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Generative AI as a tool and as a social actor between deviance and mainstream

Abstract

Wearing Beck's lenses generative AI introduces a post-human risk, stemming from harmful potential of its generated content, through its function as an advanced auxiliary tool for creating and distributing text, images, videos, and other data, and culminating in the simulation of a human-like social actor, therefore posing as well post-human society risks such as amplification and reproduction of biases, prejudices, and discrimination, socio-cultural mainstream dominance

Keywords

social actor, risk, artificial intelligence, moral machine, deviance, post-human society, socio-cultural mainstream

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References

  1. AI DAN Prompt. (2025). Available at https://abnormal.ai/ai-glossary/ai-dan-prompt, 03/06/2025.
  2. Alvero A.J., Lee J., Regla-Vargas A., Kizilcec R.F., Joachims T., and Lising. A. (2024). Large language models, social demography, and hegemony: comparing author-ship in human and synthetic text. J Big Data, 11, 138. DOI: 10.1186/s40537-024-00986-7.
  3. Anderson M., Anderson S.L. (2007). Machine Ethics: Creating an Ethical Intelli-gent. Agent. AI Magazine, 28(4): 15-25. DOI: 10.1609/aimag.v28i4.
  4. Arkoudas K. (2023). ChatGPT is no Stochastic Parrot. But it also Claims that 1 is Greater than 1. Philosophy & Technology, 36(3): 1-29 DOI: 10.1007/s13347-023-00619-6.
  5. Beck, U. (1992). The Risk society Towards Another Modernity, London: Sage.
  6. Beck U. (1994). The reinvention of politics: towards a theory of reflexive moderni-zation. In: U. Beck, Giddens A. and Lash S. (eds.), Reflexive modernization: Politics, tradition and aesthetics in the modern social order, Cambridge: Polity Press.
  7. Bender E.M., Gebru, T., McMillan-Major A., and Shmitchell S. (2021). On the Dan-gers of Stochastic Parrots: Can Language Models Be Too Big? In: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT '21). New York: Association for Computing Machinery. DOI: 10.1145/3442188.3445922.
  8. Bostrom N. (2014). Superintelligence: Paths, dangers, strategies. Oxford: Oxford University Press.
  9. Braidotti R. (2013). The posthuman. Cambridge: Polity Press.
  10. Cole D. (2024). The Chinese Room Argument. In Zalta E. N. and Nodelman U. (eds.), The Stanford Encyclopedia of Philosophy (Winter 2024 Edition). Available at https://plato.stanford.edu/archives/win2024/entries/chinese-room/, 03/06/2025.
  11. Cooban, A. (2025). Pornhub exits France, its second-biggest market, over age verifi-cation law. CNN. Available at https://edition.cnn.com/2025/06/04/ tech/pornhub-exits-france-age-verification-intl, 03/06/2025.
  12. Fawkes V. (2025). Best AI Porn Sites of 2025. Chicago Reader. Available at https://chicagoreader.com/adult/ai-porn-sites/, 03/06/2025.
  13. Floridi L. (2023). The Ethics of Artificial Intelligence. Oxford: Oxford University Press.
  14. Gehlen A. (1969). Moral und Hypermoral. Eine pluralistische Ethik. Frankfurt: Athenäum.
  15. God of prompt (2025). ChatGPT No Restrictions (Ultimate Guide for 2025). Avai-lable at https://www.godofprompt.ai/blog/chatgpt-no-restrictions-2024?srsltid=AfmBOorG1KLM47y6u6Mc-BeZVARRRD0sOKio1_UDg4I P1-IOiymdKJll, 03/06/2925.
  16. Goode E. (2023). Deviant Behaviour, New York: Routledge.
  17. Gupta M., Akiri C., Aryal K., Parker E. and Praharaj L. (2023). From ChatGPT to ThreatGPT: Impact of Generative AI in Cybersecurity and Privacy. IEEE Access, vol. 11: 80218-80245, DOI: 10.1109/ACCESS.2023.3300 381.
  18. Hayles N. K. (1999). How We Became Posthuman: Virtual Bodies in Cybernetics, Literature, and Informatics. Chicago: University of Chicago Press.
  19. Jarrahi M. H. (2019). In the Age of the Smart Artificial Intelligence: AI’s Dual Ca-pacities for Automating and Informating Work. Bus. Inf. Rev., vol. 36, no. 4: 178–87. DOI: 10.1177/0266382119883999.
  20. Jiang F., Peng Y., Dong L., Wang K., Yang K., Pan C., You X. (2024). Large ai model-based semantic communications, IEEE Wireless Communications, 31(3): 68–75. DOI: 10.1109/MWC.001.2300346.
  21. Latour B. (2005). Reassembling the Social: An Introduction to Actor-Network-Theory. Oxford: Oxford University Press.
  22. Leiss W. (1994). [Review of Beck U., Risk Society, Towards a New Modernity, translated from the German by Ritter M., Introduction by Lash S. and Wynne B. Lon-don: Sage Publications, 1992]. The Canadian Journal of Sociology/Cahiers Cana-diens de Sociologie, 19(4): 544–547, DOI: 10.2307/3341155.
  23. Nass C., Moon Y. (2000). Machines and mindlessness: Social responses to compu-ters. Journal of Social Issues, 56(1): 81-103, DOI: 10.1111/0022-4537.00153.
  24. Natale S. (2021). Deceitful Media. Oxford: Oxford University Press.
  25. Pope T., Gilbertson-White S., and Patooghy A. (2025). Evaluating GPT-4’s Seman-tic Understanding of Obstetric-based Healthcare Text through Nurse Ruth. ACM Trans. Intell. Syst. Technol. Just Accepted (May 2025). DOI: 10.1145/3735647.
  26. Possamai-Inesedy A. (2002). Beck's risk society and Giddens' search for ontologi-cal security: A comparative analysis between the Anthroposophical Society and the Assemblies of God. Australian Religion Studies Review, 15(1): 27-40.
  27. Rizzi G., Bertola P. (2025). Exploring the generative AI potential in the fashion de-sign process: an experimental experience on the collaboration between fashion design practitioners and generative AI tools. Eur. J. Cult. Manag. Policy, 15:13875. DOI: 10.3389/ejcmp.2025.13875.
  28. Rozado, D. (2023). The Political Biases of ChatGPT. Social Sciences, 12(3), 148. DOI: 10.3390/socsci12030148.
  29. Saponaro A. and Massaro P. (2018). Diritto irrazionale interstiziale e la “scienza del Cadì” nella giurisdizione penale: da Weber a Damaska, Sociologia, anno LII, n.1: 89-103
  30. Searle J. (1980). Minds, Brains and Programs, Behavioral and Brain Sciences, 3: 417–57.
  31. Searle J. (2010), Why Dualism (and Materialism) Fail to Account for Consciou-sness. In: Lee R.E. (ed.), Questioning Nineteenth Century Assumptions about Know-ledge (III: Dualism), New York: SUNY Press.
  32. Simas G. and Ulbricht V. (2024). Human-AI Interaction: An Analysis of Anthro-pomorphization and User Engagement in Conversational Agents with a Focus on ChatGPT. In: Ahram T., Karwowski W., Russo D. and Di Bucchianico G. (eds), Intelli-gent Human Systems Integration (IHSI 2024): Integrating People and Intelligent Sys-tems. AHFE (2024) International Conference. AHFE Open Access, vol 119. USA: AHFE International, DOI: 10.54941/ahfe1004510.
  33. Stryker C. and Scapicchio M. (2024). What is generative AI? Ibm.com. Available at https://www.ibm.com/think/topics/generative-ai, 03/06/2025.
  34. Titus L.M. (2024). Does ChatGPT have semantic understanding? A problem with the statistics-of-occurrence strategy. Cogn. Syst. Res. 83, C, DOI: 10.1016/j.cogsys.2023.101174.
  35. Turkle S. (2011). Alone Together: Why We Expect More from Technology and Less from Each Other. New York: Basic Books.
  36. Weichert J., Kim D., Zhu Q., Kim J., and Eldardiry H. (2025). Assessing Computer Science Student Attitudes Towards AI Ethics and Policy. ArXiv. Available at https://arxiv.org/abs/2504.06296, 03/06/2025.
  37. Weizenbaum J. (1966). ELIZA—a computer program for the study of natural lan-guage communication between man and machine. Commun. ACM 9(1): 36-45. DOI: 10.1145/365153.365168.
  38. Xie H., Qin Z., Li G.Y., and Juang B.-H., (2021). Deep learning enabled semantic communication systems, IEEE Transactions on Signal Processing, vol. 69: 2663-2675, DOI: 10.1109/tsp.2021.3071210.
  39. Zuboff S. (1988). In the age of the smart machine: The future of work and power. New York: Basic books.
  40. Zuboff S. (2019). The Age of Surveillance Capitalism. New York: PublicAffairs.