Webinar and Q&A on ‘AI Analysis of Racism in Sports Journalism and College Coaching’

Mohit Iyyer
Mohit Iyyer

Assistant professor Mohit Iyyer of the College of Computer and Information Sciences (CICS) will conduct an online webinar and Q&A offering an analysis of racism in sport journalism and coaching from 4 to 5:30 p.m. Wednesday, Sept. 30. The public is invited, but space is limited and registration is required.

Iyyer’s zoom webinar will explore whether artificial intelligence (AI) can offer insights into the prevalence of racial bias in the sports world. He uses artificial intelligence– in particular, natural language processing and machine learning – to analyze evidence of racial bias in sports broadcasting and coaching.

The AI expert will share his computational analysis of over 60 years of sports broadcasts, as well as evidence of racism and unconscious bias in game commentary and the discussion of athletes. He also will share information about a new study of racism in college football coaching and the AI tools he uses in his research. A Q&A will follow his remarks.

Iyyer quotes Nelson Mandela, “Sport has the power to change the world. It has the power to inspire. It has the power to unite people in a way that little else does. It speaks to youth in a language they understand. Sport can create hope where there was only despair.”

Iyyer observes that as the nation engages in a painful examination of institutional racism, longstanding bias in the sports world is in the public eye. Professional athletes are taking collective action to halt playoff games and bring attention to Black Lives Matter, he states. Also, college athletes are joining forces to call out racism and financial exploitation in college sports, and, curtailed or canceled sports seasons are contributing to a highly charged environment.

Iyyer’s talk is part of the Computing and Social Justice Series that brings CICS researchers and the public together to critically assess how computing innovation intersects with vitally important issues like structural bias, civic participation, economic inequality, and citizen privacy.