The Algorithmic Turn: A Comparative Analysis of AI Integration in Literary and Linguistic Research

Abstract

The integration of Artificial Intelligence (AI) has revolutionized literary and linguistic research, shifting methodologies from manual, labour-intensive techniques to data-driven, computational frameworks. This paper examines the transition from traditional "close reading" and manual corpus analysis to AI-powered "distant reading" and Natural Language Processing (NLP). By comparing methodologies before and after the advent of AI, this study highlights advancements in authorship attribution, machine translation, and discourse analysis. While AI enhances efficiency and accessibility, it introduces critical challenges regarding algorithmic bias, the erosion of human interpretative depth, and the redefinition of creative authorship.