THE USE OF NEURAL NETWORK TECHNOLOGIES BY TEACHERS OF OLDER AGE GROUPS: A COMPARATIVE ANALYSIS OF REPRESENTATIVES OF MEDICAL AND SOCIOLOGICAL SCIENCES

Abstract


The article presents the results of an empirical study on the use of neural network technologies by elderly university teachers representing medical and sociological sciences. The study is based on survey data from 524 academic professionals, with a focus on 60 respondents aged 60 and older. Special attention is given to the comparative analysis of digital activity, engagement with generative AI, and preferred tools (GPT, DeepSeek, GigaChat, etc.). The findings show that medical educators are more likely to use neural networks in research, while sociologists integrate them more into teaching practices. The selection of these two disciplines is justified as representative for analyzing digital adaptation in academia. The article concludes with limitations and directions for future research.

About the authors

E. V. Malinovich

N. A. Semashko National Research Institute of Public Health, 105064, Moscow, Russia

I. E. Nadutkina

Saint Petersburg State Agrarian University, 196601, Saint Petersburg, Russia; Belgorod State National Research University, Belgorod, Russia, 308015

I. V. Konev

Belgorod State National Research University, Belgorod, Russia, 308015

N. S. Danakin

Belgorod State National Research University, Belgorod, Russia, 308015

References

  1. Wang F., Casalino L. P., Khullar D. Artificial intelligence in geriatric medicine: challenges and opportunities // J. Gen. Intern. Med. 2023. Vol. 38, N 3. P. 521–529.
  2. Ienca M., Vayena E. On the responsible use of artificial intelligence in health care // Nat. Med. 2020. Vol. 26. P. 463–464.
  3. Kim H., Park J., Lee J. The ethics of using artificial intelligence in medical research // Kosin Med. J. 2024. Vol. 39, N 1. P. 16–23.
  4. Joyce K. E., Selinger E., Cohn M. Toward a sociology of artificial intelligence: a call for research on inequalities and structural change // Socius: Sociological Research for a Dynamic World. 2020. Vol. 6. P. 1–10.
  5. Park H., Shin S. Y., Lee H. Public perceptions of artificial intelligence in healthcare: a national survey in South Korea // BMC Med. Ethics. 2024. Vol. 25. P. 23. doi: 10.1186/s12910-024-01052-9
  6. Schmidt J., Braun M., Blessing L. T. Artificial intelligence in medical care: patients’ perceptions and ethical challenges // J. Med. Ethics. 2023. Vol. 49, N 2. P. 145–152.

Statistics

Views

Abstract - 11

PDF (Russian) - 5

Cited-By


PlumX

Dimensions


Copyright (c) 1970 АО "Шико"

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mailing Address

Address: 105064, Vorontsovo Pole, 12, Moscow

Email: ttcheglova@gmail.com

Phone: +7 903 671-67-12

Principal Contact

Tatyana Sheglova
Head of the editorial office
FSSBI «N.A. Semashko National Research Institute of Public Health»

105064, Vorontsovo Pole st., 12, Moscow


Phone: +7 903 671-67-12
Email: redactor@journal-nriph.ru

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies