Artificial Intelligence and Literary Creativity: Examining New Frontiers in English Literature
With the advent of artificial intelligence (AI), a lot of spheres in life and work have been introduced to a new stage, and English literature cannot be an exception here. It proposes an investigatory research paper that tries to unmask the intersections between AI technologies and literary creativity, delving into how, in fact, such digital novelties are turning the scenery of English literature upside down. This paper will, at first, make an attempt to give some sort of comprehensive overview of the current state of AI technologies. Among the AI tools and algorithms, it is the special attention of somehow making their applications within the realm of literary creation, analysis, and interpretation. The core of these studies plunges into the details of what AI has to do with generating literary content, be it through algorithms writing poems, short stories, and even novels in the style of famous authors or totally from scratch. This study expands the scope of consideration to the collaborative processes between human authors and AI, focusing on synergetic potential for creative exploration and emergence of hybrid authorial identities. In addition, implications of the use of AI in literary analysis were described due to the fact that it is being applied to reveal new critical insights into classic texts using machine-learning models, predicting the future direction of literature, and even critiquing—again using a similar style generator—works of literature with a degree of insight thought previously exclusive to human scholars. Another important focus area will be the pedagogical implications for integrating AI into English literature education.
Authors
- M. H. Hamza (ORCID: https://orcid.org/0000-0001-6823-1946)
Institutions
- University of Ha'il (SA)
Publication Details
- Published
- 2024-11-23
- DOI
- https://doi.org/10.1109/icicat62666.2024.10923368
- Citations
- 5
- Primary Topic
- Computational and Text Analysis Methods
- Type
- article
- Field-Weighted Citation Impact
- 9.47