Abstract

This examination aims to assess the reliability of Artificial Intelligence (AI), specifically ChatGPT, in generating academic content across the disciplines of literature and linguistics. The study utilizes Natural Language Processing (NLP) theory, originally conceptualized by Alan Turing in (1969), as a framework for understanding AI's linguistic capabilities. The research conducts a comparative analysis of AI-generated responses regarding the character of Molvi Jalal from Nafisa Rizvi's novel The Blue Room and the Linguistic Relativity theory proposed by Sapir and Whorf. The primary objectives were to evaluate the accuracy, relevance, and credibility of AI's responses in both fields. Data were collected through targeted prompts, and the AI’s output was critically analyzed against established literary critiques and linguistic theories. The findings revealed that while AI demonstrated higher accuracy in linguistics, particularly with well-defined theories, it performed poorly in literature, misinterpreting key character attributes and plot details. The study concludes that AI is more reliable in structured academic fields like linguistics but falls short in disciplines requiring nuanced interpretation, such as literature. The key limitations include AI's reliance on available data, lack of emotional understanding, and challenges in dealing with less-critically evaluated texts. The research recommends a cautious approach to using AI in interpretive fields and emphasizes the need for future studies to address AI's limitations in handling context-dependent academic content. The implications suggest improvements in AI models for better performance in humanities-based disciplines.