White Papers of AI Conformity Assessment Published on HSE University Website

The Russian Technical Committee for the Standardization of ‘Artificial intelligence’ (TC164), together with the Chamber for Indo Russo Technology Collaboration and the RUSSOFT Non-profit Partnership of Software Developers, has published new White Papers related to Artificial Intelligence Conformity Assessment. It reflects the approaches to the standardization and ethical regulation of AI technologies in two pilot industries — healthcare and agriculture.
The Russian Technical Committee on Standardization ‘Artificial intelligence’ (TC 164) was established by order of Rosstandart in 2019. It regulates cooperation between interested organisations and the government in carrying out work on national, interstate and international standardization. Sergey Garbuk, Director for Research Projects at HSE University, chairs the committee.
Work on the White Papers project started in 2023 after the signing of a Memorandum of Understanding between CIRTC, TC164 and RUSSOFT.
The published analytical report consists of five sections. The first one is dedicated to the goals agreed upon by two states, Russia and India, in the field of conformity assessment of AI technologies, and more specifically, the conformity assessment of AI in healthcare and agriculture. The second section contains a list of AI tasks in both industries. The third section lists the existing AI solutions in the Russian and Indian markets in pilot industries. The fourth section highlights relevant national and international standards. The last section is devoted to approaches to the ethical regulation of artificial intelligence agreed upon by the two countries, as well as international approaches in this area.
The authors of the White Paper are Indian and Russian experts, including scientists from HSE University.
As part of the pilot project, the parties plan to develop quality assessment metrics for AI technologies participating in the pilot experiment and the quality requirements for applied AI technologies, including comparison with a human operator. The results presume unified standardization documents for Russia and India, which establish requirements for testing particular applied AI technologies in the field of healthcare and agriculture.
The first results of Russian-Indian cooperation in the field of standardization and conformity assessment of AI technologies will be presented at the summit of the heads of national standardization bodies of the BRICS member states, which Russia will be chairing in summer 2024.
After completing the pilot experiment, the researchers plan to create a joint laboratory for AI testing, as well as work on promoting testing methods to the level of international organisations for standardization (ISO/IEC, ITU).
Director for Research Projects at HSE University, Chairman of TC 164
We can overcome barriers associated with the use of artificial intelligence in areas where an incorrect decision can lead to threats to human health and life, and significant environmental and economic damage, through the standardization of requirements for testing methods of responsible intelligent systems, as well as through the objective confirmation of compliance of systems with established requirements in the field of functionality and safety.
Sergey Garbuk
See also:
AI Users Earn Up to 41.8% More Than Non-Users
Research conducted by economists at HSE University has revealed a significant correlation between the regular use of GenAI in the workplace and higher pay among Russian employees. The study found that individuals who frequently use GenAI in their professional activities earn notably more than those who reject these new tools or resort to them occasionally. The salary premium for highly qualified specialists reaches 41.8%. The article was published in the Voprosy Ekonomiki journal.
AI Robot for Environmental Recognition Tested at HSE University
Engineers and researchers at the HSE Institute for Robotics Systems have successfully run the first tests of an AI-powered environmental recognition model deployed on a robot dog. The robot navigated around the HSE Pokrovka building and Pokrovsky Bulvar, analysing the surrounding environment to identify its location.
Algebra, Geometry, and AI: Russian and Vietnamese Mathematicians Discuss Current Research
A delegation of scientists from Hanoi visited the HSE Faculty of Computer Science and then took part in a Russian-Vietnamese conference in St Petersburg. The events were part of the three-year project ‘Flexibility and Computational Methods.’ Over the course of the project, the researchers have prepared joint publications and obtained new mathematical results.
Scientific Expedition to Hainan: HSE Scientists Organise Conference on Statistical AI in China
The Statistical AI Conference was held in Sanya, Hainan Island, China, from 24 to 28 August 2026. The international event brought together leading experts in statistics, machine learning, and applied AI. Alexey Naumov, Director of the AI and Digital Science Institute at the HSE Faculty of Computer Science, and Sergey Samsonov, Head of the International Laboratory of Stochastic Algorithms and High-Dimensional Inference, were among the conference organisers.
How to Assess Students’ Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.
Researchers Assess Contributions of BRICS Countries to Leading ML/AI Conferences
The HSE Scientometrics Centre analysed more than 104,000 papers published between 2020 and 2025 and presented at ten top-level A* conferences ranked by ICORE 2026. The researchers examined the contributions of Brazil, Russia, India, China and South Africa. Together, these countries accounted for around 40,800 publications, or 39.2% of the total. However, the distribution is highly uneven, and a shared BRICS research space has yet to emerge.
Laboratory of Future Networks: HSE Telecommunications Research Institute Develops 5G/6G Research Testbed
The 5G/6G testbed at the HSE Telecommunications Research Institute is becoming a research platform, an educational laboratory, and a foundation for developing new software components for future networks. It makes it possible not only to observe how a mobile network operates, but also to change its operating conditions and measure the results: data-transmission speed, latency, errors, radio-resource utilisation, and other parameters. Based on the testbed, researchers plan to develop MIMO, O-RAN, xApp, and IAB technologies, as well as experiment with artificial intelligence.
Hybrid Intelligence: Competencies in the Age of AI Discussed at Technoprom-2026
Artificial intelligence is not creating new professions, but rather transforming the nature of existing ones. This was the conclusion reached by participants in the panel session ‘Hybrid Intelligence: Digital and Human Drivers of Development,’ organised by the Institute for Statistical Studies and Economics of Knowledge (ISSEK) at HSE University as part of the 13th International Forum of Technological Development (Technoprom-2026). The experts discussed how the nature of work is changing, which skills are becoming increasingly sought after, and what prevents companies from fully capitalising on new technologies.
Researchers Rank Recommendation Algorithms Using Sports Tournament Model
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed an approach for selecting recommendation algorithms more effectively. Their approach uses pairwise comparisons of algorithms to create a tournament table, with the overall ranking based on their performance across all datasets in the tournament. This can reduce the number of algorithms that need to be tested when developing new services, saving both time and money. The study was presented at the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2026).


