THE IMAGE OF THE FUTURE AS A FORM OF MYTHMAKING IN THE CONTEXT OF ARTIFICIAL INTELLIGENCE
DOI:
https://doi.org/10.31392/cult.alm.2026.3.20Keywords:
image of the future, myth, mythmaking, artificial intelligence, imaginary, archetype, Gilbert Durand, Nick Bostrom, typology of images of the future, structural-symbolic analysisAbstract
The article examines the image of the future as a form of contemporary myth-making in the context of the development of artificial intelligence. Drawing on a synthesis of the approaches of E. Cassirer, M. Eliade, C. Lévi-Strauss, C.G. Jung, R. Barthes, R. May and G. Durand, myth-making is understood as the process of creating, organizing and transforming symbolic images, archetypal structures, values and socio-cultural conceptions into coherent narratives. On this basis, the article substantiates an understanding of the image of the future as a form of myth-making: the fundamental indeterminacy of the future is compensated for by the work of the imagination, which converts it into images and narratives organized in terms of meaning and value. Conceptualizing the image of the future as a form of myth-making makes it possible to reveal the mechanisms of its symbolization, archetypal structuring, evaluative interpretation and narrative organization. The methodological foundation of the study is G. Durand’s figurative structuralism; structural-symbolic analysis, hermeneutic, typological and comparative methods are applied, along with theoretical analysis, synthesis and generalization. The author’s archetypal typology of images of the future is tested on the material of N. Bostrom’s Superintelligence: Paths, Dangers, Strategies and contemporary research on AI. Three types are identified – progressive-heroic, regressive-harmonious and synthetic-cyclical – which differ in the way they organize historical time, in the character of the transformation they envisage, and in the symbolic logic of the interaction between the human being and the world. In the context of artificial intelligence, these types acquire specific myth-making forms: “superintelligence as savior / superintelligence as destroyer”, “digital guardian / benevolent tyrant”, and “co-evolution / cyclical trap”. In the course of testing, the typology was refined by the principle of ambivalence, according to which each archetypal structure is capable of generating scenarios opposite in their value orientation while retaining its own symbolic logic. The results obtained can serve as a methodological instrument for the structural-symbolic analysis of images of the future and of the processes by which they are constructed through myth-making.
References
Bareis J., Ackerl C. & Heil R. (2026). AI going rogue? An integrative narrative review of the tacit assumptions underlying existential AI-risks. AI Ethics, 6, 152. https://doi.org/10.1007/s43681-025-00928-w.
Barthes R. (1957). Mythologies. Paris: Éditions du Seuil, 272 p.
Bentivegna F. (2025). Artificially voiced intelligences: voice and the myth of AI. AI & Society, 41 (3), 1749–1760. https://doi.org/10.1007/s00146-025-02383-x.
Berlinski E., Morales J. & Sponem S. (2024). Artificial imaginaries: Generative AIs as an advanced form of capitalism. Critical Perspectives on Accounting, 99, 102723. https://doi.org/10.1016/j.cpa.2024.102723.
Bory P., Natale S. & Katzenbach C. (2025). Strong and weak AI narratives: an analytical framework. AI & Society, 40, 2107–2117. https://doi.org/10.1007/s00146-024-02087-8.
Bostrom N. (2014). Superintelligence: Paths, Dangers, Strategies. Oxford: Oxford University Press, 352 p.
Brause S.R., Schäfer M.S., Katzenbach C., Mao Y., Richter V. & Zeng J. (2025). Sociotechnical imaginaries and public communication: Analytical framework and empirical illustration using the case of artificial intelligence. Convergence: The International Journal of Research into New Media Technologies, 31 (4), 1267–1287. https://doi.org/10.1177/13548565251338192.
Cassirer E. (2021). An essay on man: An introduction to a philosophy of human culture. London, New Hawen: Yale University Press, 237 p.
Denia E. (2025). AI narratives model: Social perception of artificial intelligence. Technovation, 146, 103266. https://doi.org/10.1016/j.technovation.2025.103266.
Dishon G. (2024). From Monsters to Mazes: Sociotechnical Imaginaries of AI Between Frankenstein and Kafka. Postdigital Science and Education, 6, 962–977. https://doi.org/10.1007/s42438-024-00482-4.
Durand G. (1963). Les structures anthropologiques de l’imaginaire: Introduction à l’archétypologie générale (2e éd.). Paris: Presses Universitaires de France. 506 p.
Eliade M. (1963). Myth and reality (W.R. Trask, Trans.). New York: Harper & Row. 204 p.
Hendriks A., Karhunmaa K. & Delvenne P. (2025). Shaping the future: A conceptual review of sociotechnical imaginaries. Futures, 170, 103607. https://doi.org/10.1016/j.futures.2025.103607.
Inloes A. (2025). The Golem, the Djinni, and ChatGPT: Artificial Intelligence and the Islamicate Occult Sciences. Theology and Science, 23 (1), 147–166. https://doi.org/10.1080/14746700.2024.2436785.
Jung C. G. (1968). Archetypes of the collective unconscious. In H. Read, M. Fordham, G. Adler & W. McGuire (Eds.), The collected works of C.G. Jung (R.F.C. Hull, Trans.; Vol. 9, Pt. 1, pp. 1–41). New York: Princeton University Press.
Jung, C. G. (1968). The psychology of the child archetype. In H. Read, M. Fordham, G. Adler & W. McGuire (Eds.). The collected works of C. G. Jung (R.F.C. Hull, Trans.; Vol. 9, Pt. 1. P. 151–181). New York: Princeton University Press.
Kasirzadeh A. (2025). Two types of AI existential risk: decisive and accumulative. Philosophical Studies, 182, 1975–2003. https://doi.org/10.1007/s11098-025-02301-3.
Kasirzadeh A. & Gabriel I. (2023). In Conversation with Artificial Intelligence: Aligning language Models with Human Values. Philosophy & Technology. 36. https://doi.org/10.1007/s13347-023-00606-x.
Kurzweil R. (2024). The Singularity Is Nearer: When We Merge with AI. Penguin Publishing Group. 432 p.
Laba N. (2026). Whose imagination? Conflicting narratives and sociotechnical futures of visual generative AI. AI & Society, 41, 2279–2295. https://doi.org/10.1007/s00146-025-02675-2.
Lévi-Strauss C. (1955). The structural study of myth. The Journal of American Folklore, 68 (270), 428–444. https://doi.org/10.2307/536768.
May R. (1991). The cry for myth. New York, London: W.W. Norton & Company, 320 p.
Oldenburg N. & Papyshev G. (2025). The stories we govern by: AI, risk, and the power of imaginaries. Proceedings of the Eighth AAAI/ACM Conference on AI, Ethics, and Society (AIES 2025), 1939–1950. https://doi.org/10.1609/aies.v8i2.36686.
Pedreschi D., Pappalardo L., Ferragina E., Baeza-Yates R., Barabási A.-L., Dignum F., Dignum V., Eliassi-Rad T., Giannotti F., Kertész J., Knott A., Ioannidis Y., Lukowicz P., Passarella A., Pentland A.S., Shawe-Taylor J. & Vespignani A. (2025). Human-AI coevolution. Artificial Intelligence, 339, 104244. https://doi.org/10.1016/j.artint.2024.104244.
Thorstad D. (2025). Against the singularity hypothesis. Philosophical Studies, 182, 1627–1651. https://doi.org/10.1007/s11098-024-02143-5.
Wang W. & Downey J. (2025). Mapping the sociotechnical imaginaries of generative AI in UK, US, Chinese and Indian newspapers. Public Understanding of Science, 34 (7), 930–948. https://doi.org/10.1177/09636625251328518.
Yudkowsky E. & Soares N. (2025). If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All. Little, Brown and Company.
Zhong B., Song Y., Feng G.C., Shi J., Zhu Y., Xie L., Zhou W.A., Yu S., Lu Y., Qin Y. & Xiong Z. (2025). AI imaginaries shape technological identity and digital futures. Computers in Human Behavior, 169, 108682. https://doi.org/10.1016/j.chb.2025.108682.
Новикова В. (2025). Типологія образів майбутнього в контексті образного структуралізму Жільбера Дюрана. Вісник Київського Авіаційного Інституту. Серія: Філософія. Культурологія, 42 (2), 79–86. https://doi.org/10.18372/2412-2157.42.21027.
Хамітов Н. (2026). Взаємодія людини і штучного інтелекту: методологія осмислення викликів і перспектив. Вісник Національної академії наук України, (7), 13–23. https://doi.org/10.15407/visn2026.07.013.
