The Waste Land and the Question of Translation: The Poem's Journey Between Humans, Google, and Artificial Intelligence

This study presents a comparative analysis of three Arabic translations of selected passages from T. S. Eliot’s The Waste Land, evaluating human translation (Abdul Wahid Lu’lu’a), rule-based machine translation (Google Translate), and AI-generated translation (ChatGPT). Through four core criteria linguistic accuracy, poetic aesthetics, symbolic transfer, and cultural engagement the study reveals critical strengths and limitations in each modality. Findings show that Lu’lu’a’s human translation excels in conveying Eliot’s intertextual density and rhythmic nuance. ChatGPT performs moderately well, demonstrating stylistic fluency but lacking deeper interpretive insight. Google Translate underperforms across all axes due to literalism and syntactic instability. The study concludes that while AI tools offer potential for initial drafting, human translators remain indispensable for capturing the full poetic and cultural depth of modernist texts. This research contributes to current debates in literary translation and AI by highlighting the interpretive challenges neural models face in high-literary contexts. These findings may inform future design of AI translation systems for complex literary tasks.