A study by researchers at Cornell University in Ithaca, New York, found that women athletes are subjected to a subtle gender bias by sport journalists. The researchers conducted a computer analysis of several thousand tennis player interviews at post-match press conferences. Words spoken by reporters to athletes were tabulated and examined by computer analysis to determine whether or not the questions related to non-court events or actions. The artificial intelligence computer model eliminated any researcher bias that would impact the results.
The results showed that women were significantly more likely than men to be asked questions that did not pertain to their on-court performance. Women were more likely than men to be asked questions about their fathers, their personal lives, and what they were wearing.
The article, “Tie-breaker: Using Language Models to Quantify Gender Bias in Sports Journalism,” won the Best Paper Award at the recent Natural Language Processing Meets Journalism Workshop at the 25th International Joint Conference on Artificial Intelligence in New York City.