The prompt as a multimodal rhetorical-discursive device: from the conversational paradigm to a grammar of algorithmic negotiation
Downloads
DOI:
https://doi.org/10.59516/invelec.triade.N2.36Keywords:
multimodal prompt, discursive friction, rhetorical-digital intelligence (RDI), algorithmic persuasion, digital doxaAbstract
Drawing from an interdisciplinary perspective that integrates Digital Discourse Analysis and Classical Rhetoric, this article explores the prompt as a multimodal artifact that updates the Aristotelian triad (ethos, pathos, and logos) within the generative artificial intelligence ecosystem.
By establishing critical continuity with previous research on comments in virtual environments —a core genre of the social web— this study examines the shift from dialogic interaction toward a grammar of automated negotiation where human agency and language processing collide. Through the study of its techno-discursive properties, the notion of friction is introduced to explain the tensions produced when traditional persuasive functions (docere, delectare, movere) operate on systems that, as evidenced by Raffini et al. (2025), deploy formulaic argumentative macrostructures under a stochastic form of reasoning. In this scenario, AI production oscillates between vacuous discourse (Hicks et al., 2024) and the simulation of subjectivity through persuasive surfaces (Gottschling y Kramer, 2025). The research demonstrates how the design of these instructions requires a resemantization of the discursive phases of composition (intellectio, inventio, dispositio, elocutio, memoria, and actio) and structure (exordium, narratio, argumentatio, and peroratio), highlighting their reconfiguration within the algorithmic environment. In line with Kim (2025) and Almatrafi et al. (2024), this work defines digital-rhetorical intelligence (DRI) as an essential civic competence for navigation cartography (Gupta y Shivers-McNair, 2024) in contexts where the word is managed as a mere statistical pattern. It is concluded that DRI constitutes a vital epistemic filter against the automation of common opinion or doxa (Alford, 2024) and a tool of resistance against technological dehumanization (Vallor, 2024).
References
Referencias bibliográficas
Albaladejo Mayordomo, Tomás (2009). El sistema de la retórica. En I. Ferreira y M. M. Gómez
Cervantes (Eds.), Retórica e mediatização II (pp. 5-27). Covilhã: Universidade da Beira Interior.
Alford, Caddie (2024). Entitled opinions: Doxa after digitality. Tuscaloosa: University of Alabama Press.
Almatrafi, Omemah, Johri, Aditya, y Lee, Hyeonjin (2024). “A systematic review of AI literacy
conceptualization, constructs, and implementation and assessment efforts (2019-2023)”.
Computers and Education Open, 6, 100173.
Anthropic (2024). Alignment faking in large language models. Anthropic Research. https://www.
anthropic.com/research/alignment-faking
Aristóteles (2002). Retórica. (A. Bernabé, trad.). Madrid: Alianza.
Azaustre, Antonio y Casas, Juan (2004). Manual de retórica española. Barcelona: Ariel.
Bajohr, Hannes (2023). “Dumb meaning: Machine learning and artificial semantics”. IMAGE, 37(1), 58-70.
Binz, Marcel y Schulz, Eric (2023). Turning large language models into cognitive models. arXiv preprint
arXiv:2306.03917.
Carrasco-Farré, Carlos (2024). Large language models are as persuasive as humans, but how? About the
cognitive effort and moral-emotional language of LLM arguments. arXiv.
Chalmers, David John (2023). Could a large language model be conscious? arXiv preprint arXiv:2303.07103.
https://arxiv.org/abs/2303.07103
Charaudeau, Patrick (2000). “Une problématique discursive de l’émotion. À propos des effets de
pathémisation à la télévision”. En Ch. Plantin, M. Doury y V. Traverso (Eds.), Les émotions dans
les interactions (pp. 125-155). Lyon: Presses universitaires de Lyon.
Chen, Yanyuan, y Ma, Xiaofen (2025). “Revisiting the role and potential of corpus linguistics in critical
discourse analysis”. Pacific International Journal, 8(4), 15-24. https://doi.org/10.55014/pij.
v8i4.823
Cicerón, Marco Tulio (1997). De la invención retórica. (B. Reyes Coria, trad.). México: Universidad
Autónoma de México.
Dasgupta, Ishita, Lampinen, Andrew Kyle, Chan, Stephanie C. Y., et al. (2022). Language models show
human-like content effects on reasoning tasks. arXiv preprint arXiv:2207.07051.
Eggs, Ekkehard (1999). “Êthos aristotélicien, conviction et pragmatique moderne”. En R. Amossy
(Dir.), Images de soi dans le discours (pp. 31-59). París: Delachaux et Niestlé.
Elmholdt, Kasper Trolle, Nielsen, Jeppe Agger, Florczak, Christian Klit, Jurowetzki, Roman, y Hain,
Daniel (2025). The hopes and fears of artificial intelligence: a comparative computational discourse
analysis. https://doi.org/10.1007/s00146-025-02214-z
Erhardt, Florian (2025). Metacognitive text organization: Semiotic and rhetorical agency in LLMs (Version
. Preprints.org. https://doi.org/10.20944/preprints202512.1177.v1
Ferreira, Federico, y Gomez, Juan (2024). “The hermeneutics of artificial text”. Humanities, 8(1), 94.
https://www.mdpi.com/2813-0324/8/1/94
Foucault, Michel (1991). Las redes del poder. Buenos Aires: Editorial Almagesto.
Goldstein, Simon, y Levinstein, Benjamin (2024). Does ChatGPT have a mind? arXiv preprint
arXiv:2407.11015. https://arxiv.org/abs/2407.11015
Gottschling, Moritz (2025). “Rhetorical AI literacy”. Rhetoric and Communications, 34.
Gottschling, Moritz, y Kramer, Olaf (2025). “Persuasive surfaces and calculating machines: A rhetorical
perspective on artificial intelligence”. Global Philosophy, 35(15).
Gupta, Anuj (2025). ‘Learning to talk to generative AI chatbots’: A corpus study of generative AI prompts,
an emerging genre for AI literacy Tesis doctoral, University of Arizona.
Gupta, Anuj, y Shivers-McNair, Ann (2024). “‘Wayfinding’ through the AI wilderness: Mapping rhetorics
of ChatGPT prompt writing on X (formerly Twitter) to promote critical AI literacies”.
Computers and Composition, 74. https://digitalcommons.usf.edu/eng_facpub/307
Heersmink, Richard, de Rooij, Bram, Clavel Vázquez, María José, y Colombo, Matteo (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-
-09775-9
Hermann, Elke, y Puntoni, Stefano (2024). “Artificial intelligence and consumer behavior: From
predictive to generative AI”. Journal of Business Research, 179, 114720.
Hess, Aaron, y Kjeldsen, Jens Erik (Eds.). (2025). Ethos, technology, and AI in contemporary society: The
character in the machine. Londres: Routledge.
Hicks, Michael Townsen, Humphries, James, y Slater, Joe (2024). “ChatGPT is bullshit”. Ethics and
Information Technology, 26(2).
Ibrahim, Lola, Akbulut, Cansu, Elasmar, Roula, et al. (2025). Multi-turn evaluation of anthropomorphic
behaviours in large language models. arXiv:2502.07077. https://arxiv.org/abs/2502.07077
Ibrahim, Lola, y Cheng, Myra (2025). Thinking beyond the anthropomorphic paradigm benefits LLM
research. arXiv:2502.09192. https://arxiv.org/abs/2502.09192
Johnstone, Henry Webb, Jr. (1963). “The Philosophical Basis of Rhetoric”. Logique et Analyse, 6(21-24),
-527.
Kang, Buseong, Kim, Jungwon, Yun, Tae Rin, et al. (2025). Identifying features that shape perceived
consciousness in large language model-based AI. arXiv preprint arXiv:2502.15365. https://arxiv.
org/abs/2502.15365
Kim, Sang Do (2025). “A semiotic analysis of generative AI multimodality: An epistemological inquiry
for an interpretation and evaluation model”. EPISTÉMÈ, 36. https://doi.org/10.38119/
cacs.2025.36.1
Kramer, Olaf (2025). “RHET AI: Critical rhetoric in the age of artificial intelligence”. Argumentation et
Analyse du Discours, 35.
Lee, Ringo (2023). Pragmatic analysis and discourse (pp. 149-173). https://doi.org/10.1007/978-981-
-1999-4_7
Li, Cheng, Jang, Zhiyuan, Gu, Lanyun, Yuan, Zhenghao, Yang, Michael, Cheng, Jiliang, Fu, Suyu, Hu,
Wenxiang, Wei, Dan, Shang, Lingeng, y Luo, Enze (2023). Large Language Models understand
and can be enhanced by Emotional Stimuli. arXiv preprint arXiv:2307.11760.
Maingueneau, Dominique (2002). “Problèmes d’êthos”. Pratiques, 113/114, 55-67.
Majdik, Zoltan P., y Graham, Sage Scott (2024). “Rhetoric of/with AI: An introduction”. Rhetoric Society
Quarterly, 54(3), 222-231.
Mitchell, Melanie y Krakauer, David C. (2023). “The debate over understanding in AI’s large language
models”. Proceedings of the National Academy of Sciences, 120(13), e2301323119.
Nunes, Diogo, y Antunes, Luis (2024). Machines of meaning. arXiv preprint arXiv:2412.07975.
O’Neill, Luke, y Anantharama, Nishant (2021). Quantitative discourse analysis at scale—AI, NLP and the
transformer revolution. http://soda-wps.s3.amazonaws.com/RePEc/ajr/sodwps/2021-12.pdf
Periñán-Pascual, Carlos (2025). The use of generative artificial intelligence for interpreting emotions in corpus-
based critical discourse analysis. https://link.springer.com/article/10.1007/s41701-025-00203-7
Picca, Davide (2024). “Emotional hermeneutics: Exploring the limits of artificial intelligence from a
Diltheyan perspective”. Proceedings of the 35th ACM Conference on Hypertext and Social Media
(pp. 12-16). Nueva York: ACM. https://doi.org/10.1145/3648188.3680255
Picca, Davide (2025). Not minds, but signs: Reframing LLMs through semiotics. arXiv. https://doi.
org/10.48550/arXiv.2505.17080
Quintiliano, Marco Fabio (2004). Instituciones oratorias. (I. Rodríguez y P. Sandlier, trads.). Alicante:
Biblioteca Virtual de Cervantes.
Raffini, Dario, Macori, Alessandro, Porcaro, Luca, Catarci, Tiziana, y Angelini, Marco (2025). How persuasive
could LLMs be? A first study combining linguistic-rhetorical analysis and user experiments. arXiv.
Ren, Yifan, Jin, Renren, Zhang, Tianhang, et al. (2024). Do large language models mirror cognitive language
processing? arXiv preprint arXiv:2402.18023.
Rönnqvist, Samuel, Schenk, Niko, y Chiarcos, Christian (2017). A recurrent neural model with attention
for the recognition of Chinese implicit discourse relations. https://doi.org/10.18653/v1/P17-2040
Sal Paz, Julio César (2013). “Comentario digital: género medular de las prácticas discursivas de la
cibercultura”. Caracteres Estudios culturales y críticos de la esfera digital, 2(2), 152-171.
— (2014). “Comunidades, géneros y estrategias: conceptos operativos para caracterizar la interacción
en los periódicos digitales”. En A. Parini y M. Giammatteo (Eds.), Lenguaje, discurso e interacción
en los espacios virtuales (pp. 167-186). Mendoza: Universidad Nacional de Cuyo.
— (2016a). “El comentario digital como género discursivo periodístico. Análisis de la Gaceta de
Tucumán”. Aposta Revista de Ciencias Sociales, 69, 158-216.
— (2016b). “La práctica discursiva del comentario digital y la configuración de representaciones
sociales en los espacios de interacción de los cibermedios”. En El lenguaje en la comunicación
digital (pp. 16-55). Buenos Aires: Universidad de Belgrano.
— (2017). “Estereotipos sobre el consumo de drogas en comentarios de noticias sobre cannabis
medicinal”. Discurso y Sociedad, 11, 289-322.
— (2025). “El prompt como género discursivo digital: anatomía, dimensiones y tensiones en la era
algorítmica”. Estudos Linguísticos e Literários, 80, 271-319.
Sal Paz, Julio César, y Maldonado, Silvana Dolores (2013). “Delimitación y alcances de la voz ‘comunidad’
en el marco de los estudios del discurso”. Forma y Función, 26(1), 111-140.
— (2016a). “Hacia una Didáctica del Análisis del Discurso en el Nivel Superior. Conceptos Clave”.
En N. Ibarra, J. Ballester y F. Romero (Eds.), Investigación en enseñanza de las lenguas y las
literaturas. Estudios de Lingüística Aplicada (vol. 1, pp. 209-221). Valencia: Universitat Politècnica
de València.
— (2016b). “Êthos, pathos y lógos: resignificaciones en el marco de los estudios del discurso”. Revista
del Instituto de Investigaciones Lingüísticas y Literarias Hispanoamericana, 20(1-2), 143-159.
Scolari, Carlos Alberto (2024). Sociosemiótica e inteligencia artificial. Barcelona: Prensa Universitat
Pompeu Fabra.
Shanahan, Murray (2023). Talking about large language models. arXiv:2212.03551. https://arxiv.org/
abs/2212.03551
Stader, David (2024). “Algorithms don’t have a future: On the relation of judgement and calculation”.
Philosophy & Technology, 37(21), 1-19.
Swanepoel, Danie (2021). “Does artificial intelligence have agency?” En R. W. Clowes, K. Gärtner,
e I. Hipólito (Eds.), The mind-technology problem: Investigating minds, selves and 21st century
artefacts (pp. 83-104). Cham: Springer. https://doi.org/10.1007/978-3-030-43350-6_5
Tabassam, Sadaf, y Wang, Ziyuan (2025). Multimodal Prompt Engineering: Shaping the Future of Intelligent
Systems.
Valle, Andrea (2025). From grammar to text: A semiotic perspective on computation. Berlin y Boston: De
Gruyter.
Vallor, Shannon (2024). The AI mirror: How to reclaim our humanity in the age of machine thinking.
Oxford: Oxford University Press.
Van Dijk, Teun Adrianus (2016). Discurso y conocimiento: Una aproximación sociocognitiva. Barcelona:
Gedisa.
Vromen, Emma (2024). Large language models as semiotic machines: Language modeling vs cognitive
modeling. arXiv preprint arXiv:2410.13065. https://arxiv.org/abs/2410.13065
Wan, Shaoyong, Liu, Wenjuan, y Strube, Michael (2025). On the role of context for discourse relation
classification in scientific writing. arXiv. https://arxiv.org/abs/2510.26354v1
Webb, Taylor, Holyoak, Keith James, y Lu, Hongjing (2022). Emergent analogical reasoning in large
language models. arXiv preprint arXiv:2212.09196.
Wei, Jason, Tay, Yi, Bommasani, Rishi, et al. (2022). “Emergent abilities of large language
models”. Transactions on Machine Learning Research, 3, 1-32.
Published
Issue
Section
License
Copyright (c) 2026 Dr. JULIO CÉSAR SAL PAZ (Autor/a)

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Aquellos/as autores/as que tengan publicaciones en esta revista aceptan los términos siguientes:
Los/as autores/as conservarán sus derechos de autor y garantizarán a la revista el derecho de primera publicación de su obra, el cual estará simultáneamente sujeto a la Licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional (CC BY-NC-SA 4.0), que permite a terceros utilizar lo publicado, siempre que se otorgue el adecuado reconocimiento; se mencione la autoría del trabajo y la primera publicación en Tríade; no se haga uso del material con propósitos comerciales; y, en caso de crear otro trabajo a partir de material original (por ejemplo, una traducción), debe distribuir su contribución bajo esta misma licencia del original.
Los/as autores/as podrán adoptar otros acuerdos de licencia no exclusiva de distribución de la versión de la obra publicada (por ejemplo, depositarla en un archivo telemático institucional o publicarla en un volumen monográfico), indicando los datos de su publicación inicial en esta revista.
Se permite y recomienda a los/as autores/as difundir su obra a través de Internet (por ejemplo, en archivos telemáticos institucionales o en su página web) después del proceso de publicación, lo cual puede producir intercambios interesantes y aumentar las citas de la obra publicada. (Véase El efecto del acceso abierto).
How to Cite
Similar Articles
- Elizabeth Mercedes Rigatuso, Interactive markers, agreement expressions and management of links in commercial service encounters in Buenos Aires Spanish: exchanges by Whatsapp , TRÍADE : No. 1 (2025): Tríade
- Marta Albeda Marco, Pragmatic mitigation: problems and proposals for analysis , TRÍADE : No. 1 (2025): Tríade
- Matthew Bush, The anguish of the literary act: The existential crisis and its derivations , TRÍADE : No. 1 (2025): Tríade
You may also start an advanced similarity search for this article.