Algor‐Ethics in Diabetes Care: Mapping the Route

Diabetes mellitus represents a multifaceted global health challenge, frequently coexisting with obesity, cardiovascular complications, and metabolic disorders. Effective management requires individualised, evidence-based decisions informed by an array of clinical, genetic, and lifestyle data. With the rapid growth of digital health technologies, artificial intelligence (AI) and algorithmic systems have emerged as powerful tools to support clinicians in diagnosis, treatment planning, and risk stratification. While AI shows promise in improving diabetes outcomes and health system efficiency, its integration into patient care is not without ethical and epistemic challenges. Algorithmic decision-making can influence therapeutic strategies, sometimes without full transparency or adequate oversight, potentially compromising human values such as autonomy, justice, and trust. In this context, the discipline of 'Algor-ethics', a term coined to describe the intersection of algorithmic systems and ethical principles, becomes critical. This article explores the foundational concepts of Algor-ethics applied to diabetes care, analyzes the current state of AI integration, and highlights the epistemic and ethical implications of algorithmic decision-making. Emphasis is placed on developing a framework that ensures AI is implemented safely, equitably, and responsibly, particularly for complex patients with diabetes.