We need to add prompt engineering education to optimize generative artificial intelligence in medicine

DJT Gonzalez, MB Djulbegovic, H Bair - Academic Medicine, 2024 - journals.lww.com
Academic Medicine, 2024journals.lww.com
To the Editor: We read the comments by Burke and Gwillim with great interest. 1 Recent
advancements in artificial intelligence (AI) have resulted in increased applications in various
areas of medicine, including mentorship and education. Although AI-based mentorship can
mitigate time limitations of mentors, we must ensure that these mentorship models do not
propagate harmful stereotypes. It remains vital for educators to ensure equitable use and
access of these tools for all learners; biases in education lead to biases in practice. There …
To the Editor: We read the comments by Burke and Gwillim with great interest. 1 Recent advancements in artificial intelligence (AI) have resulted in increased applications in various areas of medicine, including mentorship and education. Although AI-based mentorship can mitigate time limitations of mentors, we must ensure that these mentorship models do not propagate harmful stereotypes. It remains vital for educators to ensure equitable use and access of these tools for all learners; biases in education lead to biases in practice.
There has been growing popularity within academic medicine of AI-assisted tools, such as ChatGPT, that may enhance learner experiences by addressing specific queries and synthesizing information into digestible formats. 2 These tools may enhance mentorship by providing realtime feedback and presenting trainees with a safe space to satisfy their curiosities. Yet, in order to provide learners with accurate training, researchers and educators must ensure that these tools are equitable; current AI models frequently assert falsehoods as factual, 2 and have been shown to perpetuate racial biases by promoting inaccurate and harmful racebased medicine. 3
Lippincott Williams & Wilkins
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