Human-Centered AI in Human Resource Development: Reframing Human–AI Collaboration, Trainer Roles, and Ethical Learning Design

Abstract

Artificial intelligence is reshaping workplace learning, yet HRD lacks an integrated explanation of how AI redistributes developmental authority, feedback legitimacy, and trainer accountability. This paper advances the Human–AI Synergy Framework for HRD, an integrative role-and-governance model linking role clarity, shared control, and governance safeguards to learner trust and perceived procedural fairness. It defines emotionally intelligent AI as learning support that uses emotion-related signals to adapt pacing, feedback, or scaffolding, and positions supportive adaptation and high-stakes emotion inference along a risk continuum shaped by consequentiality, voluntariness, verifiability, data repurposing, and contestability. Integrative theory synthesis reveals three tensions: support versus surveillance, personalization versus opacity, and automation versus accountability. The framework positions trainers as accountable decision makers, AI as bounded advisory support, and learners as participants with voice and recourse. Its central claim is that transparency strengthens trust and perceived procedural fairness only when meaningful contestability exists; otherwise, it may heighten perceptions of surveillance and control.