Generative AI and medical oncologists: Be curious, but cautious!
Abstract
The purpose of this editorial is to explore the potential and risks of using AI in the medical field, particularly in oncology. We describe the history of AI from its origins to the present day, highlighting its positive aspects and potential for each type of AI (expert system, machine learning, generative AI). Technologies like ChatGPT are increasingly being used across various domains; however, without proper caution, they can give rise to phenomena such as 'AI hallucinations'-responses that may appear precise, detailed, clear, and logical, but are in fact entirely fabricated and unfounded, potentially confusing those who read them. We want to caution oncologists against the unconditional use of these technologies, where human input remains still essential both in interpreting the responses and in formulating the questions.
How strong is the evidence?
Evidence Hub reads this as a editorial / letter, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.
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