Volume 1, Issue 1 (January 2024)                   JCALS 2024, 1(1): 161-182 | Back to browse issues page

‎ 10.22034/jcals.1.1.161

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A Critical Analysis of Mirza Reza Kermani's Interrogation Through Grice's Conversational Maxims with the Assistance of Artificial Intelligence (AI)
Ali Beikian
Ali Beikian (Corresponding Author), Assistant Professor of Translation Studies, Faculty Member of the English Language Department, Chabahar Maritime University, Chabahar, Iran. Email: a_beikian@yahoo.co.uk
Abstract:   (1980 Views)
This study applies Grice's cooperative principle and its conversational maxims to analyze the interrogation transcript of Mirza Reza Kermani, a significant historical document. Leveraging Claude.ai., as an artificial intelligence assistant for a rigorous quantitative and qualitative assessment, the research examines 52 question-and-response pairs to evaluate the adherence to Grice's maxims: quality, quantity, relevance, and manner. The findings show high compliance with the maxims of quality (86.54%) and relevance (82.69%), but lower adherence to the maxims of quantity (73.07%) and manner (28.86%). The study provides a detailed categorization of instances of both adherence and violation, revealing strategic communication tactics by the suspect, including evasion and ambiguity, which often necessitated adaptive interrogation techniques. These insights emphasize the importance of tailored questioning strategies to address such evasive behaviors and highlight the need for a nuanced, analytical approach to interpreting responses. The integration of AI in this analysis enhances the objectivity and systematization of examining the complex dynamics in historical interrogation records, offering valuable implications for law enforcement and legal professionals.
Article number: 10
Keywords: Conversational Maxims, Grice’s Cooperative Principle, Interrogation Transcript, Mirza Reza Kermani, Claude.AI, Quantitative and Qualitative Assessment
Full-Text [PDF 379 kb]   (889 Downloads)    
Type of Study: Research | Subject: Special
Received: 2023/08/12 | Accepted: 2023/11/25 | Published: 2024/01/1
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