Chicago Art School Deploys Machine Learning in Admissions

Inside Higher Ed

Lauren Coffey

April 29, 2024

 In 2019, Kyle O’Connell had a vision of leveraging technology to boost in-person relationships with students at the School of the Art Institute of Chicago. He set out to create a machine learning-enabled system that could help with the admissions process, ultimately meant to direct employees’ energy and resources toward students in an earlier and more effective way.

“We deal with the technology, but ultimately we want to bring it back to getting more in-person time with who we can make the most impact on,” said O’Connell, director of enrollment analytics and forecasting at the Chicago institution, known as SAIC. “And there’s more information we have about students than you’re able to assess as an individual person.”

He admitted that the machine-learning attempt “didn’t knock it out of the park on the first try,” undermined by data that was not very robust. He worked to adjust the data-gathering process over the next couple years, and his timeline coincided with an opportunity to work with the Chicago technology consulting firm SPR to use machine-learning models during the application process.

At the start of 2023, SPR asked organizations to send in pitches on how to better the local community, with the winner getting $50,000 in honor of the company’s 50th anniversary. The criteria were broad—SPR received pitches on topics as diverse as drones and deforestation—but the firm ultimately chose SAIC because it “fit best with our mission” of boosting the local community, according to Steven Devoe, SPR’s data specialty director.

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