نوع مقاله : مقاله پژوهشی
نویسندگان
1 استاد مهندسی فناوری اطلاعات، دانشگاه تربیت مدرس، تهران، ایـران
2 دانشجوی کارشناسی ارشد مهندسی فناوری اطلاعات، دانشگاه تربیت مدرّس، تهران، ایران.
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Given the increasing growth of artificial intelligence, especially chatbots, in the process of producing scientific content, numerous opportunities and challenges have emerged in this field. This study comprehensively examines the applications, opportunities, and challenges of artificial intelligence tools in writing and reviewing articles. Findings from a review and analysis of the policies of major global publishers such as Science, Elsevier, Springer Nature, IEEE, and Emerald show that the use of artificial intelligence as an author in scientific articles is prohibited and transparency and disclosure of the use of these technological tools is mandatory; however, their application is very effective in improving the quality of literary writing, accelerating the process of searching and reviewing sources, and facilitating interdisciplinary collaborations. On the other hand, risks such as plagiarism, producing false content (delusion), bias, reducing critical thinking, and violating data confidentiality can undermine trust in the scientific publishing system. In scientific peer review, these tools can also be useful by reducing the workload of reviewers and accelerating the implementation processes, but limitations such as low accuracy in interdisciplinary areas and ethical issues (such as confidentiality violations) reduce their effectiveness. Accordingly, at the end of the article, policy recommendations are proposed for Iranian publications, in which transparent policies tailored to local needs should be developed to define how these tools should be used in creating content and reviewing scientific texts. It is also necessary for national institutions (such as the National Scientific Publications Commission) to create effective mechanisms to monitor biases and ensure the confidentiality of scientific publication data, and to reduce dependence on foreign systems by developing local models.
کلیدواژهها [English]
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