Responsible integration of artificial intelligence in clinical care: An American Association of Orthodontists position paper.

Authors

Heather Stone Hopkins, Jonas Bianchi, Lucia Cevidanes, Anthony Puntillo, Mario Tai, Ryan Goy, Frank Hemm, Zelko Relic, Lisa Alvetro, Mindi Brothers, Trista Felty, Jae Hyun Park

Published in

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics. Volume 170. Issue 3. Pages 299-321.e4.

Abstract

This paper, which is adapted for publication and differs slightly from the original version distributed to American Association of Orthodontists (AAO) members in January 2026, is authored by the AAO Task Force on Artificial Intelligence in Orthodontics, and provides professional guidance for the responsible development, implementation, and oversight of artificial intelligence (AI) technologies in orthodontic clinical care. Although not regulatory, it establishes a framework to support ethical adoption, patient safety, and professional accountability in the integration of AI systems. The objectives of this paper are to preserve professional authority, promote transparency in AI development, protect patient safety, and establish a principles-based framework. These objectives will be guided through the following 6 core principles: (1) AI governance and the human-in-command, (2) regulatory alignment and risk-based oversight, (3) trustworthiness and transparency across the lifecycle, (4) patient autonomy, (5) education and clinical AI competency, and (6) operational integration and data privacy. The seamless integration of AI into orthodontic and dental care positions the orthodontist not only as the final decision-maker in the use of AI for patient care but also as the responsible party. Through transparency and a clear understanding of the underlying algorithms and learning models, orthodontists can deliver enhanced care that thoughtfully integrates technological innovation with traditional biomechanical principles without compromising patient safety, quality of care, or autonomy.

PMID:
42716645
Bibliographic data and abstract were imported from PubMed on 10 Sep 2026.

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