Responsible artificial intelligence for addressing equity in oral healthcare

• Published in: Frontiers in oral health Vol. 5; p. 1408867
• Main Authors: Khoury, Zaid H, Ferguson, Alexys, Price, Jeffery B, Sultan, Ahmed S, Wang, Rong
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 18-07-2024
• Subjects: artificial intelligence; bias; equity; explainable models; interpretable models; Oral Health; responsible models; explainable models; responsible models; bias; oral healthcare; interpretable models; equity; artificial intelligence
• ISSN: 2673-4842; 2673-4842
• DOI: 10.3389/froh.2024.1408867

Oral diseases pose a significant burden on global healthcare. While many oral conditions are preventable and manageable through regular dental office visits, a substantial portion of the population faces obstacles in accessing essential and affordable quality oral healthcare. In this mini review, we describe the issue of inequity and bias in oral healthcare and discuss various strategies to address these challenges, with an emphasis on the application of artificial intelligence (AI). Recent advances in AI technologies have led to significant performance improvements in oral healthcare. AI also holds tremendous potential for advancing equity in oral healthcare, yet its application must be approached with caution to prevent the exacerbation of inequities. The "black box" approaches of some advanced AI models raise uncertainty about their operations and decision-making processes. To this end, we discuss the use of interpretable and explainable AI techniques in enhancing transparency and trustworthiness. Those techniques, aimed at augmenting rather than replacing oral health practitioners' judgment and skills, have the potential to achieve personalized dental and oral care that is unbiased, equitable, and transparent. Overall, achieving equity in oral healthcare through the responsible use of AI requires collective efforts from all stakeholders involved in the design, implementation, regulation, and utilization of AI systems. We use the United States as an example due to its uniquely diverse population, making it an excellent model for our discussion. However, the general and responsible AI strategies suggested in this article can be applied to address equity in oral healthcare on a global level.