Did the Oracles of Delphi Shape the Tragedies? On the Economics of Predictive Processing
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Although predicting the future is a fundamental cognitive capacity that enables humans to plan and adapt to their environment, under certain conditions it can shift from a cognitive tool to a powerful force shaping perception, emotion, behavior, and real-life outcomes. This conceptual article analytically examines the role of future-oriented predictions, expectations, and beliefs in the formation of self-fulfilling cycles, anxiety, and psychosomatic consequences. Drawing on the concept of the self-fulfilling prophecy, predictive processing theory, the free-energy principle, and research on confirmation bias, the article argues that humans do not merely predict the future; through attention, interpretation, and action, they may actively help construct the futures they anticipate. When a threatening prediction is accepted with excessive certainty, it can narrow the range of perceived possibilities and organize perception, physiological responses, and protective behaviors around that anticipated outcome. In the domain of mental health and medicine, this process becomes evident through heightened health anxiety, increased attention to bodily sensations, nocebo responses, and the amplification of psychosomatic distress. The article emphasizes that the central challenge is not eliminating prediction and foresight, but developing flexible anticipation, calibrating certainty appropriately, and staying open to revising future assumptions. Predictions should therefore be understood as probabilistic hypotheses rather than fixed verdicts, incorporating evidence, limitations, and constructive pathways for action. This perspective provides a novel framework for understanding the relationship between future-oriented cognition, anxiety, human behavior, and mental health in an era increasingly shaped by predictive technologies and continuous information flows. Importantly, this article presents a theoretical synthesis rather than an empirical model, and its proposed relationships should be understood as conceptual pathways that require further experimental and clinical investigation.
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Brady, W. J., Doyle, M., Elnakouri, A., Finkel, E. J., Jackson, J. C., Kteily, N., Parker, V., Puryear, C., Spelman, T., & Teeny, J. (2026). Redesigning algorithms to intervene on social norm misperceptions during a national election. Nature, 1-15. https://doi.org/10.1038/s41586-026-10536-1
Clark, A. (2013). Whatever next? Predictive brains, situated agents, and the future of cognitive science. Behavioral and Brain Sciences, 36(3), 181-204. https://doi.org/10.1017/S0140525X12000477
Colloca, L., & Barsky, A. J. (2020). Placebo and nocebo effects. New England Journal of Medicine, 382(6), 554-561. https://doi.org/10.1056/NEJMra1907805
Costello, T. H., Pennycook, G., & Rand, D. G. (2024). Durably reducing conspiracy beliefs through dialogues with AI. Science, 385(6714), eadq1814. https://doi.org/10.1126/science.adq1814
Friston, K. (2010). The free-energy principle: a unified brain theory? Nature Reviews Neuroscience, 11(2), 127-138. https://doi.org/10.1038/nrn2787
Glickman, M., & Sharot, T. (2025). How human–AI feedback loops alter human perceptual, emotional and social judgments. Nature Human Behavior, 9(2), 345-359. https://doi.org/10.1038/s41562-024-02077-2
Goli, F. (2016). Biosemiotic medicine. Springer. https://doi.org/10.1007/978-3-319-35092-9
Hackenburg, K., Tappin, B. M., Hewitt, L., Saunders, E., Black, S., Lin, H., Fist, C., Margetts, H., Rand, D. G., & Summerfield, C. (2025). The levers of political persuasion with conversational artificial intelligence. Science, 390(6777), eaea3884. https://doi.org/10.1126/science.aea3884
Jervis, R. (1978). Cooperation under the security dilemma. World Politics, 30(2), 167-214. https://doi.org/10.2307/2009958
Liekefett, L., Christ, O., & Becker, J. C. (2023). Can conspiracy beliefs be beneficial? Longitudinal linkages between conspiracy beliefs, anxiety, uncertainty aversion, and existential threat. Personality and Social Psychology Bulletin, 49(2), 167-179. https://doi.org/10.1177/01461672211060965
Merton, R. K. (1948). The self-fulfilling prophecy. The Antioch Review, 8(2), 193-210. https://doi.org/10.2307/4609267
Milli, S., Carroll, M., Wang, Y., Pandey, S., Zhao, S., & Dragan, A. D. (2025). Engagement, user satisfaction, and the amplification of divisive content on social media. PNAS nexus, 4(3), pgaf062. https://doi.org/10.1093/pnasnexus/pgaf062
Nickerson, R. S. (1998). Confirmation bias: A ubiquitous phenomenon in many guises. Review of General Psychology, 2(2), 175-220. https://doi.org/10.1037/1089-2680.2.2.175
Rotolo, C. (2025). 30% of Americans Consult Astrology, Tarot Cards or Fortune Tellers. In: Washington, DC: Pew Research Center. https://www. pewresearch. org/religion ….
Salvi, F., Horta Ribeiro, M., Gallotti, R., & West, R. (2025). On the conversational persuasiveness of GPT-4. Nature Human Behavior, 9(8), 1645-1653. https://doi.org/10.1038/s41562-025-02194-6
Seth, A. K., & Friston, K. J. (2016). Active interoceptive inference and the emotional brain. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1708), 20160007. https://doi.org/10.1098/rstb.2016.0007
Steyvers, M., Tejeda, H., Kumar, A., Belem, C., Karny, S., Hu, X., Mayer, L. W., & Smyth, P. (2025). What large language models know and what people think they know. Nature Machine Intelligence, 7(2), 221-231. https://doi.org/10.1038/s42256-024-00976-7
Wason, P. C. (1960). On the failure to eliminate hypotheses in a conceptual task. Quarterly journal of experimental psychology, 12(3), 129-140. https://doi.org/10.1080/17470216008416717
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