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Article Abstract
Background: Use of artificial intelligence to generate personal statements for residency is currently not permitted but is difficult to monitor. This study sought to evaluate the ability of surgical residency application reviewers to identify artificial intelligence-generated personal statements and to understand perceptions of this practice.
Methods: Three personal statements were generated using ChatGPT, and 3 were written by medical students who previously matched into surgery residency. Blinded participants at a single institution were instructed to read all personal statements and identify which were generated by artificial intelligence; they then completed a survey exploring their opinions regarding artificial intelligence use.
Results: Of the 30 participants, 50% were faculty (n = 15) and 50% were residents (n = 15). Overall, experience ranged from 0 to 20 years (median, 2 years; interquartile range, 1-6.25 years). Artificial intelligence-derived personal statements were identified correctly only 59% of the time, with 3 (10%) participants identifying all the artificial intelligence-derived personal statements correctly. Artificial intelligence-generated personal statements were labeled as the best 60% of the time and the worst 43.3% of the time. When asked whether artificial intelligence use should be allowed in personal statements writing, 66.7% (n = 20) said no and 30% (n = 9) said yes. When asked if the use of artificial intelligence would impact their opinion of an applicant, 80% (n = 24) said yes, and 20% (n = 6) said no. When survey questions and ability to identify artificial intelligence-generated personal statements were evaluated by faculty/resident status and experience, no differences were noted (P > .05).
Conclusion: This study shows that surgical faculty and residents cannot reliably identify artificial intelligence-generated personal statements and that concerns exist regarding the impact of artificial intelligence on the application process.
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| http://dx.doi.org/10.1016/j.surg.2024.08.018 | DOI Listing |
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