التحديات اللغوية للذكاء الاصطناعي وآفاق تطويره

Linguistic Challenges in Artificial Intelligence: Prospects and Future Directions

Abstract

In the modern era, the rapid development of Artificial Intelligence (AI) has had a significant impact on various fields, particularly language studies and Natural Language Processing (NLP). Arabic, as one of the world’s major languages, presents unique challenges for AI-based language technologies due to its rich morphological and syntactic structures, linguistic diversity, contextual ambiguity, and the frequent absence of diacritical marks in written texts. These characteristics make accurate Arabic language processing, understanding, translation, and generation particularly complex. This study examines the relationship between the Arabic language and Artificial Intelligence, focusing on the major linguistic challenges encountered in the development of AI technologies for Arabic. It explores the ability of contemporary language models to understand, analyze, and generate Arabic texts accurately and appropriately. The study also highlights the applications of AI in Arabic language teaching, machine translation, grammatical and spelling correction, text analysis, speech recognition, and Arabic content generation. Furthermore, the study discusses prospects for improving AI technologies for Arabic through the development of high-quality Arabic linguistic corpora, specialized language models, and advanced morphological, syntactic, and semantic analysis tools. It emphasizes the importance of collaboration between linguists, computational linguists, and AI specialists. The study concludes that AI offers significant opportunities for advancing Arabic language education, processing, and dissemination, provided that the linguistic and cultural characteristics of Arabic are carefully considered. Integrating linguistic expertise with modern AI technologies can contribute substantially to developing more accurate, effective, and culturally appropriate Arabic language applications.