Navigating the ethical landscape of artificial intelligence in dental education and practice: A Cross-sectional study.
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| Title: | Navigating the ethical landscape of artificial intelligence in dental education and practice: A Cross-sectional study. |
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| Authors: | Nasreen, A. Aysha (AUTHOR), Harishma, S (AUTHOR), Jayakumar, Srilekha (AUTHOR), Sanyal, Gopal Chandra (AUTHOR), Harshini, S (AUTHOR), Barkavi, Panchatcharam (AUTHOR) |
| Source: | Journal of Oral Research & Review. Jan-Jun2026, Vol. 18 Issue 1, p34-41. 8p. |
| Subjects: | Artificial intelligence, Dental education, Cross-sectional method, Algorithmic bias, Ethical problems, Attitude (Psychology), Data security |
| Abstract: | Introduction: Artificial intelligence (AI) is revolutionizing health care by supporting diagnosis, treatment planning, education, and patient engagement. Within dentistry, interest in AI applications has expanded, yet the ethical, educational, and practical challenges related to its use are not fully explored. Exploring the knowledge, attitudes, and perceptions of dental professionals and students is therefore essential to address these concerns effectively. Aim: This study evaluates the ethical challenges of integrating AI in dental practice and education through Knowledge, Attitude, and Practice (KAP) survey, aiming to identify key concerns and assess perceptions of AI's role in dentistry. Methodology: The study employed a cross-sectional survey of 180 dental practitioners and 180 dental students, using a 30-item self-developed questionnaire. Ethical approval and electronic consent were obtained before data collection through Google Forms. Statistical Analysis: Data were analyzed using IBM SPSS Statistics 20.0, employing descriptive statistics, Chi-square tests, correlation, and regression to evaluate trends, associations, and factors affecting willingness to share AI-related data. Results: Awareness of AI varied, with 21.9% of participants reporting high familiarity and 22.9% showing moderate knowledge. Concerns were most pronounced regarding data security (35.4% extremely concerned) and algorithmic bias (36.5%). A significant association (P = 0.0001) was noted between willingness to share data and trust in AI's confidentiality mechanisms. Conclusion: AI holds considerable promise in dentistry; however, addressing ethical concerns is crucial for its responsible implementation. Building AI literacy, reinforcing regulatory frameworks, and ensuring transparency are key to its ethical integration in dental education and clinical practice. [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Oral Research & Review is the property of Wolters Kluwer India Pvt Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Psychology and Behavioral Sciences Collection |
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