Page 38 - Shaping ethics, regulation and standardization in AI for health

Shaping ethics, regulation and standardization in AI for health

assigned to a level. Items were systematized into domains and a curricular structure defined.
The resulting curriculum was consented using an online Delphi process.

Results: Four domains of learning outcomes emerged, with most outcomes being on the
"knowledge" level: (1) Basic definitions and terms, the reasoning behind AI and the principle
of machine learning, the idea of training, validating and testing models, the definition of
reference tests, the contrast between dynamic and static AI, and the problem of AI being a
black box and requiring explainability should be known. (2) Use cases, the required types of AI
to address them, and the typical setup of AI software for dental purposes should be taught. (3)
Evaluation metrics, their interpretation, the relevant impact of AI on patient or societal health
outcomes and associated examples should be considered. (4) Issues around generalizability and
representativeness, explainability, autonomy and accountability and the need for governance
should be highlighted.

Both educators and learners should consider this core curriculum during planning, conducting
and evaluating oral and dental AI education. A core curriculum on oral and dental AI may help
to increase oral and dental healthcare providers' literacy around AI, allowing them to critically
appraise AI applications and to use them consciously and on an informed basis.

A�4�20 TG-Dental Output 3: Ethical considerations on artificial intelligence in
dentistry: A framework and checklist

Summary: This document from the International Telecommunication Union (ITU) outlines a
framework and checklist for the ethical considerations of Artificial Intelligence (AI) in dentistry.
Recognizing AI's potential to improve diagnostics and patient care, the authors emphasize the
crucial need to address associated ethical challenges. Through a consensus-based process
involving experts and stakeholders, they identified and defined eleven core principles (such
as transparency, equity, privacy, and accountability) that should guide the development,
implementation, and use of AI tools in dental practice to ensure responsible and beneficial
integration

Objective: Artificial Intelligence (AI) refers to the ability of machines to perform cognitive and
intellectual human tasks. In dentistry, AI offers the potential to enhance diagnostic accuracy,
improve patient outcomes and streamline workflows. The present study provides a framework
and a checklist to evaluate AI applications in dentistry from this perspective.

Methods: Lending from existing guidance documents, an initial draft of the checklist and an
explanatory paper were derived and discussed among the groups members.
Results: The checklist was consented to in an anonymous voting process by 29 group members.
Overall, 11 principles were identified (diversity, transparency, wellness, privacy protection,
solidarity, equity, prudence, law and governance, sustainable development, accountability,
and responsibility, respect of autonomy, decision-making).

Conclusions: Providers, patients, researchers, industry, and other stakeholders should consider
these principles when developing, implementing, or receiving AI applications in dentistry.

Clinical Significance: While AI has become increasingly commonplace in dentistry, there are
ethical concerns around its usage, and users (providers, patients, and other stakeholders), as
well as the industry should consider these when developing, implementing, or receiving AI
applications based on comprehensive framework to address the associated ethical challenges.

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