Dear colleagues, partners, friends — all who remember and honor!
On this sacred day — Victory Day over Nazi Germany — we bow to the courage and fortitude of our ancestors. They defended freedom and human dignity. Eternal glory to the heroes who gave us the future!
Today, decades later, history imposes us a new challenge. The ideology of hatred and superiority is raising its head — fascism is once again attempting to unleash deadly unrest. We see this orgy and are doing everything to stop it. We firmly know: good is stronger than evil, truth is immortal, and retribution is inevitable.
We believe and hope: the prison of greed and stupidity will shamefully collapse, just as the Third Reich collapsed. We will destroy the neo-Nazi scum, just as our ancestors put an end to the brown plague. We will achieve another Great Victory — over hatred and lies.
Happy holiday! Happy day when memory becomes a weapon, and truth a banner. May our new victory be just as brilliant, and may the peace won by our ancestors return to Earth once again!
Glory to the heroes of the past! Glory to the heroes of the present! For Victory!
IIS leaders paid a working visit to Kuban State University
From April 24 to 29, 2026, Yuri Hohlov, Chairman of the Board of Directors of the Institute f of the Information Society, and Tatiana Ershova, a member of the IIS Board of Directors and Editor-in-Chief of the scientific and analytical journal “Information Society,” visited Krasnodar at the invitation of Kuban State University.
On April 27, Yuri Hohlov gave an open lecture, “Standards in Artificial Intelligence: From Creation to Impact Through Use.”
“Standards are the quintessence of accumulated knowledge and best practices. They represent a consensus among key players on where the industry is heading and how to apply technology for socioeconomic development,” he noted in his speech.
The lecturer explained that a modern AI system is not simply software code, but a complex ecosystem encompassing data collection, model creation, validation, and operation. Particular attention was paid to the diverse perspectives of stakeholders—from data providers and developers to end users and regulators.
The lecture addressed the pressing issue of harmonizing the international and national standardization landscapes. He described the dynamics of synchronizing Russian AI standards with international ones. While at the end of 2021, the average lag behind international standards was 26 months, and coverage was only 10%, by the end of 2025, coverage had already increased to levels that allow us to speak of a harmonized regulatory framework.
The lecture presented a conceptual model of digital development, in which artificial intelligence, along with big data and the Internet of Things, is classified as “third wave” technologies. The impact of digital solutions on the economy and society was emphasized, where standards are one of the critical factors ensuring interoperability, trust, and security of technologies.
On April 28, T. Ershova gave an open lecture on “How to Prepare a Scientific Article to Avoid Rejection.”
She explained why up to 50% of articles are rejected even before peer review and specifically discussed the correct and categorically unacceptable uses of artificial intelligence in scientific writing.
She detailed the structure of an ideal article—from the abstract to the conclusion. Particular attention was paid to the fact that the work should provide a clear answer to the question, “What has been done for the first time?”
The section on artificial intelligence generated the greatest interest from the audience.
“AI is a fast secretary and editor, but not an author. Only humans should think, be responsible for their conclusions, and sign their texts,” the lecturer noted.
She also discussed how neural networks actually help researchers and save their time. AI is excellent at checking grammar, improving headings, turning chaotic drafts into coherent text, and explaining complex passages.
The lecture concluded with a practical checklist for final proofreading before submitting material to the editor and a discussion of professional ethics.
On April 29, Yuri Hohlov gave an open lecture for students of the Faculty of Computer Technology and Applied Mathematics on “Big Data Standards for Machine Learning and Analytics.”
The event focused on the systematization of international and national standards governing the work with big data at all stages of its lifecycle.
The lecture covered in detail:
key stages in the development of Big Data technologies and associated standardization
basic terms and concepts of the topic
the data lifecycle in artificial intelligence systems
data quality metrics for analytics and machine learning
Big Data reference architecture
Particular attention was paid to the harmonization of Russian big data standards with international ones.
In addition to lectures, the IIS leaders’ visit to Krasnodar included working meetings with KubSU Rector Mikhail Astapov, Dean of the Faculty of Computer Technology and Applied Mathematics Alexander Kolotiy, Head of the Department of Data Analysis and Artificial Intelligence Anna Kovalenko, Associate Professor of the Department of Information Technologies Sergei Sinitsa and the Director of the Regional Computer Communications Center Boris Levitsky.
KubSU press releases were used in the preparation of this material.
The articles in this issue cover, among others, the following topics:
Platform employment: convenient freelancing or a “Gray Zone” for IT professionals? Quantum computing for oil and gas: economic benefits of up to 500% – fiction or reality? AI through students’ eyes of: smart assistant, future competitor, or danger? Large Language Models: will humanities disappear or expand their role? Terminator and the Matrix: how does science fiction shape our perception of time and technology? Ethics and law: can algorithms be “forced” to be transparent? Sanctions as a growth driver: why do most Russian IT companies see new opportunities in challenges? Developing the Information Society in Moscow: how did the Russian capital move from piecemeal measures to systemic policy?
In her address to readers “2025: Summa summarum”, the journal’s editor-in-chief Tatiana Ershova wrote:
Back in 1997, the Bulletin of the Russian Society for Informatics and Computer Engineering, which by then was in its eighth year of publication, was renamed “Information Society.” And there was a reason for this: in 1994, the world learned of the famous “Bangemann Report”—a political manifesto that emphasized the transformative role of information and communication technologies and had a clear socioeconomic focus. This document proved to be truly momentous: it inspired not only politicians but also countless enthusiasts in many countries, including Russia. Many believed in the positive potential and power of ICT, which could and should be harnessed for the benefit of people.
Before this, in the 1950s–1980s, people mostly talked about “mechanization and automation.”
Since the 1980s, they had shifted to “informatization.” Since the 1990s, the term “digitalization” has been widely used. But at the turn of the millennium, the “information society” emerged on the global political agenda, with a dedicated summit held in two stages in 2003 and 2005. Even before this event, a concept for the development of the information society was approved in Moscow, and in 2008, we received the Strategy for the Development of the Information Society. In 2011, a state program, “Information Society,” was developed to implement it, covering the period up to 2030. However, it evolved into a departmental program of the Ministry of Communications/Ministry of Digital Development, and the lion’s share of budget funds went toward creating state information systems that address the needs of government officials and, only indirectly, citizens and businesses.
Since the early 2010s, amid the rapid development of cloud services, artificial intelligence, big data, and the Internet of Things, “digital transformation” has come to the forefront. This implies a profound rethinking of strategies, processes, business models, and organizational cultures under the influence of digital technologies. In our country, this term was formally enshrined in the national program “Digital Economy of the Russian Federation” in 2017. The activities surrounding this program were more focused on economics, perhaps even corporate development, so it all had a strong capitalist feel.
At the same time, objective processes have radically changed the nature of work, trust and security models, forms of education, and even ethics. We are not simply witnessing the introduction of new tools—digital platforms, large language models, and quantum algorithms are beginning to reshape the very fabric of society. What happens to individuals and society when algorithms begin to generate content, platforms begin to manage employment, legal imperatives begin to catch up with technology, and the Industrial Internet of Things begins to connect millions of devices? The answer is paradoxical. The smarter machines become, the more clearly unique human qualities emerge. This is precisely the theme of our authors’ articles, which demonstrate that digital transformation can only succeed to the extent that we learn to ask the right questions. And the most important of these is: how can we preserve humanity at the center of a world that is becoming increasingly artificial? The answers are in our hands.
Yuri Hohlov spoke at the Data Fusion’26 conference
On April 8, 2026, a case study session titled “The Economics of AI: Does It Add Up or Not?” was held as part of the Data Fusion conference on data analysis and artificial intelligence technologies.
Undoubtedly, AI has the potential to dramatically reduce labor costs and help save time. However, the question of converting this time into real money remains a matter of economic art. The obvious cost reduction through staff reductions often fails to recoup even the company’s investment in developing and owning professional AI. Therefore, the focus is on AI application models that transform the labor process itself and allow for quantifiable impact assessments, taking into account specific costs and risks, such as those associated with AI errors.
The session discussed:
Successful, non-trivial cases of turning “time into money” through AI in companies.
The economic aspects of implementing AI in highly specialized production processes with a significant share of labor.
Quantitative assessment and forecasting of the economic effects of AI implementation: approaches, models, and results. Do modern economic theories work well with AI?
“Reconnaissance in force”: how to assess the economics of ai in the early stages of development and implementation? What signs can be considered as harbingers of inefficiency?
Practical aspects of developing the cost of AI ownership: how to consider the risks associated with inevitable errors? insurance for AI-related risks.
Profound Transformation of the AI economics in industries: how will the costs of individual work be redistributed once all market participants successfully implement AI? Could this lead to a situation where implementation costs won’t pay off? What should we do: be first to implement or wait for the market to restructure?
The session was moderated by Alexander Bukhanovsky, ITMO University, Head of the “”Strong AI in Industry” Research Center.
The session program included the following presentations:
Elena Belobrova, Yandex Cloud, Head of ML&AI Business Development AI: Where is the Money, and Where is an Expensive Experiment
Ekaterina Kanunnikova, VK Tech, Director of Product, Data Services Before and After the Model: How to Calculate an AI Project Fairly
Yuri Hohlov, Institute of the Information Society, Chairman of the Board of Directors, full member of the Russian Engineering Academy The Economics of AI: From Creation to Impact through Use
Dmitry Ruzanov, Alfa-Bank, Director of the Model Development Department How AI Turns Time into Money: A Model Approach and New Pricing at the Bank
Yuri Borodachev, National Research Nuclear University MEPhI, Deputy Director of the Artificial Intelligence Center The Economics of AI: The Real Sector. Is it Aligned or Not? The Problems of Expectations and Effects from Hardware Consumers
Yuri Hohlov spoke at the IT&MM 2026 plenary session
The 15th A. I. Kitov International Scientific and Practical Conference “Information Technology and Mathematical Methods in Economics and Management (IT&MM)” is being held at Plekhanov Russian University of Economics on March 26-27, 2026. The conference is organized by the Institute of Digital Economy and Information Technology and the Informatics Department of the Plekhanov Russian University of Economics.
Leading scientists, faculty, and students from Plekhanov Russian University of Economics, the Federal Research Center “Informatics and Control” of the Russian Academy of Sciences, the Institute of Control Sciences of the Russian Academy of Sciences, the V. M. Glushkov Institute of Cybernetics of the National Academy of Sciences of Ukraine, the Higher School of Economics, Lomonosov Moscow State University, MPEI, MAI, MIPT, the Presidential Academy of National Economy and Public Administration, the Financial University under the Government of the Russian Federation, and other leading universities and research centers from Russia and several other countries are participating in the conference.
Participants discuss current fundamental problems in computer science and applied mathematics, particularly in such important scientific areas as intellectual analytical methods in managing economic and social systems; information systems for making management decisions; mathematical methods for analyzing and optimizing the use of economic information; and more.
The conference agenda includes a plenary session and six sections.
The agenda for the plenary session, which took place on March 26, 2026, included the following presentations.
Dmitry Aleksandrovich Shtykhno, Vice-Rector of the Plekhanov Russian University of Economics. Plekhanov Opening of the ITiMM-2026 Conference
Igor Anatolyevich Sokolov, Dean of the Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, full member of the Russian Academy of Sciences Artificial Intelligence Technologies in Scientific Research
Yuri Evgenievich Hohlov, Chairman of the Board of Directors of the Institute for the Development of the Information Society, full member of the Russian Engineering Academy Training Top Specialists in Information Technology: Competency-Role Models and Accelerated Growth
Vladimir Eduardovich Balasanyan, Chairman of the Board of Directors of the Electronic Office Systems Group Andrey Aleksandrovich Pashkov, Chief Software Promotion Specialist of the Electronic Office Systems Group Potential for Ensuring Information Security in Electronic Document Management Systems (EDMS) and Long-Term Document Storage Systems
Vladimir Vasilievich Korenkov, Scientific Director of the Information Technology Laboratory, JINR, Doctor of Engineering, Professor Digital Technologies and Intelligent Analysis in Large-Scale Projects
Alexander Konstantinovich Petrenko, Head of the Programming Technologies Department at the Institute for System Programming of the Russian Academy of Sciences, Professor, Doctor of Physical and Mathematical Sciences Modern Technologies for Developing Trusted Software
Alexander Alexandrovich Lotakov, Leading Analyst at Loginom How to Spend a Budget on Artificial Intelligence and Achieve Nothing
Alexander Oskarovich Gurdus, Chief Specialist at the Federal Research Center for System Programming of the Russian Academy of Sciences, Professor, Doctor of Economics, Candidate of Engineering Sciences Some Aspects of Global Governance in a Single Digital Space of Economic Interaction
More detailed information about the event is available on the ITiMM website.
National standard GOST R 72514-2026, prepared by IIS, has been published
The national standard GOST R 72514 “Artificial Intelligence System Impact Assessment” has been published on the Rosstandart website. The document was developed by the Institute of the Information Society based on its own Russian translation of the international standard ISO/IEC 42005:2025 “Information technology — Artificial intelligence (AI) — AI system impact assessment.” The standard was submitted by Technical Committee for Standardization TC 164 “Artificial Intelligence” and comes into effect on May 1, 2026.
This standard establishes guidelines for organizations conducting impact assessments of artificial intelligence (AI) systems on individuals and social groups that may be affected by the AI system and its foreseeable applications. It specifies how and when to conduct such assessments and at what stages of the AI system’s lifecycle, and also provides guidelines for documenting the impact assessment of an AI system. It establishes how the AI system impact assessment process can be integrated into an organization’s existing artificial intelligence risk management system and AI management system.
This standard is intended for use by any organization developing, providing, or using AI systems.
The standard’s contents are as follows:
1 Scope 2 Normative References 3 Terms and Definitions 4 Abbreviations 5 Development and Implementation of the Artificial Intelligence System Impact Assessment Process 6 Documentation of the Artificial Intelligence System Impact Assessment Appendix A (informative) Guidelines for using this standard in conjunction with GOST R ISO/IEC 42001 Appendix B (informative) Guidelines for using this standard in conjunction with ISO/IEC 23894 Appendix C (informative) Taxonomy of Harms and Benefits Appendix D (informative) Combining the Artificial Intelligence System Impact Assessment with Other Assessments Appendix E (informative) Example of an Artificial Intelligence System Impact Assessment Template Bibliography
National standard GOST R 72515-2026, prepared by Volgograd State University and IIS, has been published
The national standard GOST R 72515, “Transparency Taxonomy of Artificial Intelligence Systems,” has been published on the Rosstandart website. The document was prepared by Volgograd State University and the Institute of the Information Society based on their own Russian translation of the international standard ISO/IEC 12792:2025, “Information technology — Artificial intelligence (AI) — Transparency taxonomy of AI systems.” The standard was submitted by Technical Committee for Standardization TC 164 “Artificial Intelligence” and comes into effect on May 1, 2026.
The objectives of this standard are:
to enhance trust, accountability, and communication among various artificial intelligence (AI) stakeholders, including supply chain partners, customers, users, society, and regulators, by creating a consistent terminology related to the transparency of AI systems
to provide AI stakeholders with information about various transparency elements, outlining their significance and potential limitations for different use cases and target audiences
to provide a basis for developing AI system transparency standards for specific technologies, industries, and geographies
Transparency of AI systems is the ability of stakeholders to obtain adequate information about the system. This information may include information about the system’s functionality, limitations, data, system design, and design decisions. Increased transparency provides relevant stakeholders with information that allows them to better understand how AI systems are developed and used. For example, it allows an AI client (e.g., an AI user) to determine whether the system is suitable for their situation, and it helps an AI auditor assess whether it meets compliance requirements. A standardized transparency taxonomy allows representatives of different professions to better understand each other through the use of common terminology. This, in turn, facilitates a better understanding of AI systems and provides a basis for the development of interoperable and harmonized transparency-related standards.
This standard is intended for use by organizations of all types using any type of AI system.
The standard’s contents are as follows:
1 Scope 2 Normative References 3 Terms and Definitions 4 Abbreviations 5 Overview 6 Stakeholder Needs and Transparency Goals 7 Context Taxonomy 8 System Taxonomy 9 Model Taxonomy 10 Dataset Taxonomy Appendix A (informative): Examples of Stakeholder Roles in Transparency Disclosure Bibliography
The first issue of the Information Society Journal for 2026 is published
The first issue of the Information Society Journal for 2026 is published. The main theme of the issue is Accelerated development of modern technologies. The articles in this issue cover, among others, the following topics:
Virtual reality as an information phenomenon Creating value from data Regulating the data sphere in public administration The phenomenon of “information warfare” National cybersecurity system Algorithms as a subject of communication Evolution of blockchain technology Land resource management technologies Smart technologies in the hospitality industry Digital transformation of the Russian Arctic
In her address to readers “Science for the defense of the Fatherland,” the journal’s editor-in-chief Tatiana Ershova wrote:
This issue of the journal was published during a period when our country celebrates two holidays: Russian Science Day on February 8 and Defender of the Fatherland Day on February 23. The connection between science and defense is especially important now, when we are essentially in a state of a formidable military confrontation with the high-tech West through its Ukrainian testing ground.
As the weekly “Zvezda” rightly points out, in the scientific “trenches,” delay is tantamount to death, so the combat lines of the Special Military Operation have become a testing ground for Russian military technologies and defense research. From the first days of the SMO, our troops were confronted with the realities of network-centric warfare, which is being actively implemented in NATO structures and has thoroughly penetrated the training system of the Ukrainian Armed Forces. It links command posts and endpoints of specific combat units into a single network, and there are ongoing attempts to transform digital and scientific-technical advantages into military superiority. This cannot be allowed to happen, so there is an uncompromising struggle to preempt the enemy’s acquisition of intelligence, its rapid processing, and the transmission of information to alert combat assets and units.
Today, Russian scientists are working in many areas to defend the Fatherland. Let’s name just a few. At the forefront is the development of electronic warfare systems. This method helps neutralize the enemy’s ability to gather intelligence and coordinate its forces and is used to achieve a tactical advantage in both defensive and offensive missions. Another area is the development of unmanned aerial vehicles, which are used for border patrols, detection of potential threats, reconnaissance operations, strikes, and much more. Another key area is the development of nuclear power plants, such as low-power plants and floating power units, which can solve energy shortages.
Scientists, engineers, and researchers are behind technological progress in the military-industrial complex, the modernization of existing weapons, and the creation of new ones. Today, their ranks are being swelled by bright and talented representatives of the younger generation. One of them is Konstantin Titov, an associate professor at Voronezh State University, a PhD candidate in physics and mathematics, and a laureate of the Russian Presidential Prize in Science and Innovation. He noted: “We are essentially developing the technology of the future, meaning we have to analyze trends in the development of modern technologies, determine and make forecasts, and calculate the probabilities of using certain technologies. And then, based on this data, we conduct our analytical and experimental research, develop the technology, test it, and deploy it.” On behalf of the editorial board, I would like to congratulate all scientists working for Russia’s defense on two important holidays and wish them breakthrough achievements in the use of information society technologies to defend the Fatherland.
IIS congratulates partners and colleagues on Defender of the Fatherland Day
Dear colleagues, partners and friends!
Congratulations on a glorious holiday – Defender of the Fatherland Day! May each of us contribute to our victory in the name of the peace and prosperity of Russia!
Congratulations to A. N. Raikov on his 75th anniversary!
The staff of the Institute of the Information Society sincerely congratulates A. N. Raikov, a member of the IIS Supervisory Board, on this glorious anniversary! We wish Alexander Nikolaevich, our loyal friend and comrade for decades, good health, boundless energy, new ideas, and a long life!
