes, its contribution lies in the systematic comparison of the strategies of advanced economies and those of the Global South, the identification of specialization models, and the development of conceptual approaches to assessing technological sovereignty in a multipolar world.

Beyond Replacement: How AI Reconfigures Academic Roles

Amir Ghorbani — 2026-08-04

The literature examining the impact of artificial intelligence (AI) on higher education often boils down to the question of whether AI will replace teachers. This study examines the issue more broadly — through the lens of the diverse nature of academic tasks. A multidimensional analysis is conducted to show how academic work is being redistributed among tasks that AI can replace, augment, or cannot meaningfully displace. This study uses qualitative content analysis on a purposive corpus of 46 documents, including scientific papers, reports, policy and practitioner texts, and higher education commentary published between 2020 and 2026. A 3×3 analytical matrix was developed, reflecting the degree of distribution of functions between humans and AI ("Replace," "Augment," or "Human-dominant") across three basic dimensions of academic activity (teaching, research, and socio-technical work). The findings show that AI is strongest in codifiable and routine tasks such as basic educational content generation, objective grading, literature processing, drafting, and administrative support. By contrast, tasks involving judgment, ethics, interpretation, mentoring, relationship-building, assessment design, governance, and public trust remain human-dominant. The research concludes that AI does not eliminate academic work; it simply reorders it, shifting value from content transmission toward learning design, interpretive expertise, and institutional stewardship.

From Accumulation to Conversion: Intellectual Capital and Economic Response

Gulimzhan Suleimenova — 2026-08-04

The transition to a knowledge-based economy increasingly depends upon the accumulation and effective use of regional intellectual capital (RIC). This challenge is particularly acute for resource-oriented countries seeking to reduce their dependence on natural resources and achieve sustainable long-term development. However, the immediate economic effects of RIC remain unclear. This paper examines whether regions that accumulate RIC are able to convert it into short-term economic dynamics and whether such an accumulation creates the foundations for long-term regional transformation. Using panel data for regions of Kazakhstan, the empirical strategy distinguishes between two complementary dimensions of RIC’s impact. The structural effect of RIC is estimated using a two-way fixed-effects panel model, while the short-term conversion effect is operationalized through a novel indicator - Regional Intellectual Capital Conversion Elasticity (RICCE_Elasticity). The results show that RIC functions primarily as an accumulated institutional resource whose development impact depends not only on its stock, but also on regional mechanisms that enable its economic conversion. By distinguishing between accumulation and conversion effects, this paper contributes to the literature on intellectual capital and regional development.

Looking Within the Ivory Tower: How Research Groups’ Characteristics Affect Industrial Innovation

Michele Kremer Sott — 2026-08-31

Numerous studies have examined innovative partnerships between universities and industrial companies; however, universities are typically treated as a monolithic unit of analysis. Shifting the focus to individual academic research groups (RGs) provides a better understanding of the complexity and heterogeneity of such interactions. This article aims to analyze the interactions between Brazilian industrial firms and university research groups to understand how specific characteristics of these micro-level units influence firms' innovative outcomes. The research utilizes data from the Brazilian national census of research groups (DGP-CNPq) combined with a survey of industrial firms that collaborated with these groups. The study develops five econometric models to measure the effects of firm and research group characteristics on the dimensions of innovation performance, such as technological and business capabilities, and product and process innovation. The results indicate that research group characteristics do not directly affect a firm’s innovation performance. Instead, the presence of a robust knowledge infrastructure and involvement in R&D departments are the primary determinants of enhanced technological and business capabilities in collaborative agreements. Furthermore, while applied science is a significant predictor for product innovation, process innovation is primarily driven by the firm's own technological intensity and the university’s knowledge infrastructure. This study is among the first to provide a granular, micro-level analysis of how research group characteristics — rather than university-wide traits — shape the tangible benefits firms derive from collaboration, specifically within the context of an emerging economy.

Grafting Innovation onto Ancient Roots: Technology, Autonomy, and Traditional Knowledge in Agricultural and Forest Livelihoods

Babu George — 2026-08-04

Digital technologies, from precision agriculture and drone surveillance to blockchain supply chains and AI-driven agronomic advisors, are remaking traditional agricultural and forest-based livelihoods across the developing world. Proponents cast these tools as pathways to efficiency, market access, and ecological resilience. Critics counter that they deepen dependency on external corporations, erode indigenous knowledge systems, and reproduce colonial patterns of value extraction under new digital labels. This paper argues that neither framing captures the full picture. Drawing on political ecology, science and technology studies, indigenous knowledge frameworks, and the ethics of care, the paper examines how context, governance, and power determine whether a given technology strengthens or hollows out rural communities. It traces structural parallels between today’s digital agriculture push and the Green Revolution of the mid-twentieth century, showing how similar promises of productivity gains produced similar distributions of winners and losers. The analysis identifies several underexplored risks: algorithmic monoculture (where uniform AI recommendations reduce crop diversity at landscape scale), infrastructure fragility (where platform abandonment strands dependent users), and epistemic displacement (where app-based decision-making supplants observational skills that took generations to develop). The paper proposes symbiotic modernization as an alternative framework, one that measures technological success by whether it grafts onto existing knowledge systems rather than uprooting them. Practical pathways include open-source hardware and software, community data sovereignty protocols, technology intermediaries embedded in local institutions, and adaptive management cycles that treat deployment as an ongoing experiment rather than a finished rollout. The paper concludes that connectivity and autonomy can coexist, but only when communities set the terms of engagement.

How Digital Technologies Penetrated the Lives of Russians: A Retrospective Analysis

Vadim Radaev — 2026-08-04

The study reveals the history of the emergence of user digital technologies and their dissemination among the Russian population. A chronology of key events with specific dates has been constructed from open internet sources since the 1990s. Based on representative quantitative data, the research examines the achievement of broad, mass, and universal involvement of Russians in the most important digital technologies. The primary source for analyzing population involvement in digital technologies is data collected from the Russian Longitudinal Monitoring Survey of the National Research University Higher School of Economics (RLMS-HSE). The combined dataset for 2000–2024 includes 337,406 respondents aged 16 and older, comprising 42% men and 58% women. The results cover the growth in population involvement with the internet and electronic devices (personal computers, mobile phones, and smartphones), social network usage and messaging apps, participation in video games, and interactions with AI-equipped chatbots. Main findings are summarized in chronological tables. Analysis of diverse empirical data enables characterization of the main chronological patterns of dissemination for different digital technologies and identification of several technological waves reflecting the growing involvement of Russian users in these technologies.

The Digital Transformation of Public Governance: A Foresight Study for the Water Sector

Majdi Argoubi — 2026-09-03

The digital transformation of public administration requires more complex approaches than previously thought. There are no one-size-fits-all solutions, as each country has a unique resource base, natural conditions, historical context, and capacity to adopt technologies and accelerate development. A key role is also played by a multidimensional analysis of the national governance system’s potential for profound and systemic transformation, an ambidextrous approach to current and strategic tasks, and the search for relevant examples that have proven their viability under similar conditions. This article presents an expanded model for the digital transformation of public administration in countries with a catch-up development model. It provides a theoretical rationale and approaches for the transition to high-tech cloud platforms. The limitations, risks, and potential of the digital transition are illustrated using the example of countries in the Middle East and North Africa (Saudi Arabia, the UAE, Tunisia, Morocco, Egypt, etc.). Based on the foresight process, criteria for prioritizing management tasks have been developed, defining review procedures, measurement scales, and rules for selecting weightings; as a result, the presented model becomes structurally reproducible and can be applied in various management contexts. Its potential applications are illustrated using the water sectors of Tunisia and Morocco as examples. The paper explains why, despite the maturity of these technologies and their proven effectiveness in a number of leading countries, they cannot be applied in countries where the conditions are not yet ready for such a transition. It offers recommendations on which approaches can facilitate the digital transition in public administration in developing regions and provide a foundation for reaching a new level of opportunities.

Foresight for Anticipatory Water Resources Governance

Oleg Rosenthal — 2026-08-18

A conceptual framework is proposed for analyzing and forecasting catastrophic regime shifts in water resource availability and quality, synthesizing catastrophe theory, contemporary understandings of critical transitions in socio-ecological systems, and the methodological tools of foresight. It is shown that ignoring nonlinear dynamics, threshold effects, and hysteresis can lead to a systematic underestimation of strategic threats to the energy sector, agriculture, industry, and urban infrastructure. The objective necessity of transitioning from a reactive model of water resources management to a proactive one, integrated into the long-term agenda of sustainable development and national security, is demonstrated. An integrated approach is proposed that combines early warning signals, scenario analysis, economic instruments, and multilevel basin management. Based on an analysis of the Russian context (including a critical reassessment of the 2014–2015 scenarios developed by the Institute for Strategic and Economic Studies at the National Research University Higher School of Economics), strategic recommendations for state water policy are formulated.

Strategic dialogue is a key methodological element of the proposed approach, viewed as one of the prerequisites for effective scenario planning in the public water sector. In contrast to the traditional sequence of “scenarios → discussion,” this study justifies the reverse sequence: strategic dialogue is used to align objectives, identify institutional barriers, overcome bureaucratic inertia, and establish a common language among stakeholders in the water management sector. Only after this are scenarios developed—not as abstract forecasts, but as jointly agreed-upon boundaries of a plausible future—which increases the likelihood of their actual use in adjusting public water policy.