A multi-stakeholder ethical framework for AI-augmented HRM

被引:10
|
作者
Prikshat, Verma [1 ]
Patel, Parth [2 ]
Varma, Arup [3 ]
Ishizaka, Alessio [4 ]
机构
[1] Cardiff Metropolitan Univ, Llandaff Campus, Cardiff, Wales
[2] Australian Inst Business, Discipline Management & Human Resources, Adelaide, SA, Australia
[3] Loyola Univ, Chicago, IL 60611 USA
[4] NEOMA Business Sch, Informat Syst Supply Chain Management & Decis Sup, Mont St Aignan, France
关键词
Stakeholder; Ethics; Artificial intelligence; Human resource management; HUMAN-RESOURCE MANAGEMENT; ARTIFICIAL-INTELLIGENCE; PERSONAL DATA; DECISION-MAKING; INTERSECTIONALITY; TECHNOLOGY; PROFESSIONALS; PERSPECTIVE; CHALLENGES; SALIENCE;
D O I
10.1108/IJM-03-2021-0118
中图分类号
F24 [劳动经济];
学科分类号
020106 ; 020207 ; 1202 ; 120202 ;
摘要
Purpose This narrative review presents a multi-stakeholder ethical framework for AI-augmented HRM, based on extant research in the domains of ethical HRM and ethical AI. More specifically, the authors identify critical ethical issues pertaining to AI-augmented HRM functions and suggest ethical principles to address these issues by identifying the relevant stakeholders based on the responsibility ethics approach. Design/methodology/approach This paper follows a narrative review approach by first identifying various ethical/codes/issues/dilemmas discussed in HRM and AI. The authors next discuss ethical issues concerning AI-augmented HRM, drawing from recent literature. Finally, the authors propose ethical principles for AI-augmented HRM and stakeholders responsible for managing those issues. Findings The paper summarises key findings of extant research in the ethical HRM and AI domain and provides a multi-stakeholder ethical framework for AI-augmented HRM functions. Originality/value This research's value lies in conceptualising a multi-stakeholder ethical framework for AI-augmented HRM functions comprising 11 ethical principles. The research also identifies the class of stakeholders responsible for identified ethical principles. The research also presents future research directions based on the proposed model.
引用
收藏
页码:226 / 250
页数:25
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