ANALYSING POSTMODERN IDENTITY AND ARTIFICIAL INTELLIGENCE: A COMPARATIVE STUDY OF ISHIGURO’S KLARA AND THE SUN AND MCEWAN’S MACHINES LIKE ME

Authors

  • Sana Tahir Senior Lecturer, Iqra University, Main Campus, Karachi, Sindh, Pakistan.
  • Hamna Amir PhD Scholar, Department of English, University of Education, Lahore, Punjab Pakistan.
  • Abdul Hanan M.Phil. Scholar, Department of English, University of Management and Technology Lahore, Punjab, Pakistan.

DOI:

https://doi.org/10.63878/cjssr.v3i1.913

Keywords:

Qualitative research, literature, novels, artificial intelligence and textual analysis.

Abstract

This study explores the intersection of postmodern identity and artificial intelligence in Kazuo Ishiguro’s Klara and the Sun and Ian McEwan’s Machines Like Me. The novels set against the backdrop of increasing technological advancements and their impact on human relationships, this research aims to examine how these novels represent the blurring of boundaries between human and artificial intelligence, and the implications for postmodern identity. Employing a comparative literary analysis within a post-humanist framework proposed by Hayles (1999) this study analyses the themes, motifs, and characterizations related to artificial intelligence and human-AI relationships in the two novels. The findings reveal that both novels challenge traditional notions of human identity and agency, highlighting the complexities and implications of human-AI relationships in the postmodern era. This research contributes to our understanding of the complex relationships between human identity, artificial intelligence, and postmodernism, offering insights into the possibilities and challenges of human-AI interactions in contemporary society.

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Published

2025-03-20

How to Cite

ANALYSING POSTMODERN IDENTITY AND ARTIFICIAL INTELLIGENCE: A COMPARATIVE STUDY OF ISHIGURO’S KLARA AND THE SUN AND MCEWAN’S MACHINES LIKE ME. (2025). Contemporary Journal of Social Science Review, 3(1), 2354-2362. https://doi.org/10.63878/cjssr.v3i1.913