| DC Field | Value | Language |
| dc.contributor.author | Senkevich, P. V. | - |
| dc.contributor.author | Ermakova, A. D. | - |
| dc.coverage.spatial | Минск | en_US |
| dc.date.accessioned | 2026-09-15T05:59:40Z | - |
| dc.date.available | 2026-09-15T05:59:40Z | - |
| dc.date.issued | 2026 | - |
| dc.identifier.citation | Senkevich, P. V. The human factor in human – AI interaction: hyper – reliance as a systemic cognitive and organizational risk / P. V. Senkevich, A. D. Ermakova // Актуальные вопросы экономики и информационных технологий : сборник материалов докладов 62-й научной конференции аспирантов, магистрантов и студентов БГУИР, Минск, 13–17 апреля 2026 г. / Белорусский государственный университет информатики и радиоэлектроники. – Минск, 2026. – С. 736–737. | en_US |
| dc.identifier.uri | https://libeldoc.bsuir.by/handle/123456789/65731 | - |
| dc.description.abstract | The paper analyzes hyper-reliance on AI as a cognitive and organizational phenomenon in which users consistently treat
algorithmic outputs as more trustworthy than their own expert judgments, effectively lowering the level of critical self-assessment. Drawing
on international studies, statistical data, and documented incidents, the paper shows that this tendency is becoming systemic and
generating new professional and economic risks. Unlike works focused on the technical improvement of AI, the paper highlights the human
factor as the most vulnerable element of the system. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | БГУИР | en_US |
| dc.subject | материалы конференций | en_US |
| dc.subject | artificial intelligence | en_US |
| dc.subject | the algorithms work | en_US |
| dc.subject | economic risks | en_US |
| dc.title | The human factor in human – AI interaction: hyper – reliance as a systemic cognitive and organizational risk | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | Актуальные вопросы экономики и информационных технологий : материалы 62-й научной конференции аспирантов, магистрантов и студентов (2026)
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