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September 25, 2026
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.
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User Perception and Evaluation of a Portrait Drawn by KUKA KR3 AGILUS Manipulator

P. 45–58.
Zagirov A., Chebotareva E., Osokin S., Li H., Magid E.

Creating an artistic portrait is considered one of the most complex areas of a generative art. Currently, generative artificial intelligence (AI) has made significant advancements in generating portraits of people based on photographic images. This has opened up new opportunities for utilizing AI achievements in robotic artistry. However, questions related to evaluation and human perception of such works, including their artistic value, remain open. In our work, we present experimental results of integrating the processing of human photographs using the generative model InstantID with a drawing robot and studying users' reactions to the obtained images. In our experiments, we generated graphic portraits of people and constructed their images using KUKA KR3 AGILUS robot. We then asked participants to rate the resulting portraits based on three parameters: similarity/recognition, beauty/aesthetics, and evoked emotions. The results of the experiments can be used in social robotics, including art therapy that involves social robots and human-robot interaction.

Language: English
DOI
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Keywords: взаимодействие человека и роботаhuman-robot interactionAutomated PortraitCreative RoboticsDrawing RobotsKUKA KR3 AGILUS RobotRobotic Portrait Drawing

In book

Interactive Collaborative Robotics. 9th International Conference, ICR 2024, Mexico City, Mexico, October 14–18, 2024, Proceedings
Cham: Springer, 2024.
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