Large language models in medical ethics: useful but not expert

Area of Science:

• Medical Ethics
• Artificial Intelligence
• Health Informatics

Background:

• Large language models (LLMs) are increasingly explored for applications in medicine.
• The intersection of LLMs and medical ethics presents novel research opportunities and challenges.

Purpose of the Study:

• To evaluate the performance of a specific LLM (GPT-4) in addressing medical ethics cases.
• To examine the epistemic limitations of LLMs in the context of medical ethics.
• To propose appropriate applications for LLMs within medical ethics.

Main Methods:

• Assessed GPT-4's responses to a range of medical ethics scenarios.
• Analyzed the LLM's ability to identify and articulate ethical issues.
• Examined the nature of expertise and limitations of LLM technology in this domain.

Main Results:

• GPT-4 can identify and articulate complex medical ethical issues.
• The LLM's proficiency in capturing the nuances of real-world ethical dilemmas requires further development.
• LLMs possess limitations that necessitate caution in their application to medical ethics decision-making.

Conclusions:

• LLMs show potential in medical ethics but should not be considered experts.
• Recommended applications include data mining of electronic health records and scientific literature for evidence synthesis.
• LLMs can serve as valuable educational tools to enhance ethical reasoning in medical professionals.