[3N5-GS-11] AI and Society

[3N5-GS-11-05] Empirical Study of Human Resource Assessment Utilizing Bayesian Network, and Development of Matching Optimization System

〇Hiroshi Sakuma^1,2, Rika Hayahara³, Kazuya Yamashita³, Yoichi Motomura³ (1. The University of Tokyo, 2. Osaka University, 3. National Institute of Advanced Industrial Science and Technology)

Keywords:Bayesian Network, Matching Optimization, Human Resource Assessment, Empirical Study

The demand for professionals skilled in artificial intelligence (AI) is increasing rapidly. As such, it is imperative to assess human resources based on their aptitude, rather than solely relying on self-assessment. To meet this need, we have designed a diagnostic system that estimates applicants' personalities and potential abilities, specifically tailored for the AI domain. Our system was developed using the "POSEIDON" development environment, which facilitates the construction of Bayesian networks and the collection and updating of data. We analyzed assessment items obtained from companies seeking AI talent and compared them with the skill sets published by the Japan Data Scientist Society. Empirical research was conducted at the 3rd Symposium on Industrial applications of Artificial Intelligence (SIAI 2023). To enhance the response rate, we employed innovative designs, such as interactive user interfaces and visualization of results that feature anthropomorphic characters. These methods are not limited to the AI field but can be adapted for use in any domain.