本研究利用半結構式深度訪談，探討企業主管對於「AI面相招募系統」的建議與願意採納之程度。此系統結合AI科技中的人臉辨識功能與中國傳統的面相學，對人臉進行辨識並給出相應的人格特徵。本研究同時將Holland職業類別模型論納入「AI面相招募系統」中，增加「AI面相招募系統」的準確度與效度。
本研究專注於「AI面相招募系統」的眉毛和眼睛兩部位。歸納訪談結果後得出，企業主管優先參考的臉部部位為眼睛，尤其專注於眼神和面談時是否直視對方，若有面相學基礎的主管則會避免招募上下三白的人才；而大部分主管皆認為眉毛是眼睛的附屬五官部位，兩個部位是連動的，可同時看出一個人的情緒、個性特質。Holland職業類型論呈現的報告結果深受企業主管的喜愛，因其提供與面相學報告相同的準確度，且具有整合與簡明的特性，不僅協助企業主管為公司找到適合的人才，且為主管節省許多時間。
本研究將訪談結果分析與記錄，提出「AI面相招募系統」未來能改善的方向與方法，期能提供企業主管更準確、更有效率、更便利的判斷依據。

This study adopts semi-structured in-depth interviews to better understand the suggestions by and willingness of supervisors to implement the “AI-Physiognomy Recruiting System”. This system combines the facial recognition function in AI technology with physiognomy to identify various facial features and present the corresponding personality characteristics. At the same time, the study combines Holland’s RIASEC model with the “AI-Physiognomy Recruiting System”.
This research focuses on the two facial features, namely, the eyebrows and eyes, within the “AI-Physiognomy Recruiting System”. After carefully analyzing the results of the interviews, it is concluded that the eyes are the main priority among the facial features for supervisors, especially eye contact and whether the supervisor and the job candidate look at each other directly during the interviews. If the supervisors have a basic knowledge of physiognomy, they will avoid recruiting talents with certain features related to the whites of the eyes. Furthermore, most supervisors believe that the eyebrows serve as an accessory to the eyes, and the two features are linked. These two facial features can simultaneously reflect a person’s emotions and personality traits. The content of the part of Holland’s RIASEC model is most attractive to supervisors because it is briefer than the part of physiognomy and has the same accuracy. Providing supervisors quickly to read the integrated report, Holland’s RIASEC model not only help supervisors find suitable talents for the company but also save supervisors’’ time.
This study offers suggestions and directions for improving the “AI-Physiognomy Recruiting System” in the future. It is believed that the system can provide supervisors with a more accurate, efficient and convenient basis for recruiting suitable employees.

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