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News
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.

 

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Bias Perceptions of Generative AI: A Comparison of Public Sentiment on Twitter and Workplace Perspectives

Innovations. 2025. Vol. 80. No. 1. P. 281–304.
Uhunoma E., Maryann Asemota

Generative Artificial Intelligence (Gen AI) is one of the most
significant technological inventions in the last decade.It enhances content generation
across various domains, from personal messages to work-related tasks, encompassing
text, images, and videos. However, there have also been several debates surrounding
its inadvertent risks for bias and perpetuating stereotypes (Ferrara, 2023; Xavier 2024)
both from gender and racial perspectives (Nicoletti & Bass, 2023; Zhou, 2024;
Sadeghiani, 2024).Today, Gen AI is also being used in the workplace, with many
organisations adopting custom-built Gen AI tools as part of their working tools and
systems. Consequently, the objective of this research was tofind out if employees
perceive work-related outputs of Gen AI to be biased against women, people of colour
or neurodiverse people, and how this perception compares to that of the public, who
use Gen AI tools for both work and non-work-related purposes. A mixed-methods
approach was employed in this research. From workplace perspectives, quantitative
data were collected using a structured questionnaire from UK employees. From the
public perspective, qualitative data were collected through text mining using specific
keywords from Tweets on X platform. Findings showed that, while workplace
respondents reported modest levels of perceived bias across all groups, public
sentiment analysis and themes showed significant mistrust and negative perception of
bias in generative AI outputs for women and people of colour. There was however
positive perception as it relates to Neurodiverse people, with the public data showing
positive sentiments for Gen AI outputs as it relates to Neurodiverse people, as the users
view it as a tool for helping dyslexic users communicate better.

Research target: Computer Science Psychology Economics and Management
Language: English
Full text
Keywords: Social MediaSentiment AnalysisGenerative AIGen AIAI BiasWorkplace Perception
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