Decoding ChatGPT’s ‘impact’ on the future of healthcare

Abstract

Neural networks with many computational layers have been used as deep learning models to solve real-world problems.[1] Mostly composed of a network of artificial neurons, these are trained on existing datasets to learn novel patterns in applications ranging from image processing and speech recognition to human-like navigation of autonomous cars.[2] One area that has seen immense progress is natural language processing, which uses a specific class of deep learning model, known as a transformer,[3] which is scalable with respect to model size and training data. These language models have outperformed other deep learning architectures such as recurrent neural networks,[1] which were traditionally used for natural language processing tasks.[4] More recently, language models have formed the backbone of generative artificial intelligence (AI) tools, which are trained over huge, often publicly available datasets to generate human-like responses on diverse topics. Two prominent examples are ChatGPT, which generates human-like responses to text prompts, and Stable Diffusion, which generates images based on text prompts. ChatGPT is a large language model developed by OpenAI, designed to understand natural language and communicate with humans via a text-based conversational interface.[5] Derived from their GPT-3.5, it has been trained on a tremendous corpus of textual data extracted from the Internet, including books, articles, websites, and software repositories, and then refined using a technique known as reinforcement learning with human feedback, whereby human supervisors encouraged the model to understand instructions and be more conversational. Presumably because of the broad training corpus used over the billions of parameters making up the underlying GPT models, ChatGPT has demonstrated significant capabilities in a diverse range of tasks. Due to the strength of its prose, ChatGPT is capable of passing tests and examination questions from the law, medical, programming,[6–8] and creative writing and literature domains. Applications may even be built atop it, for instance using its outputs to control robotics.[9,10] These capabilities are making ChatGPT an extremely popular tool: since its release in November 2022, it is estimated that ChatGPT has already reached more than 100 million unique users,[11] making it possibly the fastest growing consumer application in the last 20 years. Such statistics cannot be ignored—the rise of generative AI such as ChatGPT has been meteoric. This naturally poses the question: What does this mean for professionals such as those who work in the healthcare sector? The answer to this question was explored by Parikh et al.[12] who surveyed 210 professionals (157, 74.8% from healthcare) with the goal of gauging their opinion on this matter by circulating a short questionnaire comprising nine multiple choice questions. They found that within this group, there was already significant awareness of ChatGPT and its potential (approx. 63% awareness) and a sizeable minority had already tried asking questions (approx. 42%) to this platform. When asked how much ChatGPT would revolutionize their fields, the majority from both groups expected the change to be less than 50%. Taking a step further and characterizing this change, medical professionals were more likely to believe that any impact of ChatGPT would be positive (approx. 52%), versus other professionals (approx. 38%). Few participants planned to make any significant changes to their career plans in 2023 based on the impact of ChatGPT like generative AI. We may start by pointing out some positives of this study. First, the study shows that there is considerable awareness regarding generative AI among healthcare professionals. Second, an early publication on this topic, in a medical journal, will help to enhance the awareness among readers of this journal, who are most likely going to be healthcare professionals. However, the major challenges in such a study