Tecnología sesgada: una mirada crítica a la ia en el sistema sanitario

Abstract

The integration of artificial intelligence (AI) into medicine represents a profound transformation in how diseases are diagnosed, treated, and monitored, with the potential to optimize healthcare through greater precision, speed, and personalization. However, this innovation also highlights deep social and economic inequalities that limit access, especially in rural or low-income communities. Despite its many benefits—such as improved diagnostic imaging, automation of clinical processes, and personalized treatments powered by advanced algorithms—significant barriers remain. These include the lack of infrastructure, insufficient digital training among healthcare professionals, high implementation costs, and inherent biases in training data used to build AI systems. Such conditions disproportionately affect vulnerable populations, widening the gap between those who can benefit from these technologies and those who are excluded from their advantages. Moreover, public perception of AI in medicine remains ambivalent: while some view it as a powerful ally, others are skeptical of replacing human clinical judgment with automation. On the other hand, the synergy between AI and telemedicine creates new opportunities to expand access and reduce costs—provided that implementation is carried out ethically and equitably. This study reveals the urgent need for a critical and inclusive approach that ensures universal access to technological advances in healthcare, with equity and sustainability as foundational principles of digital development.