Bioethics Crafted by Artificial Intelligence: Review of Organ Transplantation Decision-Making Using AI

Abstract

Artificial intelligence is increasingly used in healthcare to improve efficiency, consistency, and predictive accuracy. This paper critically examines the ethical and social implications of bias in artificial intelligence systems, particularly in the context of liver transplantation and medical imaging. While artificial intelligence is often promoted as a neutral and objective tool, its outputs are shaped by the data and design choices that inform its development. The paper analyzes how algorithmic bias can emerge from nonrepresentative datasets and design decisions, leading to unequal outcomes for marginalized populations. In liver allocation, artificial intelligence models may reinforce existing disparities by deprioritizing patients based on behavioral or cultural factors. In medical imaging, underdiagnosis and false positives disproportionately affect underserved communities due to limited representation in training data. These findings highlight the need for ethical oversight, inclusive data practices, and interdisciplinary collaboration to ensure that artificial intelligence supports equitable healthcare outcomes. The paper argues that artificial intelligence must be developed and deployed with a solid foundation in bioethical principles such as autonomy, beneficence, nonmaleficence, and justice.