Ethical Application of Generative Artificial Intelligence in Medicine

Area of Science:

• Medical Informatics
• Artificial Intelligence in Healthcare
• Bioethics

Background:

• Generative artificial intelligence (AI) presents opportunities to transform healthcare, from diagnostics to personalized treatments.
• However, its rapid integration raises significant ethical concerns, including data integrity, patient safety, and oversight.
• Key challenges involve potential misinformation, lack of transparency in AI models, and regulatory gaps.

Purpose of the Study:

• To explore the ethical considerations and challenges associated with the integration of generative AI in healthcare.
• To highlight the necessity for robust oversight, transparency, and regulatory frameworks for AI in medicine.
• To discuss the potential impact of AI on patient care, data security, and the humanistic aspects of medicine.

Main Methods:

• Review of current literature and expert opinion on generative AI in healthcare.
• Analysis of ethical dilemmas, including data integrity, patient safety, and AI transparency.
• Examination of regulatory challenges and the implications of synthetic data.

Main Results:

• Generative AI risks misdiagnosis due to potential misinformation and lacks transparency, eroding trust.
• Concerns exist regarding patient data security, synthetic data validity, and ownership.
• AI may depersonalize care by streamlining administrative tasks, impacting the provider-patient relationship.

Conclusions:

• Generative AI in medicine requires strict standards for data security, transparency, and oversight, similar to institutional review boards.
• Developing interdisciplinary guidelines involving developers, clinicians, and ethicists is crucial.
• Careful adoption is essential to align AI with humanistic healthcare principles, ensuring patient safety and trust.