![]() ![]() However, they are notoriously bad at context and nuance ( 8) – two things critical for safe and effective patient care, which requires the implementation of medical knowledge, concepts, and principles in real-world settings. Algorithms perform relatively well on knowledge-based tests despite the lack of domain-specific training ChatGPT achieved ~ 66% and ~ 72% on Basic Life Support and Advanced Cardiovascular Life Support tests, respectively ( 5), and performed at or near the passing threshold on the United States Medical Licensing Exam ( 6, 7). As the inevitable implementation of this disruptive technology will have far-reaching consequences for medicine, science, and academic publishing, we need to discuss both the opportunities and risks of its use.ĪI has a tremendous potential to revolutionize health care and make it more efficient by improving diagnostics, detecting medical errors, and reducing the burden of paperwork ( 3, 4) however, chances are it will never replace physicians. ![]() Furthermore, considering that ChatGPT was generated by fine-tuning the GPT-3.5 model from early 2022 with supervised and reinforcement learning ( 2), the quality of the chatbot-generated content can only be improved with additional training and optimization. The hype surrounding ChatGPT is not unjustified: the model is (still) free, easy to use, and able to authentically converse on many subjects in a way that is almost indistinguishable from human communication. The OpenAI's chatbot allegedly gained more than 1 million users in the first few days after its launch and 100 million in the first 2 months, positioning itself as the fastest-growing consumer application in history ( 1). The release of ChatGPT, the latest large (175-billion-parameter) language model by San Francisco-based company OpenAI, prompted many to think about the exciting (and troublesome) ways artificial intelligence (AI) might change our lives in the very near future. ![]()
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