Related Experiment Video
Updated: Oct 11, 2025

Determining the Contribution of the Energy Systems During Exercise
Published on: March 20, 2012
Paradoxical Tensions Related to AI-Powered Evaluation Systems in Competitive Sports
Elena Mazurova1, Willem Standaert2,3, Esko Penttinen1
1Aalto University, Espoo, Finland.
Abstract:
Judging in competitive sports is prone to errors arising from the inherent limitations to humans' cognitive and sensorial capabilities and from various potential sources of bias that influence judges. Artistic gymnastics offers a case in point: given the complexity of scoring and the ever-increasing speed of athletes' performance, systems powered by artificial intelligence (AI) seem to promise benefits for the judging process and its outcomes. To characterize today's human judging process for artistic gymnastics and examine contrasts against an AI-powered system currently being introduced in this context, an in-depth case study analyzed interview data from various stakeholder groups (judges, gymnasts, coaches, federations, technology providers, and fans). This exploratory study unearthed several paradoxical tensions accompanying AI-based evaluations in this setting. The paper identifies and illustrates tensions of this nature related to AI-powered systems' accuracy, objectivity, explainability, relationship with artistry, interaction with humans, and consistency.
More Related Videos
05:21Characterization of the Sense of Agency over the Actions of Neural-machine Interface-operated Prostheses
Published on: January 7, 2019
08:24The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
Published on: August 25, 2023
Related Concept Videos
Social Facilitation
Self-Evaluation: Self-Enhancement and Self-Verification
Self-Evaluation Maintenance Model
Self-Presentation: Self-Monitoring and Self-Handicapping
Attitudes
Halo Effect