نوع مقاله : مقاله پژوهشی
نویسندگان
1 دکتری، گروه تاریخ تشیع، دانشگاه ادیان و مذاهب، قم، ایران
2 استادیار، گروه تاریخ تشیع، دانشگاه ادیان و مذاهب، قم، ایران
3 دانشیار، گروه هوش مصنوعی، واحد کاشان، دانشگاه آزاد اسلامی، کاشان، ایران
4 استادیار، گروه شیعهشناسی، دانشگاه باقرالعلوم(ع)، قم، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Abstract
The history of Shia Islam, as one of the richest and most complex fields of historical studies, possesses unique characteristics that necessitate a multidisciplinary and specialized approach to its analysis. These characteristics encompass theological, cultural, political, and social dimensions, which have evolved over centuries and are reflected in Shia texts, narratives, and traditions. As an independent subject within religious and cultural studies, distinct from just a branch of Islamic history, the history of Shia Islam requires a profound and specific understanding of cultural and social contexts and developments.
In recent years, Artificial Intelligence (AI) has emerged as a novel tool for analyzing historical data, offering the ability to process vast amounts of information and identify hidden patterns. This technology allows researchers to analyze data with greater speed and accuracy, facilitating the discovery of historical trends and connections. However, the application of AI in the field of Shia history comes with several challenges that must be carefully examined.
One of the most significant challenges is algorithmic bias, which can lead to inaccurate and skewed interpretations of historical events and figures. Algorithmic bias occurs when algorithms, due to the use of incomplete, unreliable, or biased data, produce results that do not align with historical reality. This issue is particularly critical in the context of Shia history, as the data and texts in this field have unique characteristics that require deep and specialized understanding.
This research aims to identify algorithmic biases in the analysis of historical data related to Shia Islam and to provide practical solutions for mitigating these biases. The main objective is to present a model for historical analyses of Shia Islam produced by AI, in which biases are identified and reduced. To this end, the research examines various AI models and their impact on historical analyses, identifying the specific challenges that exist in this area.
The findings of the research indicate that designing an interdisciplinary framework—including the use of reliable Shia data, localization of algorithms, and active participation of history experts—can help reduce biases and increase the accuracy of analyses. This framework may include training researchers on cognitive biases, forming multidisciplinary research teams, and using more advanced machine learning techniques.
In this regard, researchers seek a deeper understanding of the historical and cultural infrastructures of Shia history to achieve more accurate analyses using AI. In particular, this research emphasizes that maintaining and emphasizing the importance of human interpretation in historical analyses is essential, as human interpretation can aid in a deeper understanding of historical complexities and prevent the semantic distortion of data.
Furthermore, the results of this research can contribute to enhancing the quality of historical research and preventing the semantic distortion of data. Researchers can achieve more accurate historical analyses by following the frameworks presented in this research, resulting in a better understanding of the history of Shia Islam and its developments.
Overall, this research can serve as a useful guide for researchers and scholars of Shia history, helping them to achieve deeper and more accurate analyses by utilizing AI and novel techniques. This not only enriches the historical and cultural narrative of Shia history and aids in a better and deeper understanding of this history but can also serve as a model for other historical fields.
کلیدواژهها [English]
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