Algorithmic College Admissions in the U.S.: Distances Between Vendors' Claims and Applicants' Perceptions

Abstract

The historically controversial U.S. college admissions process is increasingly shaped by algorithmic systems, exacerbating the potential for controversies over admissions and their fairness. Despite their increased use, questions remain about how vendors who provide algorithmic admissions technologies legitimize them and how applicants perceive these technologies. We report on 1) a qualitative content analysis of admissions technology vendor websites, and 2) interviews with college applicants, highlighting the distance between vendors' claimed benefits for universities (e.g., increased decision-making efficiency) and applicants (e.g., ''unbiased'' decisions) and applicants' perceived harms to themselves (e.g., undermining holistic review, hindering diversity, equity, and inclusion efforts). We consider the implications of algorithmic admissions decision-making, including privacy harms, discuss regulatory implications, and offer recommendations to guide algorithmic transparency efforts. However, we caution that transparency would not address some harms perceived by applicants, like inaccuracy and privacy violations.

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