AI Could Revolutionize College Admissions, Expert Argues

Artificial intelligence could fundamentally transform the college admissions process, offering a more objective and transparent approach that addresses concerns about bias and fairness, according to Hugh Hewitt, a Fox News contributor.

Hewitt argues that AI is well-suited to handle the data-intensive nature of college applications, which involve sorting through test scores, GPAs, essays, résumés, and recommendations. He suggests that AI could assess these materials with a speed and objectivity that human admissions officers may struggle to match.

"The sorting and scaling of numbers—GPAs and test scores—are exactly what AI can compile and assess in hours, if not minutes," Hewitt wrote. "If AI is even a tenth as powerful as advertised, it should be able to sort resumes and recommendations by truthfulness, quality, and sincerity."

AI models could also be trained to consider a wide range of legitimate factors beyond academic performance, such as in-state or out-of-state status, family income, life circumstances, geographic diversity, and the rigor of a student's previous educational institutions. Crucially, Hewitt notes, AI can be programmed to disregard factors such as race or ethnicity, aligning with current legal restrictions on admissions practices.

"AI models can be instructed not to give any weight to applicants’ race, ethnicity, or religion—characteristics whose use in admissions is restricted by federal law and Supreme Court precedent," he stated.

The current admissions system, Hewitt contends, has become susceptible to suspicion of politicization and the use of controversial factors. An AI-driven process, he suggests, could offer greater transparency to applicants, donors, evaluators, and legal bodies, thereby rebuilding trust in the fairness of college admissions.

"The collective process across the country could use a large dose of objectivity and a consequent rise in trust in the results," Hewitt wrote. "An AI-driven admissions process that is transparent to outside evaluators would be a welcome evolution in the increasingly controversial question of choosing elites."

Hewitt estimates that the adoption of AI in admissions could impact a workforce of at least 40,000 admissions employees nationwide. He proposes that universities should consider deploying AI as a parallel admissions process alongside their existing human-led systems to compare outcomes.

"At a minimum, colleges and universities should want to deploy a parallel admissions process run by AI alongside their existing structure. How interesting and illuminating would a side-by-side comparison of accepted applicants be?"

He further suggests that AI could evaluate factors like athletic ability, legacy status, artistic talent, and first-generation college student status, which are considered indicators of potential success. The use of AI could also provide a robust defense against potential lawsuits challenging admissions decisions, by clearly outlining the objective criteria used in the selection process.

This application of AI in admissions aims to move beyond subjective judgment and toward a system that more objectively analyzes data and identifies indicators of long-term success for admitted students, both within academia and in their future careers. The transition, however, suggests a significant shift for the existing admissions workforce, who currently perform tasks involving subjective evaluation.