Surgut, Russian Federation
Russian Federation
The article reveals the possibility and risks of using neural networks when forming project teams. The authors propose the following areas of application of neural networks in project implementation: classification, selection of projects; analysis of counterparties (contractors); project performance assessment; predicting project performance; labor productivity assessment; predicting the time required to perform intellectual work; predicting the likelihood of project escalation (that is, a situation in which the project will grow, require more and more resources and cannot be completed in principle); forecasting project duration; project cost forecasting; project schedule management; forecasting the cost of risks; assessing the likelihood of successful completion of the project. But as a new direction, it is proposed to consider the use of neural networks when forming project teams. The formation of project teams is considered by the authors of the article as a complex process that includes defining the goals and objectives of the project, analyzing the requirements for the skills and experience of team members, selecting candidates and assigning roles. The authors propose using neural networks as an innovative tool.
project team, artificial intelligence, neural networks, the capabilities of neural networks in the formation of project teams, the risks of neural networks in the formation of project teams
1. Chulanova, O. L. Koncepciya integracii tehnologiy iskusstvennogo intellekta v rabotu s personalom v cifrovoy paradigme / O. L. Chulanova // Upravlenie personalom i intellektual'nymi resursami v Rossii. - 2020. - T. 9, № 2. - S. 5-9. - DOIhttps://doi.org/10.12737/2305-7807-2020-5-9. - EDN NTQLLO.
2. Chulanova, O. L. Upravlenie integraciey tehnologiy iskusstvennogo intellekta kak tehnologicheskogo trenda v usloviyah cifrovoy transformacii v rabotu s personalom / O. L. Chulanova, K. N. Haybullova // Vestnik Surgutskogo gosudarstvennogo universiteta. - 2020. - № 1(27). - S. 112-121. - DOIhttps://doi.org/10.34822/2312-3419-2020-1-112-121. - EDN JRVAHQ.
3. Chulanova, O. L. Iskusstvennyy intellekt kak osnovnoy trend razvitiya informacionnogo obschestva / O. L. Chulanova, E. V. Fomina // Zhurnal sociologicheskih issledovaniy. - 2019. - T. 4, № 2. - S. 6-10. - EDN BRTMEJ.
4. Chulanova, O. L. Cifrovye instrumenty optimizacii deyatel'nosti proektnyh komand / O. L. Chulanova, D. V. Chulanov, Yu. A. Hohryakova // Aktual'nye problemy social'nyh i trudovyh otnosheniy : Materialy X Mezhdunarodnoy nauchno-prakticheskoy konferencii, posvyaschennoy 300-letiyu obrazovaniya Rossiyskoy akademii nauk, Mahachkala, 16 dekabrya 2022 goda. - Mahachkala: Federal'noe gosudarstvennoe byudzhetnoe uchrezhdenie nauki Institut social'no-ekonomicheskih issledovaniy Dagestanskogo nauchnogo centra Rossiyskoy akademii nauk, 2023. - S. 50-54. - DOIhttps://doi.org/10.26159/APSTO.2022.10.10.010. - EDN LTWTIB.
5. Zhavoronkova, O. R. Vliyanie cifrovoy ekonomiki na transformaciyu komandoobrazovaniya / O. R. Zhavoronkova, P. I. Red'kina // Social'no-ekonomicheskie predposylki i rezul'taty razvitiya novyh tehnologiy v sovremennoy ekonomike : Materialy III Mezhdunarodnoy nauchnoy konferencii, Nizhniy Novgorod, 17 fevralya 2021 goda. - Nizhniy Novgorod: Nacional'nyy issledovatel'skiy Nizhegorodskiy gosudarstvennyy universitet im. N.I. Lobachevskogo, 2021. - S. 80-85. - EDN OEFUKI.
6. RIA Novosti: inform. agenstvo Rossii : sayt. Moskva. Obnovlyaetsya v techenie sutok. [Elektronnyy resurs] URL: https://ria.ru/20230322/neyroset-1859660468.html (data obrascheniya 02.04.2023).
7. RBK Trendy: inform.agenstvo Rossii: sayt. Moskva. Obnovlyaetsya v techenie sutok. [Elektronnyy resurs] URL: https://trends.rbc.ru/trends/industry/641157be9a7947d3401fa3e8 (data obrascheniya 02.04.2023)
8. Skvorcov S. Chto takoe neyronnye seti i kak oni rabotayut // sky.pro: web-sayt. - 2022. - 7 oktyabrya. URL: [https://sky.pro/media/neyronnye-seti/] (data obrascheniya 15.05.2023)
9. Problemy sovremennogo mashinnogo obucheniya // Habr: web-sayt. - 2022. - 14 fevralya. - URL: [https://habr.com/ru/companies/ods/articles/651103/] / (Data obrascheniya 15.05.2023)
10. Pereulkov L. “Ya professional'no generiruyu izobrazheniya v neyroseti i schitayu, chto eto tozhe iskusstvo”, Tin'koff zhurnal [Elektronnyy resurs] URL: [https://journal.tinkoff.ru/ai-artist/] (data obrascheniya 19.04.2023
11. Ivanchenko, M. A. Chelovek igrayuschiy, mashina igrayuschaya: put' k ideal'noy neyroseti i predposylki vozniknoveniya postgumanizma / M. A. Ivanchenko, P. E. Arhipov // Idei i idealy. - 2021. - T. 13, № 1-1. - S. 151-165. - DOIhttps://doi.org/10.17212/2075-0862-2021-13.1.1-151-165. - EDN OWZFYJ.
12. Clare Duffy and Ramishah Maruf, CNN “Elon Musk warns AI could cause ‘civilization destruction’ even as he invests in it” URL: [https://edition.cnn.com/2023/04/17/tech/elon-musk-ai-warning-tucker-carlson/index.html] (data obrascheniya 19.04.2023)
13. Azarnova, T. V. Primenenie metodov intellektual'nogo analiza dannyh v ocenke funkcional'noy effektivnosti komand menedzherov / T. V. Azarnova, I. M. Terlyuga, V. V. Uhlova // Vestnik Voronezhskogo gosudarstvennogo universiteta. Seriya: Sistemnyy analiz i informacionnye tehnologii. - 2020. - № 4. - S. 50-63. - DOIhttps://doi.org/10.17308/sait.2020.4/3204. - EDN TDTEFQ.
14. Maslova V.M. Cifrovaya transformaciya - novye processy upravleniya personalom // Ekonomicheskie sistemy. 2019. Tom 12. № 1-2 (44-45). S. 50-55. DOIhttps://doi.org/10.29030/2309-2076-2019-12-1-2-50-55.
15. Vladimir Li, “Mozhno li doverit' podbor sotrudnikov iskusstvennomu intellektu? Opyt rossiyskih kompaniy”, RB.RU [Elektronnyy resurs] URL: [https://rb.ru/opinion/podbor-ii/] (data obrascheniya 20.03.2023)
