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Researchers pioneer use of AI to reduce bias in sports scouting

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In a first-of-its-kind study in Canada, researchers from Toronto Metropolitan University (TMU) have demonstrated how artificial intelligence (AI) can be used to reduce bias in professional sports scouting while preserving the critical role of human expertise.

The research, titled “Blind scouting: using artificial intelligence to alleviate bias in selection” and published in Personnel Review, was led by Dr. Louis-Étienne Dubois of the Creative Industries program and Laurel Walzak of RTA Sport Media, The Creative School at TMU.

“This study provides valuable insights into scouts’ cognition and moves past the prevailing AI versus human dichotomy by demonstrating how the technology can improve processes without removing the need for experts,” said Dubois and Walzak.

“It shows the value of AI-based tools in scouting—particularly when assessing a player’s ability—and suggests the technology can work alongside traditional approaches to support more objective, performance-focused evaluations.”

In collaboration with a professional North American soccer team, the researchers employed an experimental “blind scouting” model using AI-anonymized game footage. Scouts were asked to assess players while verbalizing their thought processes—a method known as “think-aloud” cognitive analysis.

The study found that removing identifiable features using AI enhanced the scouts’ attention to tactical performance and minimized focus on physical attributes that can introduce bias.

“This isn’t just about saving time or money—it’s about making better decisions in high-stakes environments,” said Walzak. “Our findings suggest AI can be a powerful tool, giving teams a competitive advantage, particularly in talent evaluation, where small biases can have big consequences.”

The study represents one of the first major contributions in the emerging field of AI use in sports talent management. With applications beyond scouting—from hiring practices, computer visioning in sports, and broader HR strategies—the research offers valuable insights and strong practical industry implications as sports organizations begin to adopt advanced technologies.

This study is part of TMU’s ongoing commitment to advancing ethical and impactful innovation at the intersection of technology, creativity, and society.

More information:
Louis-Etienne Dubois et al, Blind scouting: using artificial intelligence to alleviate bias in selection, Personnel Review (2025). DOI: 10.1108/PR-02-2024-0130

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Toronto Metropolitan University


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Researchers pioneer use of AI to reduce bias in sports scouting (2025, May 21)
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