As Artificial Intelligence becomes increasingly integrated into healthcare, it is essential for medical professionals to understand the ethical implications of these technologies. This paper proposes the creation of a specialized AI ethics course tailored specifically for healthcare professionals. The course utilizes an innovative framework that combines the interactive capabilities of OpenAI’s ChatGPT-4o with the comprehensive learning management features of the Moodle e-learning platform to deeply engage with complex ethical dilemmas in AI. This hybrid approach aims at ensuring that healthcare students and professionals not only gain theoretical knowledge but also develop practical skills in ethical decision-making, empowering them to navigate AI-related challenges in healthcare responsibly and effectively, while maintaining the highest standards of patient care and ethical practice.

Design an Hybrid Educational Framework for AI Ethics in Healthcare: Leveraging LLMs and E-Learning Platforms to Empower Medical Students (full paper)

Giacomo Balduzzi
;
Manuel Striani
2024-01-01

Abstract

As Artificial Intelligence becomes increasingly integrated into healthcare, it is essential for medical professionals to understand the ethical implications of these technologies. This paper proposes the creation of a specialized AI ethics course tailored specifically for healthcare professionals. The course utilizes an innovative framework that combines the interactive capabilities of OpenAI’s ChatGPT-4o with the comprehensive learning management features of the Moodle e-learning platform to deeply engage with complex ethical dilemmas in AI. This hybrid approach aims at ensuring that healthcare students and professionals not only gain theoretical knowledge but also develop practical skills in ethical decision-making, empowering them to navigate AI-related challenges in healthcare responsibly and effectively, while maintaining the highest standards of patient care and ethical practice.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11579/202182
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