The Scalpel and the Algorithm: Navigating the Ethical Landscape of AI in Medical Writing

Abstract

The rapid advancement of artificial intelligence (AI), particularly large language models (LLMs) like ChatGPT, has sparked excitement and apprehension within the medical community. While the allure of automated medical writing is undeniable, we must proceed cautiously, acknowledging the ethical implications of integrating these powerful tools into our practice. LLMs offer enticing possibilities, from streamlining literature reviews to drafting manuscripts, but their limitations and potential pitfalls demand careful consideration. As Fingerhut and Winter aptly warn, "AI in medical writing has limitations and dangers. The medical community must be aware of them."¹

One of the most significant concerns is the potential erosion of critical thinking. LLMs, trained on vast datasets, excel at mimicking human language and generating seemingly coherent text. However, they lack the nuanced understanding and contextual awareness crucial for scientific reasoning. As Sharma et al. points out, "AI tools cannot understand new information, generate insights, or perform deep analysis, which are essential for meaningful scientific discourse."2 Over-reliance on these tools can lead to cognitive offloading, where individuals delegate critical thinking tasks to the algorithm, potentially hindering the development of essential analytical skills.4 This is particularly concerning for trainees and early-career professionals, who may become overly dependent on AI, bypassing the rigorous process of independent learning and critical evaluation.^1-3