Artificial intelligence and medicine: an epistemological inquiry

Area of Science:

• Medical Epistemology
• Philosophy of AI

Background:

• Artificial intelligence (AI) is revolutionizing medicine, introducing non-human knowledge generation.
• This development necessitates a re-evaluation of medical epistemology and its philosophical foundations.
• The opacity of AI systems (the 'black box') and non-human knowledge logic pose significant challenges.

Purpose of the Study:

• To explore the epistemological and ethical implications of AI in medicine.
• To examine whether AI represents a paradigm shift in medical reasoning, as per Thomas Kuhn's framework.
• To address challenges of AI-generated knowledge, including opacity and potential epistemic monoculture.

Main Methods:

• Philosophical analysis using Immanuel Kant's four questions: 'What can I know?', 'What ought I to do?', 'What may I hope?', and 'What is the human being?'.
• Examination of epistemological disruptions caused by AI, specifically 'black box' systems and non-human knowledge.
• Discussion of potential feedback mechanisms and intelligibility restoration for AI-generated medical knowledge.

Main Results:

• AI in medicine introduces a novel form of understanding generated by non-human agents.
• The 'black box' nature of AI and its unique logic challenge traditional evidence-based medical reasoning.
• Kant's philosophical framework provides a lens to analyze AI's impact on medical knowledge and ethics.

Conclusions:

• AI in medicine necessitates a profound epistemological and ethical re-evaluation.
• Addressing AI's challenges requires building feedback mechanisms and ensuring intelligibility of machine-generated knowledge.
• The rise of AI intensifies the fundamental question of 'What is the human being?' in the context of medical practice.