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Digital Dickens: AI and The Future of Classic Literature Interpretation

Dildora GaniyevaFergana State University,Department of English Philology,Fergana,UzbekistanNavruza AliyevaFergana State University,Department of English Philology,Fergana,UzbekistanShakhloza KarimovaFergana State University,Department of English Philology,Fergana,UzbekistanDilorom IsmoilovaFergana State University,Department of English Philology,Fergana,UzbekistanIslom JurayevFergana State University,Department of English Philology,Fergana,Uzbekistan
2024en
ABI

Abstract

AI now has unparalleled capabilities for textual analysis, which means that a new world of interpretation can open up to scholars and readers who may wish to dig into some of the subtle intricate stories or themes hidden in Dickens's novels. Through NLP and machine learning algorithms - whether regression or deep neural networks-the algorithmic engine can detect the patterns, themes at play as well as warm-cold context readers might miss. This paper focuses on the use of AI tools to mine sentiments and themes from Dickens novels as well character tfidf relationship maps. The methods outlined here offer a fresh interpretation of one of England's best known raconteurs, and how she used different storytelling techniques. Thus, the AI-powered platforms have led literary analysis to be comprehensible and open for an unprecedented number of people. This paper examines the relationship between accessibility and academic labour; as well what ease of accessibility means for literary scholarship. For instance, when AI is part of the learning experience in class room it could allow individual students to get out of their seat and participate with what they are studying instead which would reduce understanding or results that one can hope for from Dickens work as well other classic literary works. It also addresses potential problems and ethical concerns with using AI for literary studies. We then elaborate on the concern for depersonalization, constraining universal interpretation maintenance that is an effective mechanism to integrate human-in-the-loop experiences while alluding some automation-only attitudes weakening such integration in differentigorously privacy-aware contexts where both HLT and AI organization accountability interests apply as transparency counsel. This paper argues for a judicious hybrid middle position that adds the best of AI to traditional hermeneutical practice, with creativity and intuition still forming an essential part of human understanding.

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