Summary
This article organizes, around three questions, how HR departments, which deal with people and organizations, are using artificial intelligence. The first is the drivers. The authors cite the desire to escape the perception of HR as a department that only spends money, the move to supplement decision-making that relied only on intuition with data, and the demand for greater fairness. The second is the cases. In hiring, AI is used for evaluating personal statements, AI interviews, support for writing job postings, and chatbots, and attempts continue in promotion, evaluation, placement, and turnover prediction. The article also introduces cases in which a prediction model was built and the organization then decided not to use it. The third is the points to watch. AI learns even the bias contained in past human judgments, and the article concludes that what can be left to technology must be told apart from what people must take part in.
Key points
- The drivers behind HR departments’ attention to AI are cost reduction, data-based decision-making, and stronger fairness.
- AI began to be used first in recruitment and selection, where costs are most visible.
- In promotion and evaluation, there are cases where a prediction model was technically possible but was not adopted on the grounds that people should decide.
- AI trained on past data can repeat biases such as gender discrimination as they are.
- The boundaries between areas to leave to AI, areas to use it as an aid, and areas where people decide entirely must be examined continually.
Citation
- 저자: 김성준, 이중학, 채충일
- 연월: 2020년 가을
- 제목: 인사(HR) 분야의 인공지능 활용
- 매체: KISDI AI Outlook
- 권호·쪽: 2020년 가을 (Vol. 3), 31–49
Citation
@online{2020,
author = {},
title = {인사(HR) {분야의} {인공지능} {활용}},
date = {2020-09-01},
url = {https://chadchae.github.io/posts_white_paper/2020-09-01-artificial-intelligence-in-hr-kisdi/artificial-intelligence-in-hr-kisdi.html},
langid = {en}
}