Research is not static in nature it is a constantly evolving dynamic process. It is a multifaceted process. This process has seen many revolutions like from manual manuscript writing to digital revolution. Digital process has changed the way we write our manuscript nowadays. Again with the AI revolution in digital technology, it has transformed the research into more structured based and more technology based learning tool. No field is untouched by AI including medical science, dental science and our very own branch of Orthodontics. In this digital world we have intraoral scanner which provides digital models as well as quick after treatment results. We have digital X-rays and use Ceph Apps for digital tracings. We have digital dslr camera to record photographs digitally. Now a day’s we use Aps to maintain our records. We create and simulate diagnosis and treatment planning to get what is best for the patient. We have digital appliances. All this have to be documented and shared in research world.

When using AI for research in orthodontics,there are certain key ethical considerations which include:

patient data privacy,

data security,

informed consent,

algorithm transparency,

potential for bias in data analysis,

clinical validation of AI results,

and ensuring that AI does not replace the professional judgment of the orthodontist;

Data Privacy and Security:

We all should maintain a strict policy of Protecting the sensitive patient information like dental records, facial scans, and X-rays from unauthorized access or disclosure when using large datasets to train AI algorithms.

We should always Obtain informed consent from patients regarding how their data will be used in AI research.

Algorithm Transparency and Explainability:

There should be a thorough Understanding of how AI models reach their conclusions to ensure clinical decisions and whether they are based on reliable and interpretable data.

We should be always have Ability to explain the rationale behind AI-generated treatment plans to patients.

Bias in Data and Algorithms:

Ensuring that AI models are not biased on factors like ethnicity, gender, or socioeconomic status present in the training data.

Regularly monitoring and mitigating potential biases in AI algorithms.

Clinical Validation and Accuracy:

Thoroughly validating AI-generated treatment plans against established clinical standards and expert opinions before implementing in practice.

Ensuring that AI systems are accurate and reliable in real-world clinical scenarios.

Professional Responsibility and Patient Autonomy:

Not relying solely on AI recommendations without considering the individual patient’s needs and clinical context.

Maintaining the orthodontist’s primary responsibility to make informed treatment decisions based on their clinical expertise.

Access to AI Technology:

Considering potential disparities in access to AI-powered orthodontic care, ensuring equitable distribution of benefits.

Important considerations for research design:

Ethical review board approval:

All AI research in orthodontics should be reviewed and approved by an appropriate ethics committee.

Data anonymization:

When possible, anonymize patient data to protect privacy.

Clear communication with patients:

Inform patients about the potential benefits and risks of participating in AI research.

Continuous monitoring and improvement:

• Regularly evaluate AI models for accuracy and potential biases, making updates as necessary.