Leveraging artificial intelligence for resident recruitment: can the dream of holistic review be realized?

Abstract

Aim: The purpose of this study was to investigate if principles of Artificial Intelligence (AI), specifically Natural Language Processing (NLP), could be applied to the personal statements of general surgery residency applicants in order to gain valuable insight into the candidates and facilitate a more comprehensive assessment. Methods: The personal statements from individuals applying for a general surgery residency position during the 2021/22 application cycle (n = 1792) were analyzed using AI technology. Comparison groups were drawn from a database of documents from the general population and the personal statements of current general surgery residents (n = 64) at a single academic center. The study was conducted in collaboration with a leading language psychology and natural language processing organization. Results: Applicants exhibited a language-based personality that was highly self-assured (P < 0.0001) and trusting (P < 0.0001), and less stress-prone (P < 0.0001) and impulsive (P < 0.0001) than that of the general population. Compared to the general applicant pool, current residents were significantly more emotionally aware (P < 0.001) and organized (P < 0.001) and less self-assured (P < 0.001) and less driven by power (P < 0.001). Conclusion: Natural language processing technology can be utilized to assess the unique characteristics of general surgery resident applicants based on the content of their personal statements. In addition, candidates who successfully gain admission to a single academic program display different language-based personalities and drives compared to the general applicant pool. Incorporating these principles of artificial intelligence into the residency selection process could facilitate a more holistic evaluation of candidates.