Navigating the Impact of Artificial Intelligence on Medical Writing

Abstract

Artificial Intelligence (AI) has become integral to all walks of life. AI dominates multiple fields, and we are all affected by the convenience associated with AI and the scams committed using AI. AI is transforming data collection, analysis, transcription, and dissemination in medical writing. Medical literature has traditionally been very conservative and regulated mainly through peer review. AI is gradually disrupting the traditional pattern followed in medical literature. To highlight the ingress of AI in medical writing, we decided to publish a Pro-Con debate in this journal issue. The impact of AI on medical writing is profound and multifaceted. Many medical writers and publishers have embraced AI-powered tools for grammar and style checking, plagiarism detection, and reference management. AI algorithms can identify potential plagiarism by comparing submitted manuscripts against a vast database of existing publications. AI tools are also widely used to develop automated summaries, analyze data, interpret findings, perform semantic searches, review literature, and translate.[1] AI tools can generate automated reports. Popular AI-powered tools include large language models (LLM) such as Grammarly, chatbots (ChatGPT), image creators, and automated literature reviews (IBM Watson Discovery, Dimensions AI).[2] The ghostwriter potential of ChatGPT and related AI tools has been widely discussed and debated.[3] The evolution toward using LLM in Natural Language Processing applications has enabled computers to understand, interpret, manipulate, and generate human language. Once an LLM is trained, the AI can be used for text generation, translation, content summarization, rewriting content, classification, and categorization.[4] Many tools have been developed to assist medical research and writing in daily practice. Research assistants (IRIS.AI and Scite.ai) can categorize scientific articles on a visual map and track the total number of citations for a given article.[5,6] AI tools can absorb existing text and data but cannot create new ideas. However, to date, AI tools still cannot produce high-quality reviews with rigorous, evidence-based medicine standards. Traditionally, medical writers have relied on their expertise and experience to produce high-quality content. AI tools can significantly enhance the efficiency of medical writing. This capability allows medical writers in anesthesiology to focus on critical thinking and interpretation rather than spending excessive time on data collection. AI systems can reduce human error using machine learning algorithms trained in extensive medical literature. AI can provide accurate references, ensure adherence to guidelines, and maintain consistency in terminology.[7] Precision and clarity of medical literature are crucial, as they influence patient safety, clinical decision-making, and the advancement of clinical practices. This is particularly important in anesthesiology, where precise language is vital for conveying complex concepts. AI can analyze patient data and outcomes to generate insights that inform medical writers. It can identify trends in anesthesia practices or patient responses, allowing writers to present data-backed recommendations. Writers can incorporate real-world evidence into their documents, enhancing the relevance and applicability of their content. AI technologies can facilitate the dissemination of medical information,[8] which is essential in promoting informed decision-making in anesthesiology. Corrupt environments in medicine and science are familiar worldwide. The need to “publish or perish” to climb the academic ladder has contributed to research waste, with numerous low-quality and fake papers. These scientists may use AI to build spurious CVs with fraudulent papers.[9] Even scientists at prestigious institutions may be involved in this practice to boost their CVs. AI-generated content is based on pre-published data and lacks original thought and creativity. AI can never replace the critical thinking and contextual understanding that humans possess. Reliance on AI-generated content may lead to a decline in the quality of medical writing. I want to quote my experience with AI in gathering information on the history of resuscitation. The tool referenced that Archimedes was the first person to describe resuscitation, something unbelievable. After a determined and prolonged search, I traced the source and found it unrecognized. AI cannot differentiate authentic from fraudulent data! These tools often fail to answer questions correctly and can generate fraudulent—albeit superficially high-quality—medical articles. Unlike the human brain, AI cannot articulate complex inductive reasoning, which is essential for coherent thinking.[10] While using AI, medical writers should check the accuracy of the text. AI medical writing raises ethical questions regarding authorship, accountability, and potential bias. Who should take responsibility for an AI-generated research article? If AI algorithms are trained on biased data, they may perpetuate these biases in writing, leading to skewed representations of anesthetic practices. The use of AI in medical writing also raises regulatory concerns. Regulatory bodies must establish guidelines for using AI-generated content in clinical trials, publications, and educational materials.[11] Ensuring compliance with ethical standards and maintaining the integrity of medical writing in anesthesiology is crucial for patient safety and trust in the healthcare system. The debate on including AI in authorship sparked many discussions in the scientific community. All leading scientific journals opine that AI does not fulfill the necessary criteria to be recognized as an author. The International Committee of Medical Journal Editors recently recommended the exclusion of AI as an author, as it does not meet the “authorship” criteria for the work’s accuracy, integrity, and originality.[12] Journals also specify that the authors should disclose whether they used AI technology to produce the submitted work at submission. If applicable, authors should describe how they used it in both the cover letter and the acknowledgment. Physicians must examine AI’s benefits, challenges, and implications in medical writing. We must harness its potential and, at the same time, ensure high medical communication standards and ethics. In the future, medical writing is bound to be a collaborative effort of AI and human writers. AI can assist in the initial drafting and data analysis, while human writers provide expertise, context, and ethical considerations. This symbiotic relationship can enhance the quality and efficiency of medical writing. Medical writers must keep pace with advancements to leverage AI tools effectively and stay informed about ethical and regulatory considerations.

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