Conferencia
Permanent URI for this collectionhttps://hdl.handle.net/11285/636053
Presentación o disertación realizada dentro de un congreso o evento similar, o como evento académico independiente, tales como: Conferencia inaugural, conferencia magistral, conferencia de clausura.
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- User experience in digital ecosystems with integration of Artificial Intelligence: a systematic literature mapping from 2010 to 2024(Springer Link, 2024-10-23) Valenzuela-Arvizu, S. Y., Ramírez-Montoya, M. S., & García-Peñalvo, F.J.; https://ror.org/03ayjn504Analyzing users’ experience in digital ecosystems (DE) is essential to ensure effective spaces capable of satisfying their needs and interests. The present study analyzed the publications in the Scopus and Web of Science (WoS) databases from 2010 to 2024 on the study topic of “user experience (UX) in DEs that integrate artificial intelligence (AI).” One hundred eighty-two published articles were reviewed using the Systematic Mapping methodology. Inclusion, exclusion, and quality criteria were applied to obtain the most relevant information. The results showed a) the preponderance of empirical research articles over theoretical/conceptual; b) the mixed methodology approach and the concurrent triangulation design were the most used; c) the main areas of interest were Health, Education, and Technology, which reflects in d) the contexts of the most cited articles and e) the areas of specialization of the main journals analyzed; f) the United States tops the list of the leading countries in this research topic, followed by China and Australia; and e) the studies emphasized assessing the usability and satisfaction with chatbots, the most prevalent and studied AI tool. This review provides a framework for identifying the state of the art of the research topic, making it possible to identify current and emerging research trends.
- Regulatory challenges and optimization strategies for open large language models: a multidimensional framework for efficient management(Springer Link, 2024-10-23) García López, Iván Miguel; Ramírez Montoya, María Soledad; Molina Espinosa, José Martín; https://ror.org/03ayjn504Innovations in artificial intelligence are rapidly transforming various in-dustries, particularly through the development and deployment of Open Large Language Models (OLLMs). However, the absence of a robust regula-tory framework presents significant challenges in ensuring the ethical, safe, and effective use of these models. This research aims to address this gap by proposing a comprehensive regulatory framework designed to optimize the scalability and performance of OLLMs, emphasizing the importance of structured pruning techniques. By integrating both quantitative and qualita-tive analyses, the study will assess the technical capabilities and societal implications of OLLMs, ultimately providing clear guidelines that promote responsible and sustainable innovation. The expected outcomes include the development of a governance model that balances the need for innovation with ethical considerations, offering a pathway for the regulation of OLLMs that supports their continued evolution while safeguarding public interests.
