Escudo Universidad de Pamplona

Repositorio Institucional

Universidad de Pamplona

Preservamos, organizamos y difundimos la producción académica, científica, investigativa y cultural de la Universidad de Pamplona, garantizando el acceso abierto al conocimiento generado por nuestra comunidad universitaria.

Explorar colecciones

Por favor, use este identificador para citar o enlazar este ítem: https://repositoriodspace.unipamplona.edu.co/jspui/handle/20.500.12744/10755
Registro completo de metadatos
Campo DC Valor Lengua/Idioma
dc.contributor.authorRojas Contreras, William Mauricio.-
dc.contributor.authorRojas Contreras, Olga Liliana.-
dc.contributor.authorMojica Acevedo, Eliana Caterine.-
dc.date.accessioned2026-08-12T15:03:46Z-
dc.date.available2025-12-12-
dc.date.available2026-08-12T15:03:46Z-
dc.date.issued2025-
dc.identifier.citationRojas Contreras, W.; Rojas Contreras, O.; Mojica Acevedo, E. (2025). Riesgos del uso de Inteligencia Artificial Generativa en comunicación e investigación científica. Sello Editorial Universidad de Pamplona. https://repositoriodspace.unipamplona.edu.co/jspui/handle/20.500.12744/10755es_CO
dc.identifier.isbn978-628-7656-87-1-
dc.identifier.urihttps://repositoriodspace.unipamplona.edu.co/jspui/handle/20.500.12744/10755-
dc.descriptionEl desarrollo y la integración de la inteligencia artificial (IA) han planteado importantes desafíos éticos, especialmente en el dominio de la desinformación. Este trabajo de investigación aborda los riesgos específicos asociados a la IA generativa en los procesos de comunicación científica, respondiendo a la pregunta: ¿Cuáles son los subdominios del dominio de desinformación que se generan en la comunicación e investigación científica por el uso de la inteligencia artificial? A través de una revisión sistemática de literatura, se identificaron los principales dominios de riesgos de la IA, tales como discriminación y toxicidad, privacidad y seguridad, desinformación, actores maliciosos, interacción humano-computadora, socioeconómicos y ambientales, y fallos de los sistemas de IA. El dominio de desinformación se desglosa en los subdominios de Información falsa o engañosa y Contaminación del ecosistema informativo y pérdida de la realidad consensuada. Los riesgos más frecuentes identificados en este dominio incluyen el sesgo de datos y la desinformación intencional. La investigación contribuye al campo de la ética de la IA, proponiendo recomendaciones para un uso ético y responsable de la IA en la ciencia. Futuros estudios deberán centrarse en el desarrollo de estrategias de mitigación de riesgos y en abordar las brechas identificadas en el dominio de la desinformación.es_CO
dc.description.abstractLos autores no proporcionan información sobre este ítem.es_CO
dc.format.extent123es_CO
dc.format.mimetypeapplication/pdfes_CO
dc.language.isoeses_CO
dc.publisherSello Editorial - Unipamplona - Facultad de Ingenierías & Arquitectura - Ciencias e Innovación.es_CO
dc.subjectAlucinación.es_CO
dc.subjectDesinformación.es_CO
dc.subjectÉtica de la IA.es_CO
dc.subjectInteligencia artificial.es_CO
dc.subjectSesgo de datos.es_CO
dc.subjectRiesgos.es_CO
dc.subjectComunicación e investigación.es_CO
dc.titleRiesgos del uso de Inteligencia Artificial Generativa en comunicación e investigación científicaes_CO
dc.typehttp://purl.org/coar/resource_type/c_2f33es_CO
dc.date.accepted2025-12-12-
dc.description.editionPrimera Edición.es_CO
dc.relation.referencesAbimbola, C., Eden, C.A., Chisom, O.N., & Adeniyi, I.S. (2024). Integrating Al in education: Opportunities, challenges, and ethical considerations. Magna Scientia Advanced Research and Reviews, 10(02), 006-013. https://doi.org/10.30574/msarr.2024.10.2.0039es_CO
dc.relation.referencesAl-Rashed, N. (2024). The Impact of Artificial Intelligence on the Future of Media. International Journal for Scientific Research., 108 https://doi.org/10.59992/ijsr.2024.v3n7p3es_CO
dc.relation.referencesBallester, V. G., & Vicente, C. T. (2024). El rol de la inteligencia artificial en la publicación científica: perspectivas desde la farmacia hospitalaria. Farmacia Hospitalaria, 48(5), 246-251. https://doi.org/10.1016/j.farma.2024.06.002es_CO
dc.relation.referencesCarobene, A., Padoan, A., Cabitza, F., Banfi, G., & Plebani, Mo. (2024).Rising adoption of artificial intelligence in scientific publishing: evaluating the role, risks, and ethical implications in paper drafting and review process. Clinical Chemistry and Laboratory Medicine, 62(5), pp. 835-843. https://doi.org/10.1515/cclm-2023-1136es_CO
dc.relation.referencesCui, T., Wang, Y., Fu, C., Xiao, Y., Li, S., Deng, X., Liu, Y., Zhang, Q., Qiu, Z., Li, P., Tan, Z., Xiong, J., Kong, X., Wen, Z., Xu, K. & Li, Q. (2024). Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems. ArXiv. http://arxiv.org/abs/2401.05778es_CO
dc.relation.referencesCritch, A., & Russell, S. (2023). TASRA: a Taxonomy and Analysis of Societal-Scale Risks from Al. ArXiv, 1. https://arxiv.org/abs/2306.06924es_CO
dc.relation.referencesCunha, P.R., & Estima, J. (2023). Navigating the Landscape of AI Ethics and Responsibility. In N. Moniz, Z. Vale, J. Cascalho, C. Silva, R. Sebastião (eds) Progress in Artificial Intelligence. EPΙΑ 2023. Lecture Notes in Computer Science (vol. 14115, pp. 92-105). Springer. https://doi.org/10.1007/978-3-031-49008-8_8es_CO
dc.relation.referencesDeng, J., Cheng, J., Sun, H., Zhang, Z. & Huang, M. (2023). Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements. ArXiv, 1. http://arxiv.org/abs/2302.09270es_CO
dc.relation.referencesDhawan, S., & Kumar, K. (2024). Ethical Implications of AI in Healthcare. International Journal of Scientific Research In Engineering And Management, 8(3), 1-12. https://doi. org/10.55041/IJSREM29006es_CO
dc.relation.referencesElectronic Privacy Information Centre. (2023). Generating Harms: Generative Al's Impact & Paths Forward. https://epic.org/documents/generating-harms-generative-ais-impact-paths-forward/es_CO
dc.relation.referencesFill, H., Härer, F., Vasic, I., Borcard, D., Reitemeyer, B., Muff, F., Curty, S., & Bühlmann, M. (28-31 de October de 2024). CMAG: A Framework for Conceptual Model Augmented Generative Artificial Intelligence. ER2024: Companion Proceedings of the 43rd International Conference on Conceptual Modeling: ER Forum, Pittsburgh, Pennsylvania, USA,es_CO
dc.relation.referencesGabriel, I., Manzini, A., Keeling, G., Hendricks, L. A., Rieser, V., Iqbal, H., Tomašev, N., Ktena, I., Kenton, Z., Rodriguez, M., El-Sayed, S., Brown, S., Akbulut, C., Trask, A., Hughes, E., Stevie Bergman, A., Shelby, R., Marchal, N., Griffin, C., "..." Manyika, J. (2024). The Ethics of Advanced Al Assistants. ArXiv, 1. https://doi.org/10.48550/arXiv.2404.16244es_CO
dc.relation.referencesGhani, M., Mustafa, W., Shakir, A., Bakhtiar, D., & Ramadan, G. (2023). Symbiotic Relationship Between Media Technology and Artificial Intelligence: A Synthesis Analysis. 3rd International Conference on Mobile Networks and Wireless Communications (ICMNWC). Tumkur, India. ICMNWC60182.2023.10435827 https://doi.org/10.1109/es_CO
dc.relation.referencesGolpayegani, D., Pandit, H.J., & Lewis, D. (2022). AIRO: An Ontology for Representing AI Risks Based on the Proposed EU AI Act and ISO Risk Management Standards. IOS Press, 55, 51-55. https://doi.org/10.3233/SSW220008es_CO
dc.relation.referencesHagendorff, T. (2024). Mapping the Ethics of Generative AI: A Comprehensive Scoping Review. ArXiv. http://arxiv.org/abs/2402.08323es_CO
dc.relation.referencesHendrycks, D. & Mazeika, M. (2022). X-Risk Analysis for Al Research. ArXiv. https://arxiv.org/abs/2206.05862es_CO
dc.relation.referencesHryciw, B. N., Seely, A. J. & Kyeremanteng, K. (2023). Guiding principles and proposed classification system for the responsible adoption of artificial intelligence in scientific writing in medicine. Frontiers in Artificial Intelligence, 6, 1-5. https://doi. org/10.3389/frai.2023.1283353es_CO
dc.relation.referencesHogenhout, L. (2021). A Framework for Ethical Al at the United Nations. ArXiv. http://arxiv.org/abs/2104.12547es_CO
dc.relation.referencesInfocomm Media Development Authority. (2023). Cataloguing LLM Evaluations. https://aiverifyfoundation.sg/downloads/Cataloguing_LLM_Evaluations.pdfes_CO
dc.relation.referencesJiao, J., Afroogh, S., Xu, Y. & Phillips, C. (2024). Navigating LLM Ethics: Advancements, Challenges, and Future Directions. ArXiv, 1. https://doi.org/10.48550/arXiv.2406.18841es_CO
dc.relation.referencesKhalifa, M. & Albadawy, M. (2024). Using artificial intelligence in academic writing and research: An essential productivity tool. Computer Methods and Programs in Biomedicine Update, 5, 100145. https://doi.org/10.1016/j.cmpbup.2024.100145es_CO
dc.relation.referencesLiu, Y., Yao, Y., Ton, J.-F., Zhang, X., Guo, R., Cheng, H., Klochkov, Y., Taufiq, M. F. & Li, H. (2023). Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment. ArXiv. http://arxiv.org/abs/2308.es_CO
dc.relation.referencesMa, Y., Liu, J., Yi, F., Cheng, Q., Huang, Y., Lu, W. & Liu, X. (2023). Al vs. Human Differentiation Analysis of Scientific Content Generation. ArXiv. https://doi.org/10.48550/arXiv.2301.10416es_CO
dc.relation.referencesManoj, K. & Sahil, J. (2025). Ethical issues in the development of artificial intelligence: recognizing the risks. International Journal of Ethics and Systems, 41(1), 45-63.https://doi.org/10.1108/IJOES-05-2023-0107es_CO
dc.relation.referencesNah, F. F. H., Zheng, R., Cai, J., Siau, K. & Chen, L. (2023). Generative AI and ChatGPT: Applications, challenges, and Al-human collaboration. Journal of Information Technology Case and Application Research, 25(3), 277-304. https://doi.org/10.1080 /15228053.2023.2233814es_CO
dc.relation.referencesNiveditha, K. P., Choubey, K., Soni, K., Mishra, P., & Naz, A. (2024). Exploring the Role of Artificial Intelligence in Modern Education. International Journal of Innovative Research in Computer and Communication Engineering, 12(5), 8147-8150. https://ijircce.com/admin/main/storage/app/pdf/PeLGRoEovWK8yJozTjh8clpsY2Y0Ae5P0FFOOKOS.pdfes_CO
dc.relation.referencesNovelli, C., Casolari, F., Rotolo, A., Taddeo, M., & Floridi, L. (2024). ΑΙ Risk Assessment: A Scenario-Based, Proportional Methodology for the AI Act. Digital Society, 3(13), 1-29. https://doi. org/10.1007/s44206-024-00095-1es_CO
dc.relation.referencesPeña-Fernández S., Peña-Alonso U., & Eizmendi-Iraola M. (2023). El discurso de los periodistas sobre el impacto de la inteligencia artificial generativa en la desinformación. Estudios sobre el Mensaje Periodístico, 29(4), 833-841. https://doi.org/10.5209/esmp.88673es_CO
dc.relation.referencesPenabad-Camacho, L., Penabad-Camacho, M. A., Mora-Campos, A., Cerdas-Vega, G., Morales-López, Y., Ulate-Segura, M., Méndez-Solano, A., Nova-Bustos, N., Vega-Solano, M. F. & Castro-Solano, Μ. Μ. (2024). Heredia Declaration: Principles on the use of Artificial Intelligence in scientific publishing. Revista Electrónica Educare, 28(S), 1-10. https://doi.org/10.15359/ree.28-S.19967es_CO
dc.relation.referencesRodrigues, F., Newell, R., Babu, G. R., Chatterjee, T., Sandhu, N. K., & Gupta, L. (2024). The social media Infodemic of health-related misinformation and technical solutions. Health Policy and Technology, 13(2), 100846. https://doi.org/10.1016/j. hlpt.2024.100846es_CO
dc.relation.referencesRogers, W.A., Draper, H., & Carter, S.M. (2021). Evaluation of artificial intelligence clinical applications: Detailed case analyses show value of healthcare ethics approach in identifying patient care issues. Bioethics, 35(7), 623-633. https://doi.org/10.1111/bioe.12885es_CO
dc.relation.referencesSamuel-Okon, A. D. (2024). Smart Media or Biased Media: The Impacts and Challenges of Al and Big Data on the Media Industry. Asian Journal of Research in Computer Science, 7(7), 128-144. https://doi.org/10.9734/ajrcos/2024/v17i7484es_CO
dc.relation.referencesShelby, R., Rismani, S., Henne, K., Moon, A., Rostamzadeh, N., Nicholas, P., Yilla-Akbari, N. 'mah, Gallegos, J., Smart, A., Garcia, E., & Virk, G. (2023). Sociotechnical harms of algorithmic systems: Scoping a taxonomy for harm reduction. AIES '23: Proceedings of the 2023 AAAI/ACM Conference on Al, Ethics, and Society (pp. 723-741). Association for Computing Machinery. https://doi. org/10.1145/3600211.3604673es_CO
dc.relation.referencesSlattery, P., Saeri, A., Grundy, E.A., Graham, J., Noetel, M., Uuk, R., Dao, J., Pour, S., Casper, S. & Thompson, N. (2024). The AI Risk Repository: A Comprehensive Meta-Review, Database, and Taxonomy of Risks From Artificial Intelligence. ArXiv, 1. https://doi.org/10.48550/arXiv.2408.12622es_CO
dc.relation.referencesStahl, B. C., Antoniou, J., Bhalla, N., Brooks, L., Jansen, P., Lindqvist, B., ... & Wright, D. (2023). A systematic review of artificial intelligence impact assessments. Artificial Intelligence Review, 56(11), 12799-12831. https://doi.org/10.1007/s10462-023-10420-8es_CO
dc.relation.referencesSun, H., Zhang, Z., Deng, J., Cheng, J., & Huang, M. (2023). Safety Assessment of Chinese Large Language Models. ArXiv, https://arxiv.org/abs/2304.10436es_CO
dc.relation.referencesUstinovich, E. (2024). Generative artificial intelligence in the electoral processes of 2024 in the world: disinformation campaigns and online trolls. Social"naja Politika I Social"noe Partnerstvo (Social Policy and Social Partnership, (3)gener. https://doi.org/10.33920/pol-01-2403-03es_CO
dc.relation.referencesVidgen, B., Agrawal, A., Ahmed, A. M., Akinwande, V., Al-Nuaimi, N., Alfaraj, N., Alhajjar, E., Aroyo, L., Bavalatti, T., Blili-Hamelin, B., Bollacker, K., Bomassani, R., Boston, M.F., Campos, S., Chakra, K., Chen, C., Coleman, C., Coudert, Z. D., Derczynski, L., "..." Vanschoren, J. (2024). Introducing v0.5 of the AI Safety Benchmark from MLCommons. ArXiv. http://arxiv.org/abs/2404.12241es_CO
dc.relation.referencesWeidinger, L., Rauh, M., Marchal, N., Manzini, A., Hendricks, L. A., Mateos-Garcia, J., Bergman, S., Kay, J., Griffin, C., Bariach, B., Gabriel, I., Rieser, V. & Isaac, W. (2023). Sociotechnical Safety Evaluation of Generative Al Systems. ArXiv. http://arxiv.org/abs/2310.11986es_CO
dc.relation.referencesWeidinger, L., Uesato, J., Rauh, M., Griffin, C., Huang, P.S., Mellor, J., Glaese, A., Cheng, M., Balle, B., Kasirzadeh, A., Biles, C., Brown, S., Kenton, Z., Hawkins, W., Stepleton, T., Birhane, A., Hendricks, L. A., Rimell, L., Isaac, W., Haas, J, Legassick, S., Irving, G. & Gabriel, I. (2022). Taxonomy of Risks posed by Language Models. FAccT '22: Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, 214-229. https://doi.org/10.1145/3531146.3533088es_CO
dc.relation.referencesWeidinger, L., Mellor, J., Rauh, M., Griffin, C., Uesato, J., Huang, P.-S., Cheng, M., Glaese, M., Balle, B., Kasirzadeh, A., Kenton, Z., Brown, S., Hawkins, W., Stepleton, T., Biles, C., Birhane, A., Haas, J., Rimell, L., Hendricks, L. A. & Gabriel, I. (2021). Ethical and social risks of harm from Language Models. ArXiv. http://arxiv. org/abs/2112.04359es_CO
dc.relation.referencesWilliamson, S. M., Prybutok, V. (2024). Balancing Privacy and Progress: A Review of Privacy Challenges, Systemic Oversight, and Patient Perceptions in Al-Driven Healthcare. Applied Sciences, 14(2), 675. https://doi.org/10.3390/app14020675es_CO
dc.relation.referencesZeng, Y., Klyman, K., Zhou, A., Yang, Y., Pan, M., Jia, R., Song, D., Liang, P., & Li, B. (2024). AI Risk Categorization Decoded (AIR 2024): From Government Regulations to Corporate Policies. ArXiv, https://arxiv.org/abs/2406.17864es_CO
dc.relation.referencesZhang, Z., Lei, L., Wu, L., Sun, R., Huang, Y., Long, C., Liu, X., Lei, X., Tang, J. & Huang, M. (2023). SafetyBench: Evaluating the safety of Large Language Models. ArXiv. https://doi.org/10.48550/arXiv.2309.07045es_CO
dc.rights.accessrightshttp://purl.org/coar/access_right/c_abf2es_CO
dc.type.coarversionhttp://purl.org/coar/version/c_970fb48d4fbd8a85es_CO
Aparece en las colecciones: Ciencia e innovación

Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
Rojas_Rojas_Mojica_2025_PI.pdf6,98 MBAdobe PDFVisualizar/Abrir


Los ítems de DSpace están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.