Abstract
PurposeIn 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/approachThis 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.FindingsAs 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/valueThe 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.
Subject
Library and Information Sciences,Computer Science Applications,Information Systems
Reference60 articles.
1. Big data's disparate impact;California Law Review,2016
2. The fourth industrial revolution and education;South African Journal of Science,2018
3. LinkedIn and Facebook in Belgium: the influences and biases of social network sites in recruitment and selection procedures;Social Science Computer Review,2011
4. Calders, B. and Žliobaitė, I. (2013), “Why unbiased computational processes can lead to discriminative decision procedures”, in Custers, B., Calders, T., Schermer, B. and Zarsky, T. (Eds), Discrimination and Privacy in the Information Society, Springer, Heidelberg, pp. 43-60.
5. The relationship between early recruitment-related activities and the application decisions of new labor-market entrants: a brand equity approach to recruitment;Journal of Applied Psychology,2002
Cited by
330 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献