Semitic Linguistics in the Age of Artificial Intelligence and the Transformation from Algorithm to Dialect

Abstract

Artificial Intelligence (AI) technology has been transforming information services and NLP as a whole by making linguistic data easily accessible, processible and interpretable. AI tools will be vital in Arabic processing, given the need to make resources accessible to Arabic speakers and to address the majority of its challenges. To process Arabic, AI tools will be crucial for addressing its complexity and variation, and for leveraging the availability of digital media to process Arabic language resources. In this research, the aim is to assess the efficiency of using Arabic language processing and digital information services, based on a qualitative document study approach using an AI tool. The research assessed different AI tools (CAMeL Tools, ChatGPT, Google Translate, Duolingo, and Busuu) in terms of their processing of Arabic data, translation, communication, and educational functions. Assessment criteria are accuracy, fluency and efficiency and cultural sensitivity. The results showed that the performance of the Arabic language processing is improved significantly using AI systems. It enables the translation and rendering of text, provides flexible learning environment, and aids in the understanding and interaction with Arabic text. Published benchmarks demonstrate that CAMeL Tools is very good at morphological analysis in Arabic, and large language models like ChatGPT are performing competitively in contextual tasks, albeit with some limitations in Arabic dialects. There are still some issues about the sentence level limitation, dialect limitation, cultural adaptation, and accuracy of the contexts in the machine translation system like Google Translate. However, websites such as Duolingo and Busuu offer a benefit in terms of engagement for the learner, but are lacking in depth of grammatical analysis and cultural context. The findings of the study indicate that artificial intelligence has great potential in the development of digital linguistic information services, as it helps to make them accessible and effective for learning and communication. However, there are some problems that still render the language processing in Arabic inefficient. Such problems include the need to improve the dialectal data sets as well as the need for culture-sensitive models and systems integration. The need for future years is AI systems that will consider the complexity of Arabic.