The Impact of Artificial Intelligence on Literary Criticism: Exploring Potentials and Limitations

The Impact of Artificial Intelligence on Literary Criticism: Exploring Potentials and Limitations

Authors

  • Muhammad Husein Hasan Muhammad Omdurman Islamic University

DOI:

https://doi.org/10.58223/dzilmajaz.v3i1.378

Keywords:

AI, Literary Criticism, Text Analysis, Arabic Literature, Natural Language Processing, Potentials and Limitations

Abstract

This research aims to explore the impact of artificial intelligence (AI) on literary criticism, focusing on the potentials it offers and the challenges it faces in this field. With the advancement of AI technologies, it has become possible to analyze literary texts in innovative ways, opening unprecedented horizons for understanding literature. However, there is a need to evaluate how these technologies interact with traditional critical approaches and whether they can enrich or constrain literary criticism. The study adopts a descriptive-analytical methodology, utilizing AI tools such as sentiment analysis, linguistic and literary pattern recognition, and natural language processing (NLP) to analyze a selected corpus of Arabic literary texts (poetry, novels, and prose). The results of AI-driven analysis are then compared with traditional critical readings of the same texts to assess the accuracy and effectiveness of AI. The findings reveal that AI holds significant potential in analyzing large volumes of text quickly and accurately, as well as identifying recurring literary patterns that may be difficult for humans to detect. However, the technology faces notable challenges, such as its limited ability to comprehend complex cultural and historical contexts, and its lack of the creative and interpretive depth characteristic of human criticism. The research concludes that AI can serve as a supportive tool for literary critics but cannot replace human creativity in criticism. It recommends developing AI tools that account for the cultural and linguistic specificities of Arabic literature and encouraging critics to integrate technology with traditional methods to enhance the critical process

References

Alabbas, M., Khalaf, Z. A., & Khashan, K. M. (2014). BASRAH: An automatic system to identify the meter of Arabic poetry. Natural Language Engineering, 20(1), 131–149. https://doi.org/10.1017/S1351324913000319

Ammar, A., Koubaa, A., Benjdira, B., Najar, O., & Sibaee, S. (2023). Prediction of Arabic legal rulings using large language models (Version 1). arXiv preprint arXiv:2310.10260. https://doi.org/10.48550/ARXIV.2310.10260

Atabuzzaman, M., Shajalal, M., Baby, M. B., & Boden, A. (2023). Arabic sentiment analysis with noisy deep explainable model (Version 2). arXiv. http://doi.org/10.48550/ARXIV.2309.13731

Bamman, D., Underwood, T., & Smith, N. A. (2020). A computational approach to literary style. Journal of Cultural Analytics, 5(2), 1–25.

Bani Omar, K. A. (2023, November 30). Image semiotics in the book Our Arabic Language for the third grade in Jordan: An analytical study using human and artificial intelligence. European Scientific Journal, ESJ. European Scientific Institute, ESI. http://doi.org/10.19044/esj.2023.v19n32p158

Barthes, R. (1967). Elements of semiology. Hill and Wang.

Berg, A., & Valaskivi, K. (2023, November 14). Representational silence and racial biases in commercial image recognition services in the context of religion. In Handbook of critical studies of artificial intelligence. Edward Elgar Publishing. http://doi.org/10.4337/9781803928562.00062

Berkani, A., Holzer, A., & Stoffel, K. (2020, November). Pattern matching in meter detection of Arabic classical poetry. In 2020 IEEE/ACS 17th International Conference on Computer Systems and Applications (AICCSA) (pp. 1–8). IEEE. https://doi.org/10.1109/AICCSA51340.2020.9298180

Bogel, F. V. (2013). New formalist criticism. Palgrave Macmillan UK. https://doi.org/10.1057/9781137362599

Bosco, P. (2020). Artificial intelligence and the hidden patterns of narrative: A case study on Gabriel García Márquez’s One Hundred Years of Solitude. Literary Studies Review, 18(4), 101–115.

Brown, D. (2020). Artificial Intelligence and Literary Analysis in Arabic Texts: Challenges and Opportunities. Arab Studies Journal, 22(3), 77–94.

Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877–1901.

Derrida, J. (1976). Of grammatology. Johns Hopkins University Press.

Dinges, L., Al-Hamadi, A., Elzobi, M., & Nurnberger, A. (2017, September). Automatic recognition of common Arabic handwritten words based on OCR and N-grams. In 2017 IEEE International Conference on Image Processing (ICIP). IEEE. http://doi.org/10.1109/icip.2017.8296958

(2024, March 1). Employing artificial intelligence in teaching the Arabic language to non-native speakers remotely. Journal of Scientific Development for Studies and Research. The Academy of Creativity Sama for Studies, Consultations and Scientific Development. http://doi.org/10.61212/jsd/176

Failasuf, C., Jubaidah, S., Sarip, M., & Bahtiar, I. R. (2024). Analysis of the use of artificial intelligence-based applications in Arabic text automatic diacritization. In Advances in Social Science, Education and Humanities Research. Atlantis Press SARL. http://doi.org/10.2991/978-2-38476-240-8_12

Froud, H., Lachkar, A., & Ouatik, S. A. (2013). Arabic text summarization based on latent semantic analysis to enhance Arabic documents clustering (Version 1). arXiv. http://doi.org/10.48550/ARXIV.1302.1612

Gryaznova, E., Kirina, M., Mikhailova, P., Zarembo, V., & Moskvina, A. (2024). Machine learning and philology: An overview of methods and applications. In Springer Geography. Springer Nature Switzerland. http://doi.org/10.1007/978-3-031-50609-3_6

Gunawan, R., & Hidayatullah, M. S. (2024, April 26). The potential of use artificial intelligence in implementing character education in Arabic language subjects. Asalibuna. STAIN Kediri. http://doi.org/10.30762/asalibuna.v8i01.2718

Habeeb, F. A., & Moulood, K. J. (2023, March 1). Speech recognition for Arabic numbers using empirical mode decomposition. International Journal of Statistics and Applied Mathematics. AkiNik Publications. https://doi.org/10.22271/maths.2023.v8.i2a.940

Jiang, K. (2024, January 1). Artificial intelligence empowers emotional expression and aesthetic imagery in modern Chinese literature. Applied Mathematics and Nonlinear Sciences. Walter de Gruyter GmbH. http://doi.org/10.2478/amns-2024-0659

Lagrini, S., Azizi, N., Redjimi, M., & Dwairi, M. A. (2019). Automatic identification of rhetorical relations among intra-sentence discourse segments in Arabic. International Journal of Intelligent Systems Technologies and Applications. Inderscience Publishers. http://doi.org/10.1504/ijista.2019.099345

LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553), 436–444.

Literary Studies Journal. (2022). Ethical concerns in AI-based literary criticism: Implications for the future. 36(2), 145–158.

Mikherskii, R., & Mikherskii, M. (2023). Application of artificial intelligence systems for stylometric analysis of texts as factor of sustainable development. In A. Muratov & S. Khasanov (Eds.), E3S Web of Conferences. EDP Sciences. http://doi.org/10.1051/e3sconf/202337103007

Muaad, A. Y., Jayappa Davanagere, H., Benifa, J. V. B., Alabrah, A., Naji Saif, M. A., Pushpa, D., … Alfakih, T. M. (2022, March 26). Artificial intelligence-based approach for misogyny and sarcasm detection from Arabic texts. In A. M. Khalil (Ed.), Computational Intelligence and Neuroscience. Wiley. http://doi.org/10.1155/2022/7937667

Mukherjee, A., & Chang, H. (2023). The creative frontier of generative AI: Managing the novelty-usefulness tradeoff (Version 1). arXiv. http://doi.org/10.48550/ARXIV.2306.03601

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Published

2025-05-22

How to Cite

Muhammad, M. H. H. (2025). The Impact of Artificial Intelligence on Literary Criticism: Exploring Potentials and Limitations. Dzil Majaz: Journal of Arabic Literature, 3(1), 94–108. https://doi.org/10.58223/dzilmajaz.v3i1.378

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