Moralizing algorithmic knowledge: Chinese patients' tactics for integrating AI-generated advice into clinical...

Area of Science:

• Medical Informatics
• Human-Computer Interaction
• Sociology of Health

Background:

• Growing use of artificial intelligence (AI) in Chinese healthcare consultations.
• Challenges in integrating AI recommendations due to physician authority and potential resistance.
• Need to understand patient strategies for AI integration in clinical settings.

Purpose of the Study:

• To explore how patients strategically incorporate AI suggestions into medical consultations.
• To examine methods patients use to maintain doctor-patient harmony while utilizing AI.
• To investigate the impact of AI integration on clinical decision-making and trust.

Main Methods:

• Conducted in-depth interviews with 60 Chinese stakeholders (35 patients, 25 clinicians).
• Employed inductive thematic analysis for data coding and interpretation.
• Qualitative research approach to understand nuanced patient behaviors.

Main Results:

• Patients utilize four semantic strategies (provenance reframing, cue selection, modal attenuation, sequential embedding) to make AI outputs clinically acceptable.
• These strategies initially preserve physician-patient harmony and integrate AI knowledge.
• Over time, patients increasingly benchmark clinicians against AI, potentially prioritizing algorithmic judgment.

Conclusions:

• Proposes clinician-led, AI-augmented models for effective integration.
• Recommends standardized communication protocols and targeted clinician training.
• Emphasizes robust validation procedures to ensure AI complements professional judgment and maintains trust.