The Future of Humanoid Robots in the Home Explored at Foresight Session

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The Future of Humanoid Robots in the Home Explored at Foresight Session

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Oct

2026

The Future of Humanoid Robots in the Home Explored at Foresight Session

On October 23–24, HSE University hosted the landmark fifth Fall into ML 2026（https://cs.hse.ru/en/ml2026/） Conference. During the foresight session titled ‘A Humanoid in Your Kitchen: When Will It Happen and What Can Prevent It?’ researchers explored why humanoid robot assistants have not yet become part of our everyday lives, what needs to change for this to happen, and who will be held responsible when such assistants make mistakes.

The session was organised by the Centre for Strategic Analysis and Big Data（https://issek.hse.ru/en/ifora/） of HSE ISSEK（https://issek.hse.ru/en/） and moderated by Mikhail Komarov（https://www.hse.ru/en/staff/mkomarov/）, Chief Research Fellow at the centre and Professor at the Department of Business Informatics（https://gsb.hse.ru/en/bi/） of the HSE Graduate School of Business（https://gsb.hse.ru/en/）, and Vladislav Beshlyaga（https://www.hse.ru/en/org/persons/305060559/）, an expert at the centre.

According to Prof. Komarov, although robotic technology is widely discussed, the question that concerns everyone most is what kind of robots will live alongside us in our homes. Technologies are already becoming an integral part of our daily lives, making it difficult to imagine what the future will look like. Foresight, however, has nothing to do with fortune-telling: it is an evidence-based method for developing a shared long-term vision of the future and using it to inform decisions today. The second moderator, Vladislav Beshlyaga, a lead expert at the centre, explained how such work is organised in practice.

Vladislav Beshlyaga, Mikhail Komarov © HSE University

As an educational exercise, session participants were invited to take on the role of HSE University researchers and work through the process of developing a foresight project. Using a semantic map prepared with the iFORA big data analysis system, three teams worked through several stages: first, they identified key trends in robotics; then, they assessed the associated opportunities and threats; and finally, they developed a future scenario and presented it to the audience.

The proposed scenarios were defended in a live discussion. Although the teams worked independently, their conclusions were similar in many respects. The moderators noted that the social dimension—namely, the role of robots in supporting people—featured in all three presentations. In particular, it underpinned the trend identified by the teams toward the development of robot assistants for the elderly and children. At the same time, participants stressed that the final say in medical treatment decisions must always rest with a human doctor. A robot could dispense medication only with a healthcare professional's approval, for example, via telemedicine. The discussion also touched on chatbot robots as a potential response to the growing demand for emotional support.

The teams linked the second trend, the development of multi-robot systems, to the idea that domestic robot assistants will not become a reality without robots being able to interact with one another. This will require network connectivity, collaborative robotics, and computer vision technologies that enable robots to navigate small urban apartments. This, in turn, points to a third trend: the emergence of ecosystems of interconnected devices and services, ranging from delivery robots already operating on city streets to order-taking systems integrated into people's homes. Participants suggested that rather than purchasing robots outright, people might access them through subscription or leasing arrangements, or have them included as part of their housing.

The teams identified several major barriers to the adoption of domestic robots: cybersecurity risks and personal data protection concerns, high costs and limited production capacity, dependence on cloud computing, the uncanny valley effect, and challenges related to cultural acceptance of the technology. Among the opportunities mentioned were large language models, autonomous and privacy-preserving solutions that operate without cloud connectivity, and AI agents capable of proactively detecting security threats.

In conclusion, the moderators identified three key themes that had emerged from the discussion: social responsibility, public perceptions of technology, and technological limitations alongside the economics of access.

HSE University Vice President Elena Odoevskaya（https://www.hse.ru/en/org/persons/198453116/）, who took part in the session, noted that the participants had stepped into the role of foresight experts, working with trends identified by HSE University researchers using the iFORA system.

‘I particularly value the students' perspective on how they envision the future and how actively they want to contribute to shaping it,’ says Elena Odoevskaya. ‘The fact that all three teams, when discussing trends, prioritised developing practices to reduce inequality and social segregation through widespread adoption of robotic technologies in households shows that HSE University has made the right strategic choice in its ambition to become a technological, global, and socially oriented university.’

In addition to leading the foresight session, the HSE ISSEK Centre for Strategic Analysis and Big Data presented iFORA, a system for intelligent big data analysis（https://issek.hse.ru/en/ifora/）. The system draws on a continuously updated database of more than 850 million documents, including over 390 million scientific publications, more than 150 million patents, and over 130 million market research and professional media materials. This extensive dataset provides the foundation for insights generated through foresight projects. The centre's experts also introduced conference participants to a new multi-agent platform for AI solutions（https://techpro.hse.ru/ai-solutions/） currently being developed as part of the Priority 2030 programme.

During a poster session, the centre's lead programmer, Alexander Anokhin（https://www.hse.ru/en/org/persons/1134568921/）, presented a recently proposed approach to latent reasoning in language models. Instead of reasoning word by word, the model ‘thinks’ by considering a mixture of several possible options simultaneously. This approach aims to generate shorter answers while allowing the model to maintain and evaluate multiple hypotheses at once. The team examined how the authors of the approach achieved the claimed improvement in performance and concluded that the main contribution came not from the Mixture-of-Thought concept itself, but from the accompanying techniques: appending regular text after the hidden reasoning stage and forcing the model to stop early.

Konstantin Vishnevskiy

Konstantin Vishnevskiy（https://www.hse.ru/en/staff/konstantin/）, Director of the HSE ISSEK Centre for Strategic Analysis and Big Data, noted that developing artificial intelligence technologies and applying them to big data analysis are among the centre's key areas of focus. ‘We are pleased to take part in this conference, which brings together Russian researchers presenting some of the best work in this field. The foresight session and poster presentations provided the opportunity to showcase different aspects of our work, from applying the iFORA system in foresight projects to our own research on language models. In particular, we have been exploring new approaches to reasoning in language models and testing which mechanisms actually improve the quality of their responses. A similar principle underpins our multi-agent AI platform, where analyst agents search for and interpret information and conduct bibliometric and patent analyses, while a critic agent checks their conclusions, identifies inaccuracies, and sends the results back for revision when necessary,’ he said.

Date

28 October

Topics

Priority 2030（https://www.hse.ru/en/news/priority/）

Keywords

HSE Development Programme until 2030（https://www.hse.ru/en/news/tags/development/）foresight（https://www.hse.ru/en/news/keywords/44001856/）HSE as a Technological University（https://www.hse.ru/en/news/keywords/1060759463/）iFORA（https://www.hse.ru/en/news/keywords/220734971/）machine learning（https://www.hse.ru/en/news/keywords/997811894/）Strategic Technological Projects（https://www.hse.ru/en/news/keywords/1049293911/）

About

, Centre for Strategic Analysis and Big Data（https://issek.hse.ru/en/ifora/）, Department of Business Informatics（https://gsb.hse.ru/en/bi/）, HSE Graduate School of Business（https://gsb.hse.ru/en/）, Institute for Statistical Studies and Economics of Knowledge（https://issek.hse.ru/en/）

About persons

Alexander Anokhin（https://www.hse.ru/en/org/persons/1134568921）

Vladislav Beshlyaga（https://www.hse.ru/en/org/persons/305060559）

Konstantin Vishnevskiy（https://www.hse.ru/en/staff/konstantin）

Mikhail M. Komarov（https://www.hse.ru/en/staff/mkomarov）

Elena Odoevskaia（https://www.hse.ru/en/org/persons/198453116）

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