Human-Centered Artificial Intelligence in Human Resource Management: The Effect of Perceived AI Fairness and Algorithmic Trust on Work Engagement

Ahmad Shalahuddin; Nur Afifah

doi:10.61255/jeemba.v4i5.1389

Authors

Ahmad Shalahuddin Universitas Tanjungpura
Nur Afifah Universitas Tanjungpura

DOI:

https://doi.org/10.61255/jeemba.v4i5.1389

Keywords:

Perceived AI Fairness, Algorithmic Trust, Work Engagement, Human-Centered AI, Human Resource Management

Abstract

This study examines whether Perceived AI Fairness is associated with Work Engagement through Algorithmic Trust in a Human-Centered Artificial Intelligence in Human Resource Management context. A quantitative cross-sectional survey involved 100 employees in Pontianak who reported direct exposure to an AI-enabled HR process containing automated scoring, prediction, ranking, natural-language interaction, or algorithmic recommendation; employees exposed only to ordinary administrative digitization were not eligible. Data were analyzed using PLS-SEM. Perceived AI Fairness was positively associated with Algorithmic Trust and Work Engagement, while Algorithmic Trust was positively associated with Work Engagement. The positive direct association and the statistically significant indirect pathway are consistent with complementary mediation, but they do not establish a causal transmission mechanism because the data are cross-sectional and self-reported. Recommendations concerning explainability, algorithmic audits, appeal mechanisms, meaningful human review, preservation of dignity, and limits on algorithmic authority are presented as theory-informed governance implications rather than as constructs directly tested by the survey.

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