Dave and Patel (2023) point out that AI tools like ChatGPT often generate information without reliable or verifiable sources, creating challenges for proper referencing and academic integrity. Because these systems draw from a huge amount of online data, they may produce inaccurate or defective citations, as the authors found when ChatGPT provided outdated or invalid references. This raises concerns about unintentional plagiarism and misinformation in academic writing. To address this, educators and researchers should verify all AI-generated content, use credible databases for citations, and teach students critical evaluation skills to ensure accuracy and ethical use of AI in scholarly work.

The authors caution that AI tools like ChatGPT make it easier for students to complete assignments without genuine understanding, especially in open-book or online exams. To address this, educators should redesign assessments to emphasize critical thinking, problem-solving, and clinical reasoning, as these are skills that AI cannot replicate. For example, analyzing patient cases or interpreting radiographs encourages original thought and applied knowledge. If students rely too heavily on AI, they may lose essential abilities like research, synthesis, and independent judgment. Therefore, integrating AI responsibly while reinforcing ethical use and reflective learning is key to maintaining academic integrity in healthcare education.

Dave and Patel (2023) acknowledge that while AI tools like ChatGPT can efficiently generate clear, factual text, their writing often lacks creativity, nuance, and emotional depth. This limitation becomes significant in healthcare education, where reflective and critical thinking are essential for clinical reasoning and empathy. Overreliance on AI-generated content may lead students to engage less deeply with material, weakening their ability to analyze, question, and synthesize ideas. Additionally, the absence of human tone or storytelling can make complex medical concepts less engaging or relatable, reducing motivation and long-term retention. Therefore, AI should complement—not replace—human creativity in learning.

AI could significantly reshape how scientific research is published and shared. AI tools can enhance efficiency by automating tasks such as plagiarism detection, reviewer matching, and data validation. These systems can also improve the accuracy and clarity of manuscripts by identifying errors or inconsistencies before publication. Beyond editing, AI can support reproducibility and transparency, helping ensure that published findings are trustworthy. Overall, the authors emphasize that, when used responsibly, AI can improve both the speed and quality of scientific communication in academic publishing.

Advances in artificial intelligence are beginning to transform the way scientific articles are published. AI can help streamline the peer-review process by automatically checking for plagiarism, detecting data errors, and suggesting qualified reviewers. These tools can also enhance the quality and consistency of reviews by identifying operational weaknesses and supporting data reproducibility. Additionally, AI presents opportunities for innovative publication formats, including automatically generated summaries and visual content. Overall, the authors suggest that AI has great potential to make academic publishing more efficient, transparent, and reliable.

Ethical issues in using AI for exams include bias in algorithms, privacy concerns, and the risk of reducing human involvement in evaluation. If the data used to train AI are biased, some students may be graded unfairly, and weak data protection could expose personal information. Experts recommend that schools weigh AI’s benefits against these risks and create clear rules to keep assessments fair. Universities should also teach students about responsible AI use and honesty in academics to ensure technology supports fairness and trust in medical education.

AI in dental education increasingly uses adaptive quizzes and serious games to enhance engagement and long-term retention. These tools apply machine learning to tailor question difficulty, provide instant feedback, and simulate clinical decision-making in a safe environment. Studies show that game-based and AI-assisted learning improves students’ diagnostic accuracy and motivation compared to traditional formats. Reviews further suggest that gamified, retrieval-based learning supports better knowledge retention when paired with timely feedback. Overall, AI-driven quizzes and educational games make dental education more interactive and personalized, strengthening learning outcomes.