NARRATIVE ALGORITHMS AND SUBJECT FORMATION: A PHILOSOPHICAL INQUIRY INTO STUDENT STORYTELLING IN THE AGE OF ARTIFICIAL INTELLIGENCE

Laura  TURARBEKOVA; Dinara  SAPAROVA; Zhanday KDYRALIEVA

doi:10.32523/3080-1281-2026-155-2-19-35

Authors

Laura TURARBEKOVA Almaty Humanitarian-Economic University Author https://orcid.org/0000-0003-3416-0160
Dinara SAPAROVA Astana International University Author https://orcid.org/0009-0007-8548-7741
Zhanday KDYRALIEVA Almaty Humanitarian-Economic University Author https://orcid.org/0000-0001-9381-6516

DOI:

https://doi.org/10.32523/3080-1281-2026-155-2-19-35

Keywords:

Artificial intelligence in education; narrative identity; subject formation; student storytelling; algorithmic mediation; human-AI co-authorship; digital agency; educational philosophy

Abstract

The rapid integration of artificial intelligence into educational environments has transformed not only instructional practices but also the conditions under which subjectivity is formed. This article offers a philosophical reflection on student storytelling in the age of AI, examining how narrative algorithms influence processes of subject formation. Drawing on the philosophical tradition that understands narrative as a key mode of self-constitution, the study conceptualizes storytelling as a space where learners construct identity, agency, and moral positioning. The paper then analyzes the algorithm as a form of meaning-structuring, emphasizing mechanisms of algorithmic selection and digital mediation that shape available narrative patterns. In AI-assisted writing practices, student storytelling increasingly emerges as a form of human-machine co-authorship, resulting in a redistribution of agency between learner and system. While such collaboration may expand expressive possibilities, it also introduces risks, including the standardization of identity and the subtle normalization of culturally dominant narrative templates. The article argues that AI does not eliminate subjectivity but transforms its mode of emergence, shifting it toward hybrid and relational forms. The conclusion outlines directions for future empirical research aimed at examining how students negotiate authorship, responsibility, and ethical self-understanding within AI-mediated educational contexts.

Downloads

Download data is not yet available.

References

Adadi, A., & Berrada, M. (2018). Peeking inside the black-box: A survey on explainable artificial intelligence (XAI). IEEE Access, 6, 52138–52160. https://doi.org/10.1109/ACCESS.2018.2870052

Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (pp. 610–623). Association for Computing Machinery. https://doi.org/10.1145/3442188.3445922

Bommasani, R., Hudson, D., Adeli, E., Altman, R., Arora, S., Arx, S., Bernstein, M., Bohg, J., Bosselut, A., Brunskill, E., Brynjolfsson, E., Buch, S., Card, D., Castellon, R., Chatterji, N., Chen, A., Creel, K., Davis, J., Demszky, D., & Liang, P. (2021). On the opportunities and risks of foundation models. arXiv. https://doi.org/10.48550/arXiv.2108.07258

Bouchardon, S., & Fülöp, E. (2024). Récit numérique et temporalité. Sens public. https://hal.science/hal-04908130v1/file/SP1719.pdf

Bourdieu, P. (1977). Outline of a theory of practice. Cambridge University Press.

Bourdieu, P. (1990). The logic of practice. Stanford University Press.

Bucher, T. (2018). If… then: Algorithmic power and politics. Oxford University Press. https://doi.org/10.1093/oso/9780190493028.001.0001

Burrell, J. (2016). How the machine “thinks”: Understanding opacity in machine learning algorithms. Big Data & Society, 3(1). https://doi.org/10.1177/2053951715622512

Capurro, R. (2010). Digital hermeneutics: An outline. AI & Society, 25(1), 35–42.

Chen, Y., Wang, Y., Wüstenberg, T., Kizilcec, R. F., Fan, Y., Li, Y., Lu, B., Yuan, M., Zhang, J., Zhang, Z., Geldsetzer, P., Chen, S., & Bärnighausen, T. (2025). Effects of generative artificial intelligence on cognitive effort and task performance: Study protocol for a randomized controlled experiment among college students. Trials, 26(1), 244. https://doi.org/10.1186/s13063-025-08950-3

Choudhuri, R., Sanchez, C. A., Burnett, M., & Sarma, A. (2026). Why Johnny can't think: GenAI's impacts on cognitive engagement. arXiv. https://doi.org/10.48550/arXiv.2601.22430

Clark, A., & Chalmers, D. (1998). The extended mind. Analysis, 58(1), 7–19. http://www.jstor.org/stable/3328150

Essel, H. B., Vlachopoulos, D., Essuman, A. B., & Amankwa, J. O. (2024). ChatGPT effects on cognitive skills of undergraduate students: Receiving instant responses from AI-based conversational large language models (LLMs). Computers and Education: Artificial Intelligence, 6, 100198. https://doi.org/10.1016/j.caeai.2023.100198

Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Lütge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., & Vayena, E. (2018). AI4People – An ethical framework for a good AI society: Opportunities, risks, principles, and recommendations. Minds and Machines, 28(4), 689–707. https://doi.org/10.1007/s11023-018-9482-5

Foucault, M. (1988). Technologies of the self. In L. H. Martin, H. Gutman, & P. H. Hutton (Eds.), Technologies of the self: A seminar with Michel Foucault (pp. 16–49). University of Massachusetts Press.

Fricker, M. (2007). Epistemic injustice: Power and the ethics of knowing. Oxford University Press. https://doi.org/10.1093/acprof:oso/9780198237907.001.0001

Gerlich, M. (2025). AI tools in society: Impacts on cognitive offloading and the future of critical thinking. Societies, 15(1), 6. https://doi.org/10.3390/soc15010006

Gillespie, T. (2014). The relevance of algorithms. In T. Gillespie, P. J. Boczkowski, & K. A. Foot (Eds.), Media technologies: Essays on communication, materiality, and society (pp. 167–194). MIT Press.

Haraway, D. (1991). A cyborg manifesto: Science, technology, and socialist-feminism in the late twentieth century. In Simians, cyborgs, and women: The reinvention of nature (pp. 149–181). Routledge.

Hassan, R. (2020). The condition of digitality: A post-modern Marxism for the practice of digital life. University of Westminster Press. http://www.jstor.org/stable/j.ctvw1d5k0

Hayles, N. K. (2017). Unthought: The power of the cognitive nonconscious. University of Chicago Press.

Heersmink, R., de Rooij, B., Clavel Vázquez, M. J., & Colombo, M. (2024). A phenomenology and epistemology of large language models: Transparency, trust, and trustworthiness. Ethics and Information Technology, 26, 41. https://doi.org/10.1007/s10676-024-09777-3

Humphreys, P. (2009). The philosophical novelty of computer simulation methods. Synthese, 169(3), 615–626. http://www.jstor.org/stable/40271312

Ihde, D. (1990). Technology and the lifeworld. Indiana University Press.

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., et al. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Kemper, N. F., Martin, T., Cohrs, L., Schmiedek, F., & Habermas, T. (2025). Agency and communion in brief entire life narratives across the life span. Journal of Personality, 93(5), 1042–1054. https://doi.org/10.1111/jopy.12990

Kitchin, R. (2017). Thinking critically about and researching algorithms. Information, Communication & Society, 20(1), 14–29. https://doi.org/10.1080/1369118X.2016.1154087

Latour, B. (2006). Nous n’avons jamais été modernes: Essai d’anthropologie symétrique. La Découverte. https://doi.org/10.3917/dec.latou.2006.01

Lazar, S. (2024). Automatic authorities: Power and AI. In D. Heersmink & J. Symons (Eds.), The Oxford handbook of philosophy of AI. MIT Press. https://doi.org/10.7551/mitpress/14962.003.0004

Manovich, L. (2019). AI aesthetics. Strelka Press.

Meretoja, H., Kinnunen, E., & Kosonen, P. (2022). Narrative agency and the critical potential of metanarrative reading groups. Poetics Today, 43(2), 387–414. https://doi.org/10.1215/03335372-9642679

Noble, S. U. (2018). Algorithms of oppression: How search engines reinforce racism. New York University Press.

Ricoeur, P. (1984). Time and narrative (Vol. 1). University of Chicago Press. (Original work published 1983)

Ricoeur, P. (1990). Soi-même comme un autre. Seuil.

Rosa, H. (2013). Social acceleration: A new theory of modernity. Columbia University Press.

Stiegler, B. (1998). Technics and time, 1: The fault of Epimetheus. Stanford University Press.

Stiegler, B. (2010). What makes life worth living: On pharmacology. Polity Press.

Striphas, T. (2015). Algorithmic culture. European Journal of Cultural Studies, 18(4–5), 395–412.

Taylor, C. (1989). Sources of the self: The making of the modern identity. Harvard University Press.

Turarbekova, L. V. (2022). Ischeznovenie ob’ekta: Realizacija hajdeggerianskogo jadernogo fantazma i internet veshhej [The disappearance of the object: The realization of the Heideggerian nuclear phantasm and the Internet of things]. Vestnik KazNU im. Al-Farabi. Serija filosofii, kul’turologii i politologii, 79(1), 22–29. https://doi.org/10.26577/jpcp.2022.v79.i1.03

Turarbekova, L. V. (2022a). Vopros o kiborge [The question of the cyborg]. Medicinskaja antropologija i biojetika, 23(1). https://doi.org/10.33876/2224-9680/2022-1-23/12

Turarbekova, L., Nurysheva, G., Sartayeva, R., & Muursepp, P. (2024). My little cyborg: Human, machine, and the philosophical paradoxes of difficult humanism. ICON, 29(2), 109–126. https://doi.org/10.11590/icon.2024.2.05

van Doeselaar, L., & Reitz, A. K. (2023). Personal narratives as a predictor of trait change and state fluctuations in self-esteem and life satisfaction during the transition from education to work. Identity: An International Journal of Theory and Research, 23(1), 18–35. https://doi.org/10.1080/15283488.2022.2106229

Wang, J., & Fan, W. (2025). The effect of ChatGPT on students’ learning performance, learning perception, and higher-order thinking: Insights from a meta-analysis. Humanities and Social Sciences Communications, 12, 621. https://doi.org/10.1057/s41599-025-04787-y

Wu, X., Zhao, H., Zhu, Y., Shi, Y., Yang, F., Hu, L., Liu, T., Zhai, X., Yao, W., Li, J., Du, M., & Liu, N. (2024). Usable XAI: 10 strategies towards exploiting explainability in the LLM era. arXiv. https://doi.org/10.48550/arXiv.2403.08946

Zhai, X. (2023). ChatGPT: Reforming education on five aspects. Shanghai Education, 16–17. https://ssrn.com/abstract=4389098

Zuboff, S. (2019). The age of surveillance capitalism. PublicAffairs.