Artificial intelligence video interviewing for employment: perspectives from applicants, companies, developer and academicians

Purpose In 2018, an artificial intelligence (AI) interview platform was introduced and adopted by companies in Korea. This study aims to explore the perspectives of applicants who have experienced an AI-based interview through this platform and examines the opinions of companies, a platform developer and academia. Design/methodology/approach This study uses a phenomenological approach. The participants, who had recent experience of AI video interviews, were recruited offline and online. Eighteen job applicants in their 20s, two companies that have adopted this interview platform, a software developer who created the platform and three professors participated in the study. To collect data, focus group interviews and in-depth interviews were conducted. Findings As a result, all of them believed that an AI-based interview was more efficient than a traditional one in terms of cost and time savings and is likely to be adopted by more companies in the future. They pointed to the possibility of data bias requiring an improvement in AI accountability. Applicants perceived an AI-based interview to be better than traditional evaluation procedures in procedural fairness, objectivity and consistency of algorithms. However, some applicants were dissatisfied about being assessed by AI. Digital divide and automated inequality were recurring themes in this study. Originality/value The study is important, as it addresses the real application of AI in detail, and a case study of smart hiring tools would be valuable in finding the practical and theoretical implications of such hiring in the fields of employment and AI.

Automated summary

The study found that AI-based interviews are more efficient than traditional interviews, but there is a concern about data bias. Applicants generally believe that AI interviews are superior to traditional evaluation processes, but some express dissatisfaction with being evaluated by AI. Digital divide and automated inequality are recurring themes in this study.