Ethical Considerations and Fundamental Principles of Large Language Models in Medical Education: Viewpoint

Area of Science:

• Medical Education
• Artificial Intelligence Ethics
• Large Language Models

Background:

• Large language models (LLMs) offer potential in medical education but raise significant ethical concerns.
• Challenges include AI hallucinations, data bias, privacy risks, lack of transparency, and issues with emotional intelligence and academic integrity.

Purpose of the Study:

• To explore the ethical challenges of LLM application in medical education.
• To analyze existing AI legal and ethical frameworks and their limitations.
• To propose a unified ethical framework for responsible LLM integration in medical education.

Main Methods:

• Viewpoint article analyzing ethical and legal challenges.
• Review of existing AI ethical and legal frameworks.
• Proposal of a new ethical framework based on 8 fundamental principles.

Main Results:

• Identified ethical challenges in LLM development and application within medical education.
• Highlighted limitations of current AI frameworks for LLM integration.
• Proposed an 8-principle ethical framework for responsible LLM use.

Conclusions:

• A unified ethical framework is crucial for safe and responsible LLM implementation in medical education.
• The proposed framework ensures a balance between technological advancement and ethical safeguards.
• This approach promotes fairness, patient safety, and an equitable educational environment.