AUTOMATED STRATEGIES FOR DEFINING A JOB INTERVIEW

AUTOMATED STRATEGIES FOR DEFINING A JOB INTERVIEW

Author
Luca LEZZERINI, POLIS University (Tirana, Albania)

Abstract
Personnel selection is a demanding task, especially when there are many candidates. As part of a broader industrial research project focused on experimental development, techniques for collecting requirements to inform the definition of a job interview process were examined. In practice, an AI asks a series of questions, according to a specific scheme, to people who meet particular profiles, and a set of requirements is derived from this, which is then used to interview the candidates. In the present study, we build upon the results of this research and explore the concepts of the AI engine that fulfils these requirements. The objective of this study is to critically evaluate the idea's potential and define how it can be effectively implemented. The methodology employed began with an analysis of the experimental development documents, from which only certain elements not subject to industrial secrecy are reported, followed by a literature review. Following this preliminary analysis, possible algorithmic and technological solutions were evaluated. These solutions were then discussed across various aspects, including ethical considerations and those related to the processing of personal data, to reach conclusions about their applicability. The final results indicate a high level of confidence in the feasibility of automating this phase of the selection process, but highlight critical ethical and GDPR compliance issues.