Balancing AI and Human Judgement in HR and ER

Abstract

The increasing use of artificial intelligence (AI) in human resources (HR) and employment relations (ER) has transformed organisational decision-making processes, particularly in areas such as recruitment, performance management, and disciplinary procedures. While AI offers significant efficiency benefits, its deployment raises significant ethical concerns that remain insufficiently explored within the context of human resource management and employment relations. This thesis examines the ethical implications of using AI in HR and ER, with a focus on issues of fairness, discrimination, accountability, transparency, and explainability. Using a qualitative research approach, this study draws on semi-structured interviews with HR and ER professionals, supported by an analysis of relevant academic literature and the overarching theoretical framework of organisational justice. Adopting an interpretivist perspective, the study explores how practitioners construct and justify ethical decision-making in relation to AI-supported systems within their organisational contexts. Key concerns include algorithmic bias, lack of transparency in automated decision-making, reduced employee voice, and challenges in assigning accountability when AI-supported decisions negatively affect a decision or employees. The findings suggest that HR and ER practitioners adopt a position of cautious optimism towards AI, recognising its potential value while emphasising the importance of human oversight, accountability, and fairness. The study highlights the need for clearer organisational guidelines, greater human oversight, and stronger ethical and AI literacy among HR and ER practitioners to ensure adoption of AI aligns with both legal obligations and ethical employment standards. The research highlights the need for clearer organisational guidelines, greater transparency, and stronger ethical and AI literacy among HR and ER practitioners to support the responsible adoption of AI.