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News
September 11, 2026
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.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
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.

 

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Autonomous systems in ethical dilemmas: Attitudes toward randomization

Computers in Human Behavior Reports. 2021. Vol. 4. Article 100145.
Bodenschatz A., Uhl M., Walkowitz G.

It is ethically debatable whether autonomous systems should be programmed to actively impose harm on some to avoid greater harm for others. Surveys on ethical dilemmas in self-driving cars’ programming have shown that people favor imposing harm on some people to save others from suffering and are consequently willing to sacrifice smaller groups to save larger ones in unavoidable accident situations. This is, if people are forced to directly impose harm. Contrary to humans, autonomous systems feature a salient deontological alternative for immediate decisions: the ability to randomize decisions over dilemmatic outcomes. To be applicable in democracies, randomization must correspond to people's moral intuition. In three studies (N = 935), we present empirical evidence that many people prefer to randomize between dilemmatic outcomes due to moral considerations. We find these preferences in hypothetical and incentivized decision-making situations. We also find that preferences are robust in different contexts and persist across Germany, with its Kantian cultural tradition, and the US, with its utilitarian cultural tradition.

Research target: Social Sciences Economics and Management Psychology
Language: English
DOI
Text on another site
Keywords: Randomization attitudesEthical dilemmasAutonomous systemsUtilitarianismMachine ethics
Publication based on the results of:
Prosocial and antisocial behavior: an experimental study (2021)
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