A New Tool Designed to Assess AI Ethics in Medicine Developed at HSE University
A team of researchers at the HSE AI Research Centre has created an index to evaluate the ethical standards of artificial intelligence (AI) systems used in medicine. This tool is designed to minimise potential risks and promote safer development and implementation of AI technologies in medical practice.
The rapid expansion of AI technologies across various areas of life, including medicine, has brought about new risks that go beyond information security, economic, or social concerns and extend into ethical challenges as well. Current standards and regulatory frameworks do not adequately address ethical considerations, making it essential to develop a specialised tool for evaluating AI systems from an ethical standpoint.
The team behind the 'Ethical Review in the Field of AI' project at the HSE AI Research Centre carried out comprehensive work in two phases: theoretical and practical. First, the researchers conducted a thorough review of numerous domestic and international documents to identify and define the key principles of professional medical ethics: autonomy, beneficence, justice, non-maleficence, and due care. Subsequently, a qualitative field study using in-depth semi-structured interviews was conducted among medical professionals and AI developers, which allowed the team to refine and actualise the initial principles and to add new ones.
Based on the study results, the researchers developed the Index of AI Systems Ethics in Medicine —a chatbot that allows for 24/7 self-assessment and provides instant feedback from the index developers. The assessment methodology includes a test with closed-ended questions designed to evaluate the awareness of both medical AI developers and AI system operators regarding the ethical risks associated with the development, implementation, and use of AI systems for medical purposes.
The new methodology has been piloted and endorsed by a number of leading IT companies, such as MeDiCase and Globus IT, specialising in the development of AI solutions for medicine. Additionally, it has been approved by the Commission for the Implementation of the AI Ethics Code and the Moscow City Scientific Society of General Practitioners.
'The development of this index is a significant step toward ensuring ethical use of AI in medicine. We hope that the solution we have developed will be valuable to the medical community, which, as our research shows, is concerned about the potential negative ethical consequences of the widespread integration of AI into medical practice,' according to Anastasia Ugleva, Project Head, Professor, Deputy Director of the Centre for Transfer and Management of Socio-Economic Information at HSE University.
The index is expected to be sought after by ethics committees, the forensic medical expert community, and other organisations responsible for evaluating and certifying AI. It will also support the shift from the principle of sole responsibility of a medical professional to a model of shared responsibility among all participants in the process. The introduction of this index will help make AI usage safer and more aligned with high ethical standards.
The methodology guidelines The Index of AI Systems Ethics in Medicine are registered at HSE University as intellectual property (IP), No.8.0176-2023.
See also:
Scientists Test Asymmetry Between Matter and Antimatter
An international team, including scientists from HSE University, has collected and analysed data from dozens of experiments on charm mixing—the process in which an unstable charm meson oscillates between its particle and antiparticle states. These oscillations were observed only four times per thousand decays, fully consistent with the predictions of the Standard Model. This indicates that no signs of new physics have yet been detected in these processes, and if unknown particles do exist, they are likely too heavy to be observed with current equipment. The paper has been published in Physical Review D.
HSE Scientists Reveal What Drives Public Trust in Science
Researchers at HSE ISSEK have analysed the level of trust in scientific knowledge in Russian society and the factors shaping attitudes and perceptions. It was found that trust in science depends more on everyday experience, social expectations, and the perceived promises of science than on objective knowledge. The article has been published in Universe of Russia.
Scientists Uncover Why Consumers Are Reluctant to Pay for Sugar-Free Products
Researchers at the HSE Institute for Cognitive Neuroscience have investigated how 'sugar-free' labelling affects consumers’ willingness to pay for such products. It was found that the label has little impact on the products’ appeal due to a trade-off between sweetness and healthiness: on the one hand, the label can deter consumers by implying an inferior taste, while on the other, it signals potential health benefits. The study findings have been published in Frontiers in Nutrition.
Final of International Yandex–HSE Olympiad in AI and Data Analysis Held at HSE University
Yandex Education and the HSE Faculty of Computer Science have announced the results of the international AIDAO (Artificial Intelligence and Data Analysis Olympiad) competition. Students from 14 countries took part. For the second year in a row, first place went to the team AI Capybara, which developed the most accurate AI model for an autonomous vehicle vision system.
AI Lingua Included in Compilation of Best International AI Practices in Higher Education
HSE University has been acknowledged internationally for its pioneering efforts in integrating artificial intelligence into higher education. The AI Lingua Neural Network developed at HSE was included in the renowned international collection ‘The Global Development of AI-Empowered Higher Education: Beyond the Horizon.’ The compilation was prepared by the Institute of Education (IOE) of Tsinghua University with the support of the Ministry of Education of the People's Republic of China and a global advisory committee, which included experts from Oxford, UCL, Sorbonne, Stanford, and other leading academic centres.
Technological Breakthrough: Research by AI and Digital Science Institute Recognised at AI Journey 2025
Researchers from the AI and Digital Science Institute (part of the HSE Faculty of Computer Science) presented cutting-edge AI studies, noted for their scientific novelty and practical relevance, at the AI Journey 2025 International Conference. A research project by Maxim Rakhuba, Head of the Laboratory for Matrix and Tensor Methods in Machine Learning, received the AI Leaders 2025 award. Aibek Alanov, Head of the Centre of Deep Learning and Bayesian Methods, was among the finalists.
HSE Psycholinguists Launch Digital Tool to Spot Dyslexia in Children
Specialists from HSE University's Centre for Language and Brain have introduced LexiMetr, a new digital tool for diagnosing dyslexia in primary school students. This is the first standardised application in Russia that enables fast and reliable assessment of children’s reading skills to identify dyslexia or the risk of developing it. The application is available on the RuStore platform and runs on Android tablets.
HSE University to Join Physical AI Garage Project by Yandex
Yandex is collaborating with leading Russian universities to launch a new educational programme called Physical AI Garage. This initiative unites five universities—HSE University, ITMO, MIPT, MAI, and MEPhI—to train future professionals in physical artificial intelligence by tackling real-world industrial challenges. The programme is free, and participants will receive scholarships.
Physicists Propose New Mechanism to Enhance Superconductivity with 'Quantum Glue'
A team of researchers, including scientists from HSE MIEM, has demonstrated that defects in a material can enhance, rather than hinder, superconductivity. This occurs through interaction between defective and cleaner regions, which creates a 'quantum glue'—a uniform component that binds distinct superconducting regions into a single network. Calculations confirm that this mechanism could aid in developing superconductors that operate at higher temperatures. The study has been published in Communications Physics.
Neural Network Trained to Predict Crises in Russian Stock Market
Economists from HSE University have developed a neural network model that can predict the onset of a short-term stock market crisis with over 83% accuracy, one day in advance. The model performs well even on complex, imbalanced data and incorporates not only economic indicators but also investor sentiment. The paper by Tamara Teplova, Maksim Fayzulin, and Aleksei Kurkin from the Centre for Financial Research and Data Analytics at the HSE Faculty of Economic Sciences has been published in Socio-Economic Planning Sciences.