Artificial Intelligence in Healthcare: Ethical Considerations

Abstract: This dissertation chapter provides a comprehensive ethical analysis of artificial intelligence applications in healthcare settings. It examines issues of algorithmic bias, patient autonomy, data privacy, and the changing physician-patient relationship in the age of AI-assisted medicine.

1. Introduction

The integration of artificial intelligence into healthcare represents one of the most significant technological transformations in modern medicine. While AI promises improved diagnostic accuracy, personalized treatment plans, and enhanced operational efficiency, it also raises profound ethical questions that challenge traditional medical ethics frameworks.

2. Algorithmic Bias and Health Equity

One of the most pressing ethical concerns in healthcare AI is the potential for algorithmic bias to perpetuate or exacerbate existing health disparities. Recent studies have demonstrated that AI diagnostic tools trained primarily on data from specific demographic groups may perform poorly when applied to underrepresented populations. For instance, Obermeyer et al. (2019) found that a widely used healthcare algorithm exhibited significant racial bias...

3. Patient Autonomy and Informed Consent

The principle of patient autonomy, fundamental to medical ethics, faces new challenges in the context of AI-assisted healthcare. The "black box" nature of many machine learning algorithms raises questions about meaningful informed consent. Can patients truly consent to treatments recommended by systems whose decision-making processes are opaque even to their developers?...