Claim Missing Document
Check
Articles

Found 1 Documents
Search

Human-Centered Artificial Intelligence in Police Human Resource Management: A Case Study of Polres Metropolitan Jakarta Utara Hendra Wijaya; Corry Yohana; Widya Parimita
International Journal Of Economics Social And Technology Vol. 5 No. 2 (2026): June, 2026
Publisher : Lembaga Riset Ilmiah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59086/ijest.v5i2.1533

Abstract

This study analyzes the implementation of Human-Centered Artificial Intelligence (HCAI) in police human resource management at Polres Metropolitan Jakarta Utara. The study responds to the growing use of artificial intelligence in HRM and the limited scholarly attention given to AI-HRM in police organizations as hierarchical, disciplinary, and public-service institutions. Using a qualitative exploratory case study design, the research examines how AI can support personnel administration, competency mapping, training needs analysis, performance evaluation, workload distribution, and evidence-based HR decision-making while preserving human judgment, procedural fairness, data protection, and organizational trust. Data were collected through document analysis, limited observation of HR-related administrative processes, and semi-structured inquiry with organizational actors relevant to HRM, data management, supervision, and personnel governance. Thematic analysis produced five interconnected themes: organizational readiness, human control, system transparency, algorithmic fairness, and personnel data protection as foundations of organizational trust. The findings show that AI should be positioned as a decision-support mechanism rather than an autonomous decision-maker, especially for high-impact decisions such as promotion, transfer, disciplinary guidance, integrity assessment, and career development. The study contributes to AI-HRM literature by extending the discussion from private-sector automation to public security organizations and by proposing a human-centered governance framework for ethical, secure, fair, and accountable AI-HRM implementation. Practically, the study recommends gradual implementation through data governance improvement, AI literacy, human-in-the-loop protocols, algorithmic audits, privacy safeguards, and clarification mechanisms for affected personnel.