Dental students welcome AI but remain wary of diagnosis, privacy and trust

Dental students surveyed about artificial intelligence generally expected the technology to advance dentistry and medicine, but only a small minority regarded an AI-generated diagnosis as as reliable as a dentist’s assessment. In the cross-sectional study, 73.1% of 327 participants said AI could produce significant advances in the fields of dentistry and medicine, while 13.1% considered AI diagnosis as reliable as diagnosis by a dentist. The results present a mixed picture: students appeared receptive to AI’s potential, yet their willingness to rely on it clinically remained limited, and their ethical concerns centered on privacy, confidentiality and the future of dentist-patient relationships.

The students completed an online questionnaire covering sociodemographic characteristics, knowledge of AI, patterns of use, clinical attitudes and ethical perspectives. The researchers analyzed categorical variables with Pearson’s chi-square test. When expected cell frequencies did not meet the test’s assumptions, they derived p values through Monte Carlo simulation and set statistical significance at p < 0.05. This was a survey of one group at a single point in time rather than a clinical trial, so the findings describe students’ reported knowledge, opinions and experiences without establishing how AI tools affect diagnosis, treatment quality or patient outcomes.

Students reported learning about AI primarily through social media and the internet, cited by 79.2% of respondents, while ChatGPT was the tool they used most frequently, named by 67.6%. Despite this high exposure to online AI resources, confidence in AI as a diagnostic authority was much lower. The contrast between broad expectations of technological progress and limited acceptance of machine-generated diagnoses suggests that familiarity with AI was not equivalent to clinical trust in it. The survey also found differences in the preferred source of authority when a dentist and an AI system disagreed, although that result was specific to comparisons by stage of education.

Ethical concerns were not evenly distributed among participants. Female students reported personal privacy and data-security concerns at higher rates than male students, with a p value of 0.004. They also more frequently reported concerns about patient confidentiality, for which the group difference had a p value of 0.013, and about AI’s potential negative effect on the dentist-patient relationship, for which the p value was 0.002. Opinions on the reliability of AI diagnosis also differed by gender, with p = 0.014. These statistical associations identify differences within the surveyed population; they do not explain the causes of those differences or establish how the same pattern might appear among practicing dentists and patients.

Educational stage was associated with several attitudes. Significant differences were found in students’ preferred source of trust when a dentist and AI conflicted, with a Monte Carlo p value of 0.002; in support for including AI courses in the dental curriculum, with p = 0.004; and in views on whether patients should be informed, with p = 0.001. Together, the findings show that dental students were generally positive toward AI while retaining reservations about trust, privacy, confidentiality and ethical responsibility. They also indicate that interest in formal AI education and patient disclosure did not remain uniform across preclinical and clinical stages. The authors concluded that structured teaching on AI technologies and their ethical and clinical limitations could be beneficial within dental education, while the survey’s cross-sectional design leaves the effect of such teaching untested.

Subject of Research: Dental students’ knowledge, attitudes and ethical concerns regarding artificial intelligence in dentistry

Article Title: Attitudes, perceptions, and ethical concerns of dental students toward artificial intelligence: a cross-sectional survey study

Article References: Gümüş Saka, C., Başakcı, S., Akman, H., & Surme, K. (2026). Attitudes, perceptions, and ethical concerns of dental students toward artificial intelligence: a cross-sectional survey study. BMC Medical Education. https://doi.org/10.1186/s12909-026-10369-6

Image Credits: AI Generated

DOI: 10.1186/s12909-026-10369-6

Keywords: dental education, artificial intelligence, dentistry, student survey, AI diagnosis, data privacy, patient confidentiality, clinical trust, medical ethics, ChatGPT, Attitudes, perceptions