THE ALGORITHMIC READER: UNCOVERING AI’S CONTEXTUAL BLIND SPOTS IN POETRY INTERPRETATION - Desthia Amalia, SS, M. Sas (THE USE OF MODERN DIGITAL TECHNOLOGIES IN LINGUISTICS AND FOREIGN LANGUAGE TEACHING. INTERNATIONAL SCIENTIFIC AND PRACTICAL CONFERENCE, 2026)
The integration of AI in literature classrooms creates a new pedagogical challenge. While AI is efficient, it often lacks the human sensibility required for poetry analysis. This study explores the contextual blindness of Large Language Models (LLMs) such as ChatGPT when interpreting modern poems. Using a qualitative case study, undergraduate students at Universitas Gunadarma examined AI outputs using the TPCASTT framework. The results show a clear gap between machine logic and human interpretation. AI excels at literal paraphrasing but fails to detect irony, complex shifts, and emotional ambiguity. Furthermore, the machine often reduces deep themes to moralistic clichés. This paper argues that AI should be treated as an imperfect tool rather than a perfect source of truth. By critiquing AI errors, students can actively cultivate higher-order critical thinking skills. This approach ensures that literary interpretation remains a deeply human act.