國立虎尾科技大學 |

Human Resource Professionals' Perceptions of Trust in Explainable Artificial Intelligence Hiring Software /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Human Resource Professionals' Perceptions of Trust in Explainable Artificial Intelligence Hiring Software // Jason Richard Powell.
Author:	Powell, Jason Richard,
Description:	1 electronic resource (396 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
Contained By:	Dissertations Abstracts International86-03B.
Subject:	Information technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31557236
ISBN:	9798384425595

Human Resource Professionals' Perceptions of Trust in Explainable Artificial Intelligence Hiring Software /
Powell, Jason Richard,

Human Resource Professionals' Perceptions of Trust in Explainable Artificial Intelligence Hiring Software /Jason Richard Powell. - 1 electronic resource (396 pages)

Source: Dissertations Abstracts International, Volume: 86-03, Section: B.

The rapid integration of artificial intelligence (AI) in hiring processes, particularly in explainable AI (XAI) hiring software, presents both opportunities and challenges for managing human resources (HR). The problem this study addressed is that recruiters and HR professionals distrust the accuracy of data produced by AI and the lack of control provided by AI-powered software (Johnson et al., 2022). The purpose of this qualitative case study was to investigate recruiters' and HR professionals' perceptions of trust and control in XAI-capable hiring software, the factors contributing to their distrust, and how doubts impacted decision-making processes in recruitment. Employing the Technology Acceptance Model (TAM) and considering the Artificial Intelligence - Technology Acceptance Model (AI-TAM) as theoretical frameworks, this study explored HR professionals' decision-making processes, trust factors in XAI-driven recruitment software, and perceived transparency of AI algorithms. Through semi-structured interviews with 15 HR professionals across various organizations in the United States, thematic analysis revealed a complex interplay of trust and control perceptions. The findings highlighted the critical role of explainability and transparency in fostering trust, the need for control mechanisms to ensure the ethical use of AI in hiring, and the potential biases that may arise from reliance on AI systems. The study contributed to the literature on AI in HR by providing empirical insights into HR professionals' perceptions, underscoring the importance of developing XAI systems that are technologically advanced, ethically sound, and user-friendly.

English

ISBN: 9798384425595Subjects--Topical Terms:

559429
Information technology.
Subjects--Index Terms:

Control

Human Resource Professionals' Perceptions of Trust in Explainable Artificial Intelligence Hiring Software /
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520 $a The rapid integration of artificial intelligence (AI) in hiring processes, particularly in explainable AI (XAI) hiring software, presents both opportunities and challenges for managing human resources (HR). The problem this study addressed is that recruiters and HR professionals distrust the accuracy of data produced by AI and the lack of control provided by AI-powered software (Johnson et al., 2022). The purpose of this qualitative case study was to investigate recruiters' and HR professionals' perceptions of trust and control in XAI-capable hiring software, the factors contributing to their distrust, and how doubts impacted decision-making processes in recruitment. Employing the Technology Acceptance Model (TAM) and considering the Artificial Intelligence - Technology Acceptance Model (AI-TAM) as theoretical frameworks, this study explored HR professionals' decision-making processes, trust factors in XAI-driven recruitment software, and perceived transparency of AI algorithms. Through semi-structured interviews with 15 HR professionals across various organizations in the United States, thematic analysis revealed a complex interplay of trust and control perceptions. The findings highlighted the critical role of explainability and transparency in fostering trust, the need for control mechanisms to ensure the ethical use of AI in hiring, and the potential biases that may arise from reliance on AI systems. The study contributed to the literature on AI in HR by providing empirical insights into HR professionals' perceptions, underscoring the importance of developing XAI systems that are technologically advanced, ethically sound, and user-friendly.
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