AI in Business and Society
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Paper Number
2166
Paper Type
Completed
Description
The increasing use of AI decision systems in recruitment processes has created challenges, including potential resistance from job applicants. To address this issue, drawing on organizational justice theory, we identify dimensions of AI explanations in the employment context and examine their impact on job applicants' perceptions of organizational justice. We conducted an experiment to understand applicants' reactions to AI versus HR managers without explanations and examined the impact of AI explanations on organizational justice perceptions and acceptance intention. Our findings show that without explanation, AI is perceived as lower organizational just and acceptance intention compared to HR managers. Organizational justice mediates the effects between outcome/process explanations of AI on acceptance intention. However, outcome explanations have a stronger impact compared to process explanations. Our study contributes to understanding explanation structures for AI-based recruitment and offers practical implications for developing explanations that improve the perceived justice of AI recruitment systems.
Recommended Citation
Tian, Yuyang; Claudy, Marius; Xu, David (Jingjun); and LIAO, Stephen Shaoyi, "Exploring the Role of AI Explanations in Delivering Rejection Messages: A Comparative Analysis of Organizational Justice Perceptions between HR and AI" (2023). ICIS 2023 Proceedings. 21.
https://aisel.aisnet.org/icis2023/aiinbus/aiinbus/21
Exploring the Role of AI Explanations in Delivering Rejection Messages: A Comparative Analysis of Organizational Justice Perceptions between HR and AI
The increasing use of AI decision systems in recruitment processes has created challenges, including potential resistance from job applicants. To address this issue, drawing on organizational justice theory, we identify dimensions of AI explanations in the employment context and examine their impact on job applicants' perceptions of organizational justice. We conducted an experiment to understand applicants' reactions to AI versus HR managers without explanations and examined the impact of AI explanations on organizational justice perceptions and acceptance intention. Our findings show that without explanation, AI is perceived as lower organizational just and acceptance intention compared to HR managers. Organizational justice mediates the effects between outcome/process explanations of AI on acceptance intention. However, outcome explanations have a stronger impact compared to process explanations. Our study contributes to understanding explanation structures for AI-based recruitment and offers practical implications for developing explanations that improve the perceived justice of AI recruitment systems.
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