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Challenges of Utilizing Artificial Intelligence in Sports Talent Identification | ||
| Archives in Sport Management and Leadership | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 30 تیر 1405 | ||
| نوع مقاله: Original | ||
| شناسه دیجیتال (DOI): 10.22108/asml.2026.146334.1095 | ||
| نویسندگان | ||
| Shahab Bahrami* 1؛ Bahman Asgari2؛ Meysam Nazari Ghanbari3 | ||
| 1Department of Physical Education, Ker.C., Islamic Azad University, Kermanshah, Iran | ||
| 2Department of Sport Management, Postgraduate Center, Payam Noor University, Tehran, Iran | ||
| 3Department of Sport Management, Faculty of Management and Accounting, College of Farabi, University of Tehran, Qom, Iran | ||
| چکیده | ||
| The aim of this study was to identify the challenges of using artificial intelligence (AI) in sports talent identification. A qualitative methodology was employed, utilizing Braun and Clarke’s (2006) six-step thematic analysis framework. Data collection involved purposive sampling of key informants until theoretical saturation was achieved. In-depth and semi-structured interviews were conducted with 14 experts and scholars specializing in sports talent identification and AI, including individuals engaged in both research and practical applications within this domain. To ensure validity and trustworthiness throughout the research process, four critical (credibility, dependability, confirmability and transferability) were meticulously evaluated at each stage. Analysis of the qualitative data obtained from the interviews resulted in 56 initial codes, which were categorized into 15 sub-themes and five main themes, including data and infrastructure, evaluation and integration, technical and model, ethical and legal, and organizational and management challenges. These findings illuminate significant obstacles encountered when leveraging AI in sports talent identification systems. Despite these challenges, the study emphasizes the potential for integrating human intelligence with AI to enhance both visual and scientific assessments. By addressing these barriers, AI-driven systems can significantly contribute to the identification of untapped talent across a variety of sports disciplines, thereby facilitating the development of more comprehensive talent development strategies. | ||
| کلیدواژه‌ها | ||
| Sports talent identification؛ Talent development؛ Artificial intelligence؛ AI؛ Machine Learning | ||
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آمار تعداد مشاهده مقاله: 174 |
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