Beyond the Algorithm: A Perspective on Tackling Bias and Cultural Sensitivity in AI-Guided Aesthetic Standards for Cosmetic Surgery in the Middle East and North Africa (MENA) Region.

Abstract

Artificial intelligence (AI) is increasingly reshaping cosmetic surgery by enhancing surgical planning, predicting outcomes, and enabling objective aesthetic assessment. Through narrative synthesis of existing literature and case studies, this perspective paper explores the issue of algorithmic bias in AI-powered aesthetic technologies and presents a framework for culturally sensitive application within cosmetic surgery practices in the Middle East and North Africa (MENA) region. Existing AI systems are predominantly trained on datasets that underrepresent MENA phenotypes, resulting in aesthetic recommendations that disproportionately reflect Western beauty ideals. The MENA region, however, encompasses a broad spectrum of beauty standards that merge traditional cultural aesthetics with modern global trends, posing unique challenges for AI integration. To ensure ethical and clinically relevant deployment, AI systems must undergo fundamental changes in algorithm design, including the incorporation of culturally diverse datasets with adequate MENA representation, implementation of cultural competency principles, and active collaboration with regional healthcare professionals. The framework outlines concrete criteria for evaluating cultural representativeness in AI training data and outcome assessments, supporting future empirical validation. Developing culturally aware AI tools is both a moral obligation and a clinical priority. This framework provides both a moral imperative and clinical pathway for ensuring AI serves to support, rather than homogenize, the region's diverse aesthetic traditions.