Is it Possible to Engage in Dialogue with Generative AI Technologies?

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Abstract

This study analyses the linguistic interaction of human beings with Generative Artificial Intelligence (GAI) technologies in terms of Hans-Georg Gadamer’s philosophical hermeneutics. It can thus be concluded that: i) a distinction must be drawn between imitating a function and possessing a property when dealing with the ontology of GAI; ii) GAI technologies are capable of imitating certain human-like mental functions without necessarily possessing the human-like properties that underpin these functions; iii) the transformation of perception that has occurred in the postmodern period, coupled with the perception that GAI possesses human-like properties, gives rise to an ontological illusion.

Keywords

Philosophy of technology

generative ai

Gadamer

philosophical hermeneutics

dialogue.

References

Aristotle. (1984). On The Soul. In J. Barnes (Ed.), The Complete Works of Aristotle (pp. 1405–1518). Princeton University Press.
Bakpayev, M., Baek, T. H., van Esch, P., & Yoon, S. (2022). Programmatic creative: AI can think but it cannot feel. Australasian Marketing Journal, 30(1), 90–95. https://doi.org/10.1016/j.ausmj.2020.04.002
Baudrillard, J. (1994). Simulacra and Simulation. University of Michigan Press.
Bellini, V., Cascella, M., Cutugno, F., Russo, M., Lanza, R., Compagnone, C., & Bignami, E. G. (2022). Understanding basic principles of Artificial Intelligence: A practical guide for intensivists: Basic Principles of Artificial Intelligence. Acta Biomedica Atenei Parmensis, 93(5), e2022297. https://doi.org/10.23750/abm.v93i5.13626
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610–623. https://doi.org/10.1145/3442188.3445922
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., Agarwal, S., Herbert-Voss, A., Krueger, G., Henighan, T., Child, R., Ramesh, A., Ziegler, D. M., Wu, J., Winter, C., … Amodei, D. (2020). Language Models are Few-Shot Learners (Version 4). arXiv. https://doi.org/10.48550/ARXIV.2005.14165
Carter, M. (2007). Minds and Computers. Edinburgh University Press.
Chang, E. Y. (2023). Prompting Large Language Models With the Socratic Method. 351–360.
Colombatto, C., & Fleming, S. M. (2024). Folk psychological attributions of consciousness to large language models. Neuroscience of Consciousness, 2024(1). https://doi.org/10.1093/nc/niae013
Dang, H., Mecke, L., Lehmann, F., Goller, S., & Buschek, D. (2022). How to Prompt? Opportunities and Challenges of Zero- and Few-Shot Learning for Human-AI Interaction in Creative Applications of Generative Models (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2209.01390
Dong, Z., Li, J., Men, X., Zhao, W. X., Wang, B., Tian, Z., Chen, W., & Wen, J.-R. (2024). Exploring Context Window of Large Language Models via Decomposed Positional Vectors. https://doi.org/10.48550/arXiv.2405.18009
Farina, M., Lavazza, A., Sartori, G., & Pedrycz, W. (2024). Machine learning in human creativity: Status and perspectives. AI & SOCIETY, 39(6), 3017–3029. https://doi.org/10.1007/s00146-023-01836-5
Farina, M., Pedrycz, W., & Lavazza, A. (2024). Towards a mixed human–machine creativity. Journal of Cultural Cognitive Science, 8(2), 151–165. https://doi.org/10.1007/s41809-024-00146-6
Floridi, L., & Chiriatti, M. (2020). GPT-3: Its Nature, Scope, Limits, and Consequences. Minds and Machines, 30(4), 681–694. https://doi.org/10.1007/s11023-020-09548-1
Gadamer, H.-G. (2004). Truth and Method. Continuum.
Genç, H. K. (2024). Yapay Zekanın Müzikal Yaratıcılığı: ChatGPT Örneği. Marmara Üniversitesi Sosyal Bilimler Enstitüsü Felsefe ve Din Bilimleri Anabilim Dalı.
Henrickson, L., & Meroño-Peñuela, A. (2023). Prompting meaning: A hermeneutic approach to optimising prompt engineering with ChatGPT. AI & SOCIETY. https://doi.org/10.1007/s00146-023-01752-8
Kant, I., & Gregor, M. J. (1998). Groundwork of the Metaphysics of Morals. Cambridge University Press. https://books.google.com.tr/books?id=Ibcy57Hz4tcC
Laçin, H. (2024). Gadamer Ontolojisindeki Köprüleri Yıkmak: Geç Dönem Energeia Kullanımının Oyun ve Organizma Kavramlarıyla Birlikte Düşünülmesi. Marmara Üniversitesi İlahiyat Fakültesi, 66(66), 101–121.
Merleau-Ponty, M. (2002). Phenomenology of Perception. Routledge.
Pan, X., Dai, J., Fan, Y., & Yang, M. (2024). Frontier AI systems have surpassed the self-replicating red line (Version 1). arXiv. https://doi.org/10.48550/ARXIV.2412.12140
Phuong, M., & Hutter, M. (2022). Formal Algorithms for Transformers. https://doi.org/10.48550/ARXIV.2207.09238
Searle, J. (1980). Minds, brains, and programs. Behavioral and Brain Sciences, 3(3), 417–457.
Shank, D. B., Graves, C., Gott, A., Gamez, P., & Rodriguez, S. (2019). Feeling our way to machine minds: People’s emotions when perceiving mind in artificial intelligence. Computers in Human Behavior, 98, 256–266. https://doi.org/10.1016/j.chb.2019.04.001
Sullins, J. P. (2006). When Is a Robot a Moral Agent? Nternational Review of Information Ethics, 6(12), 24–30.
Turing, A. (1950). Computing Machinery and Intelligence. Mind, 49, 433–460.
Wang, J. (2021). Is artificial intelligence capable of understanding? An analysis based on philosophical hermeneutics. Cultures of Science, 4(3), 135–146.
Yıldız, B. (2023). Modern Dönemde Oyun Olarak Sanat. İstanbul Üniversitesi Sosyal Bilimler Enstitüsü.
Zhou, Y., Muresanu, A. I., Han, Z., Paster, K., Pitis, S., Chan, H., & Ba, J. (2022). Large Language Models Are Human-Level Prompt Engineers (Version 2). arXiv. https://doi.org/10.48550/ARXIV.2211.01910

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