The Enduring Promise of Personalising Patient Preference Prediction.

Area of Science:

• Bioethics
• Artificial Intelligence
• Medical Decision-Making

Background:

• Healthcare decision-making for incapacitated patients presents significant ethical challenges.
• Existing methods like the Patient Preference Predictor (P3) use population data but may not fully respect individual autonomy.
• The proposed Personalized Patient Preference Predictor (P4) aims to enhance individualised predictions using personalized AI models.

Purpose of the Study:

• To comprehensively evaluate the philosophical, practical, and ethical criticisms of the Personalized Patient Preference Predictor (P4).
• To assess the feasibility and implications of using personalized large language models (LLMs) to create a 'digital psychological twin' for predicting patient preferences.
• To determine if identified concerns warrant halting P4 development or necessitate specific design and regulatory approaches.

Main Methods:

• Comprehensive review and evaluation of all published critiques of the P4 concept.
• Analysis of philosophical, practical, and ethical objections raised against P4.
• Argumentative synthesis to address criticisms and propose a path forward for P4 development.

Main Results:

• Significant philosophical, practical, and ethical concerns have been raised regarding the P4.
• The critiques highlight the need for careful consideration of individual autonomy and data privacy.
• Despite valid concerns, the potential benefits of P4 for patient-centered care warrant continued development.

Conclusions:

• The criticisms of P4, while substantial, do not necessitate abandoning the concept.
• Thoughtful design choices, robust regulation, and ongoing philosophical discourse are crucial for responsible P4 development.
• P4 development should proceed, guided by ethical considerations to ensure it aligns with patient values and respects autonomy.