Feeling Like a Number: How AI’s Neglect of Uniqueness Undermines User Acceptance in Online Medical Consultations

Artificial intelligence (AI) promises greater efficiency and accessibility in online medical consultation (OMC). However, user acceptance, particularly among older adults, remains low. This paradox is not fully explained by cognitive-centric models like the Technology Acceptance Model (TAM). This study investigates uniqueness neglect as a critical psychological barrier induced by standardized algorithmic interactions. Two between-subjects experiments manipulated consultation type (AI vs. human doctor) to induce differential perception of uniqueness neglect. Results revealed that AI-doctor consultation triggered stronger uniqueness neglect, which reduced acceptance through serial mediators of perceived usefulness and emotional response. The study also provides evidence that activating higher perceived usefulness is an effective intervention. Theoretically, our findings reveal a cognitive-affective serial mechanism extending beyond utilitarian model(s) of resistance to AI services. Practically, OMC platforms should design AI interactions that proactively affirm functional value to compensate for standardized procedure.