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Updated: Apr 30, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
Published on: June 13, 2025
Hierarchy and hope: Exploring AI's role in medicine through a thematic analysis of online discourse
Johan Pushani1, Sherwin Rajkumar1, Alishya Burrell2
1Department of Paediatrics, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada.
Abstract:
The healthcare community remains divided on the benefits of artificial intelligence (AI) in medicine. In this qualitative study, we sought to better understand the perceived opportunities and threats of AI among premedical students, medical students, and physicians. We conducted a thematic analysis on Reddit, a social platform where candid opinions are often shared. Posts from the r/premed, r/medicalschool, and r/medicine subreddits were searched using the terms "AI", "chatGPT", "openAI", and "artificial intelligence". We analyzed 2403 comments across 47 threads from December 2022 to August 2023. A coding scheme was developed manually following Braun and Clarke's (2006) framework, and common themes were extracted. The main themes identified centered on AI enhancement versus replacement. Careers perceived to be lower in the medical social hierarchy were considered most at risk of replacement. AI was thought to first replace non-medical jobs, followed by mid-levels, and then primary care and diagnostic specialties, with specialists and surgeons affected last. Some contributors emphasized that AI could never replace a physician's compassion and nuanced clinical judgment. Others viewed AI as a tool to enhance efficiency, particularly in tasks such as studying, note writing, screening, and triage. Although verifying the credentials of commenters on online forums poses a challenge, platforms like Reddit offer a valuable opportunity to understand nuanced attitudes and perceptions regarding AI in medicine. Online forums allow for a unique understanding of the impressions of AI in medicine. While AI was generally well-received, we identified a key finding: a socially hierarchical, biased form of thinking among healthcare professionals. The perpetuation of this biased mindset may contribute to role devaluation, mistrust, and collaboration challenges within healthcare teams-ultimately impacting patient care. To fully leverage AI's potential in medicine, it is critical to acknowledge and address potentially biased perceptions within the healthcare community.
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