Navigating Ethical Dilemmas Of Generative AI In Medical Writing

摘要

The history of humankind is marked by revolutionary inventions that completely transformed the quality and trajectory of human lives. Revolution and innovation are dynamic processes that have and will continue, at an increasing pace due to discoveries and inventions. Like the steam engine in the 18th century, electricity in the 19th century, and the Internet at the cusp of the 20th and 21st centuries, the modern era is undergoing a new revolution with the advent of Artificial Intelligence (AI). AI is a field of computer science which deals with the development of programs or computational models that are inspired by the human brain’s ability to learn and adapt.1 Perhaps the most prominent advancement AI contributes is generative AI, which has led to the development of robotic “human-like” tools that can generate text, audio, images, and even video with a simple prompt. The widespread and mainstream use of some of these tools, namely ChatGPT, Google Gemini, and Perplexity AI, has revolutionised almost all walks of life, from industry to academia.2 The scope of this article will be limited to the implications of generative AI in academic research writing, particularly in the field of medicine. Generative AI in Medical Writing Generative AI tools or “chatbots” combine the adaptive learning capabilities of deep learning algorithms and natural language processing, resulting in a virtual assistant or aide that is capable of answering queries, following commands, and improving its responses according to the vast data available on the Internet in addition to user responses.3 This has allowed the accomplishment of various complex tasks within seconds that would otherwise require hours of trial and error. The speed with which generative AI chatbots solve problems is one of the main reasons behind their remarkable success among the general public. Moreover, their correct grammar and comprehension skills make them a very attractive writing tool, especially for non-native English speakers. However, all of these benefits are not without their pitfalls. Data Hallucinations The tendency of generative AI chatbots to create false information or “data hallucinations” has been a cause of grave concern in the field of academia.4 Although ChatGPT declares that “it can make mistakes and users should consider checking important information”, unregulated false results generated by chatbots can significantly degrade the integrity and authenticity of medical research, which is a field characterized by strict ethical and moral guidelines. Additionally, AI chatbots are trained using data that is available on the web, where misinformation itself is abundant. Online resources like Wikipedia and WebMD, while mostly accurate, are generally not considered clinically or medically credible. Even though academic journals are trying to regulate the misuse of generative AI in medical writing by introducing AI detection as a regular part of the review process, the burden of upholding scientific accuracy and integrity still falls on the researcher’s shoulders. Biasedness Another aspect of AI tools which impacts their efficiency is the biasedness that can emerge by being repeatedly trained on the same type of information.5 By emulating the human brain’s ability to remember, understand, and adapt according to new information, AI also inherits a “flaw” of the human mind of being influenced or becoming biased by recurrent exposure to specific types of information. This indicates that the resources used by AI chatbots need to be supervised and regulated to ensure that the bots do not provide monotonous responses. Privacy and Security Concerns The innate programming of generative AI chatbots to store the information that is provided to them also raises concerns regarding their safety and security. While this feature serves to improve the performance of these tools according to user input and requirements, it also fuels the debate about privacy breaches and cybersecurity is