Russian Federation
Russian Federation
Modern trends in the development of society and the capabilities of information infrastructure require the sustainable operation of existing models for identifying conflicts among employees in an organization, as well as the use of new approaches. The research work examines certain weaknesses of existing survey methods, which can significantly reduce the quality of the model’s results. The use of artificial intelligence makes it possible to minimize the identified shortcomings of survey methods, process large volumes of information of various types, opening up new opportunities for its use in the field of personnel management. This paper examines current problems of survey methods and the good prospects of using artificial intelligence to identify conflicts between employees of an organization.
conflictology, personnel conflict management, hidden conflict, survey data, artificial intelligence
1. Kraev V.M., Tikhonov A.I. Risk management in human resource management. TEM Journal, 2019, 8(4), P. 1185–1190. DOI: https://doi.org/10.18421/TEM84-11; EDN: https://elibrary.ru/CYVNJK
2. Jan Widacki, First Attempts at Practical Use of Instrumental Lie Detection. European Polygraph. December 2019 13 (4): 203–222. DOI:https://doi.org/10.2478/ep-2019-0014
3. Mashtakov V.A., Belov V.M. Modeling of a hardware and software complex “Poligraf” based on freely distributable microcontroller platforms // Bezopasnost' cifrovyh tehnologiy. — 2021. — № 4 (103). — P. 9–19. — DOI: 10.17212/ 2782-2230-2021-4-9-19 DOI: https://doi.org/10.17212/2782-2230-2021-4-9-19; EDN: https://elibrary.ru/SAKCPV
4. Kraev V.M., Tihonov A.I. Risk-menedzhment v upravlenii kadrami // Konkurentosposobnost' v global'nom mire: ekonomika, nauka, tehnologii. 2016. № 8-2 (21). S. 22–25. EDN: https://elibrary.ru/XCNIWB
5. Alekseeva P.A., Kraev V.M. Sovremennye modeli snizheniya konfliktnosti personala predpriyatiy aerokosmicheskogo kompleksa // Moskovskiy ekonomicheskiy zhurnal. 2021. № 1. S. 28. DOI: https://doi.org/10.24411/2413-046X-2021-10004; EDN: https://elibrary.ru/TJRYWY
6. Kraev V.M., Masich I.S., Tihonov A.I. Metod vyyavleniya skrytyh konfliktnyh otnosheniy mezhdu sub'ektami biznes-processov na osnove parnyh korrelyaciy vzaimnyh ocenok // Biznes-informatika. 2022. T. 16. № 3. S. 85–97. DOI: https://doi.org/10.17323/2587-814X.2022.3.85.97; EDN: https://elibrary.ru/QMXXQE
7. Tihonov V.A., Kraev V.M. Metod vyyavleniya skrytyh konfliktov sredi sotrudnikov organizacii // Moskovskiy ekonomicheskiy zhurnal. 2023. T. 8. № 1. DOI: https://doi.org/10.55186/2413046X_2023_8_1_9; EDN: https://elibrary.ru/CSXJEJ
8. Nacional'naya strategiya razvitiya iskusstvennogo intellekta na period do 2030 goda. Ukaz Prezidenta RF № 490 ot 10.10.2019. — URL: http://www.kremlin.ru/acts/bank/ 44731
9. GOST R 59277–2020. Sistemy iskusstvennogo intellekta. Klassifikaciya sistem iskusstvennogo intellekta.
10. GOST R 59276–2020. Sistemy iskusstvennogo intellekta. Sposoby obespecheniya doveriya. Obschie polozheniya.
11. Finn V.K. Intellekt, informacionnoe obschestvo, gumanitarnoe znanie i obrazovanie: ponyatiynye i logicheskie osnovaniya iskusstvennogo intellekta, gumanitarnoe znanie i kognitivnye issledovaniya v informacionnom obschestve, obrazovatel'nye programmy dlya iskusstvennogo intellekta. M.: Lenand, 2021, 463 s. EDN: https://elibrary.ru/XXMMAC
12. Folomeeva T.V., Sadovskaya E.D., Vinokurov F.N., Fedotova S.V. Rol' cifrovyh tehnologiy v ekonomicheskih resheniyah: iskusstvennyy intellekt i sklonnost' k risku // Vestnik Moskovskogo universiteta. Seriya 14: Psihologiya. 2022. № 3. S. 40–64. DOI: https://doi.org/10.11621/vsp.2022.03.04; EDN: https://elibrary.ru/EBLKLN
13. Shaposhnikov A.A. Perspektivy ispol'zovaniya iskusstvennogo intellekta pri provedenii psihofiziologicheskih issledovaniy // Vestnik Sankt-Peterburgskogo voennogo instituta voysk nacional'noy gvardii. 2022. № 1 (18). S. 29–32. EDN: https://elibrary.ru/XRBYCQ
14. Bessonov A.A. Ispol'zovanie algoritmov iskusstvennogo intellekta v kriminalisticheskom izuchenii prestupnoy deyatel'nosti (na primere seriynyh prestupleniy) // Vestnik MGYuA imeni O.E. Kutafina. 2021. № 2 (78). S. 45–53. DOI: https://doi.org/10.17803/2311-5998.2021.78.2.045-053; EDN: https://elibrary.ru/ZZALSN
15. Romanova T.V., Homenko A.Yu. Identifikaciya avtora teksta v setevoy kommunikacii // Vestnik Volgogradskogo gosudarstvennogo universiteta. Seriya 2: Yazykoznanie. 2022. T. 21. № 3. S. 143–157. DOI: https://doi.org/10.15688/jvolsu2.2022.3.12; EDN: https://elibrary.ru/GZCXFA
16. Homenko A.Yu. Lingvisticheskoe modelirovanie kak osnova dlya sozdaniya poluavtomaticheskogo atribucionnogo algoritma // Politicheskaya lingvistika. 2022. № 3 (93). S. 90–100. EDN: https://elibrary.ru/TEQIXF
17. Homenko A.Yu. Problema formalizacii struktury yazykovoy lichnosti dlya komp'yuternogo predstavleniya // Voprosy kognitivnoy lingvistiki. 2021. № 2. S. 111–117. DOI: https://doi.org/10.20916/1812-3228-2021-2-111-117; EDN: https://elibrary.ru/VJLEJC
18. Romanova T.V. Yazyk politkorrektnosti: svoy-chuzhoy // Mir russkogo slova. 2015. № 4. S. 21–26. EDN: https://elibrary.ru/VKZJTF
19. Zvereva E.B. Etiket delovoy perepiski // Innovacii. Nauka. Obrazovanie. 2020. № 24. S. 1986–1990. EDN: https://elibrary.ru/QHMERE
20. Homenko A.Yu. Lingvisticheskoe modelirovanie kak instrument vyyavleniya iskazheniy rechevyh navykov avtora pis'mennogo rechevogo proizvedeniya: opyt prakticheskogo issledovaniya // Voprosy psiholingvistiki. 2018. № 36. S. 209–226. EDN: https://elibrary.ru/XSCRDF
21. Mitrofanova E.A., Svistunov V.M., Lobachev V.V. Cifrovizaciya ekonomiki kak vazhnyy faktor formirovaniya novyh trendov rynka truda // Upravlenie personalom i intellektual'nymi resursami v Rossii. — 2019. — T. 8, № 6. — S. 59–70. DOI: https://doi.org/10.12737/2305-7807-2020-59-70; EDN: https://elibrary.ru/IAULZI
