Workshop paper
Hyanghee Park, Daehwan Ahn, Kartik Hosanagar, Joonhwan Lee
Cite
Cite
APA
Click to copy
Park, H., Ahn, D., Hosanagar, K., & Lee, J. Your AI Boss Says, "You are Fired, but Your Colleague Got Promoted!"
Chicago/Turabian
Click to copy
Park, Hyanghee, Daehwan Ahn, Kartik Hosanagar, and Joonhwan Lee. Your AI Boss Says, &Quot;You Are Fired, but Your Colleague Got Promoted!&Quot; n.d.
MLA
Click to copy
Park, Hyanghee, et al. Your AI Boss Says, &Quot;You Are Fired, but Your Colleague Got Promoted!&Quot;
BibTeX Click to copy
@techreport{hyanghee-a,
title = {Your AI Boss Says, "You are Fired, but Your Colleague Got Promoted!"},
author = {Park, Hyanghee and Ahn, Daehwan and Hosanagar, Kartik and Lee, Joonhwan}
}
Abstract
Recently, Artificial intelligence (AI) has been used to enable efficient decision-making in managerial and business contexts ranging from employment to dismissal. However, to avoid employees’ antipathy towards AI, it is important to understand what aspect employees like and/or dislike about the AI. In this paper, we aim to identify how employees perceive current HR teams and futuristic AI’s work evaluation. Also, we explored what factor influences employees’ trust and acceptance in algorithmic decision-making. Our findings showed that employees have 1) uncomfortable feelings towards AI at first, and then 2) mixed feelings, along with 3) concerns for various issues related to the process of algorithmic decision-making. Based on our findings, we suggest design efforts and guidelines to utilize AI in fair and trustworthy ways.
Recently, Artificial intelligence (AI) has been used to enable efficient decision-making in managerial and business contexts ranging from employment to dismissal. However, to avoid employees’ antipathy towards AI, it is important to understand what aspect employees like and/or dislike about the AI. In this paper, we aim to identify how employees perceive current HR teams and futuristic AI’s work evaluation. Also, we explored what factor influences employees’ trust and acceptance in algorithmic decision-making. Our findings showed that employees have 1) uncomfortable feelings towards AI at first, and then 2) mixed feelings, along with 3) concerns for various issues related to the process of algorithmic decision-making. Based on our findings, we suggest design efforts and guidelines to utilize AI in fair and trustworthy ways.
