AIHealthcare Analytics

Overview

Research on human perception of AI-generated orthodontic facial images examines the degree to which patients, clinicians, and laypersons can distinguish AI-generated post-treatment images from authentic photographs, and the factors associated with misclassification.

Core Findings

AI-generated post-treatment orthodontic images were frequently misclassified as real by study participants. Beyond misclassification rates, AI-generated images were consistently perceived as more attractive than actual post-treatment photographs — a finding with significant implications for patient expectations and informed consent in orthodontic treatment planning.

Demographic and Behavioral Factors

The study identifies demographic and behavioral factors as associated with differential rates of misclassification, though the specific variables modulating trust and perception vary across subgroups. Understanding these factors is described as critical for designing targeted digital literacy interventions and responsible AI governance policies in dental and orthodontic contexts.

Policy and Ethical Implications

As generative AI tools for image creation become more accessible, the risk of patients forming unrealistic treatment expectations based on AI-generated imagery increases. The authors call for responsible AI policies that address the use of synthetic facial images in clinical communication, and for digital literacy education that enables patients to critically evaluate AI-generated content. This concern extends beyond orthodontics to any clinical specialty using AI-generated imagery in patient communication.