Correspondence Address:
S M Balaji
Executive Editor, Indian Journal of Dental Research, Director and Consultant Oral and Maxillofacial Surgeon, Balaji Dental and Craniofacial Hospital, 30, KB Dasan Road, Teynampet, Chennai, Tamil Nadu
India

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Artificial intelligence (AI) and natural language processing (NLP) technologies have revolutionized all fields of research including dentistry. These technologies have enabled researchers to analyze and interpret large amounts of data more efficiently, accurately, and comprehensively than ever before. In particular, the development of chatbots such as ChatGPT has opened up new opportunities for scientific publications and dental education.[1],[2],[3],[4] In the past, research publications were typically limited to academic journals that were only accessible to a small subset of professionals. However, the development of chatbots-like ChatGPT has enabled researchers to communicate their findings to a wider audience. Chatbots can translate complex scientific findings into accessible language, making them more easily understood by non-experts. This enables researchers to share their findings with a broader audience, including patients, policymakers, and the general public.[2] Moreover, chatbots-like ChatGPT can provide instant feedback to readers, offering additional resources, or clarifying any doubts that may arise. Chatbots can also be programmed to keep readers up-to-date with the latest research in a given field, providing notifications and alerts when new publications are released. The immediate role of AI and NLP technologies such as ChatGPT in the publication process is undeniable. They have enabled researchers to communicate their findings more efficiently, accurately, and comprehensively than ever before. By providing accessible language, instant feedback, and updated information, chatbots-like ChatGPT are poised to revolutionize the way that scientific research is shared and disseminated.[1],[2],[3],[4]

One negative aspect of artificial intelligence and NLP such as ChatGPT on research publications is the potential for biased or inaccurate conclusions. AI and NLP algorithms are only as good as the data they are trained on, and if that data is biased or incomplete, the resulting analysis may be flawed. This can have a significant impact on the quality of research and the validity of its findings. Another negative impact is the potential for AI and NLP to replace human researchers. While these technologies can certainly speed up the research process and help identify patterns and trends that might not otherwise be visible, they cannot replace the nuanced insights and critical thinking skills of human researchers. If researchers come to rely too heavily on AI and NLP, they may overlook important details or fail to consider alternative explanations for their findings. Finally, there is the concern that AI and NLP may exacerbate existing inequalities in research. For example, if the algorithms used to analyze research data are biased toward certain types of research or certain groups of people, then the resulting findings may not accurately reflect the experiences or perspectives of other groups. This can lead to a lack of diversity and inclusivity in research, which can have serious consequences for public policy and decision-making.[4]

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