Skip to main content
article

Embodied Emotion at Scale: Sport as the Collective Emotion Laboratory for Human Development in the Age of AI

Abstract

Sport represents humanity’s largest-scale emotion laboratory where intense competitive emotions are practiced within safe boundaries through collective participation. As artificial intelligence evolves to systematize virtual and digital experiences, sport's irreplaceable embodied practice of collective participation becomes more apparent, not less. This conceptual paper demonstrates how artificial intelligence can optimize emotional learning from large-scale sport experiences while highlighting, rather than replacing, their unique human development value. Authors propose a four-level framework positioning sport organizations as comprehensive emotional development centers that leverage AI-powered technologies, including video analytics capturing facial expressions, body movements, and collective synchrony, to systematize emotional intelligence development. The framework creates measurable competitive advantages through enhanced fan loyalty, operational efficiency, risk mitigation, and new revenue streams. Sport’s role as a cornerstone of human capital development through embodied participation will strengthen with artificial intelligence, positioning sport management as a leader in leveraging technology to enrich, not replace, authentic human experiences.

Keywords:

  • Keyword: Artificial Intelligence
  • Keyword: Embodied Emotion
  • Keyword: Emotion Laboratory
  • Keyword: Human Capital
  • Keyword: Emotional Intelligence
  • Keyword: Sport Management

How to Cite:

Lee, H., Kim, J., Yoo, Y. & Lu, Z., (2025) “Embodied Emotion at Scale: Sport as the Collective Emotion Laboratory for Human Development in the Age of AI”, Journal of Applied Sports Management 17(4). doi: https://doi.org/10.7290/jasm17uQ6t

Downloads
Download PDF

Share

Author details

Downloads

Information

Metrics

  • Views: 0
  • Downloads: 0

Citation

Download RIS Download BibTeX

File Checksums

(MD5)
  • PDF: 2ef4bf55d2477f840993e4f7e267ba24