Publications

Permanent URI for this collectionhttps://repositorio.grial.eu/handle/123456789/34

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Start date: 2023Subject: search.filters.subject.Artificial Intelligence

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    Safe AI in Education Manifesto. Version 0.4.0
    (2024-10-08) Alier-Forment, Marc; García-Peñalvo, Francisco José; Casañ, María José; Pereira, Juanan; Llorens-Largo, Faraón
    The Safe AI in Education Manifesto outlines ethical principles for integrating AI into educational environments. It emphasizes the need for human oversight, ensuring AI complements rather than replaces educators. Decision-making must remain transparent and appealable, protecting the educational process's integrity. Confidentiality is paramount; institutions must safeguard student data and ensure AI systems comply with stringent privacy standards. AI tools should align with educational strategies, supporting learning objectives without enabling unethical practices or adding complexity. The manifesto calls for AI systems to respect didactic practices, adapting seamlessly to instructional designs without burdening educators or students. It stresses accuracy and explainability, requiring AI outputs to be reliable, transparent, and verifiable. Interfaces must be intuitive, communicating their limitations to foster trust and critical engagement. Ethical training and transparency in AI model development are essential, including minimizing biases and disclosing data sources. The manifesto commits to advancing AI’s potential in education while prioritizing privacy, fairness, and educational integrity, providing a living framework adaptable to technological evolution. It can be signed at: https://manifesto.safeaieducation.org/
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    Generative Artificial Intelligence in Education: From Deceptive to Disruptive
    (Universidad Internacional de la Rioja, 2024-03-12) Alier, M.; García-Peñalvo, F. J.; Camba, J. D.
    Generative Artificial Intelligence (GenAI) has emerged as a promising technology that can create original content, such as text, images, and sound. The use of GenAI in educational settings is becoming increasingly popular and offers a range of opportunities and challenges. This special issue explores the management and integration of GenAI in educational settings, including the ethical considerations, best practices, and opportunities. The potential of GenAI in education is vast. By using algorithms and data, GenAI can create original content that can be used to augment traditional teaching methods, creating a more interactive and personalized learning experience. In addition, GenAI can be utilized as an assessment tool and for providing feedback to students using generated content. For instance, it can be used to create custom quizzes, generate essay prompts, or even grade essays. The use of GenAI as an assessment tool can reduce the workload of teachers and help students receive prompt feedback on their work. Incorporating GenAI in educational settings also poses challenges related to academic integrity. With availability of GenAI models, students can use them to study or complete their homework assignments, which can raise concerns about the authenticity and authorship of the delivered work. Therefore, it is important to ensure that academic standards are maintained, and the originality of the student's work is preserved. This issue highlights the need for implementing ethical practices in the use of GenAI models and ensuring that the technology is used to support and not replace the student's learning experience.
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    Evaluating the Effectiveness of Human-Centered AI Systems in Education
    (Departamento de Informática y Automática. Universidad de Salamanca, 2024-03-01) Shoeibi, N.; Therón, R.; García-Peñalvo, F. J.
    This thesis examines how AI can improve human-computer interaction (HCI) and user experience in education. A systematic litera-ture review (SLR) and LATILL case study show how AI can be used in education. The SLR examines existing literature to determine how AI af-fects user experience and HCI in education, highlighting personalization and adaptability of learning experiences, improved task performance, and improved user experience for teachers and students. AI implementation in education faces obstacles. Using CEFR levels and linguistic traits, the LATILL project uses a user-centered design to give students personali-zed guidance and support. It transforms language instruction and fosters engaging and successful learning by encouraging educator collaboration and resource sharing. This study emphasizes the importance of user ex-perience and HCI principles in designing AI-driven educational systems. AI and user-centered design can improve learning, student engagement, and educational outcomes.
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    KoopaML: Application for receiving and processing DICOM images
    (CEUR-WS.org, 2023-12-05) Fraile-Sanchón, R.; Vázquez-Ingelmo, A.; García-Holgado, A.; García-Peñalvo, F. J.
    AI algorithms application to medical data has gained relevance due to their powerful benefits among different research tasks. However, medical data is heterogeneous and diverse, and these algorithms need technological support to tackle these data management challenges. KoopaML enables users to unify medical data, especially DICOM images and apply AI algorithms to them in a straightforward way through an online web application. This work presents a new feature in the KoopaML platform: a Machine Learning platform to assist non-expert users in defining and applying ML pipelines. The feature comprises the reception, storage, and management of DICOM images. These images are received through a connection with a PACS (Picture Archiving Communication System) system already configured by users on the platform and, after storing the images, it is possible to apply AI algorithms to them and make modifications or annotations.
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    What Do We Mean by GenAI? A Systematic Mapping of The Evolution, Trends, and Techniques Involved in Generative AI
    (2023-08-01) García-Peñalvo, F. J.; Vázquez-Ingelmo, A.
    Artificial Intelligence has become a focal point of interest across various sectors due to its ability to generate creative and realistic outputs. A specific subset, generative artificial intelligence, has seen significant growth, particularly in late 2022. Tools like ChatGPT, Dall-E, or Midjourney have democratized access to Large Language Models, enabling the creation of human-like content. However, the concept 'Generative Artificial Intelligence' lacks a universally accepted definition, leading to potential misunderstandings. While a model that produces any output can be technically seen as generative, the Artificial Intelligent research community often reserves the term for complex models that generate high-quality, human-like material. This paper presents a literature mapping of AI-driven content generation, analyzing 631 solutions published over the last five years to better understand and characterize the Generative Artificial Intelligence landscape. Our findings suggest a dichotomy in the understanding and application of the term "Generative AI". While the broader public often interprets "Generative AI" as AI-driven creation of tangible content, the AI research community mainly discusses generative implementations with an emphasis on the models in use, without explicitly categorizing their work under the term "Generative AI".
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    The perception of Artificial Intelligence in educational contexts after the launch of ChatGPT: Disruption or Panic?
    (Ediciones Universidad de Salamanca, 2023-02-06) García-Peñalvo, F. J.
    The year 2022 has ended with one of those technological innovations that have a hard-to-predict behaviour, a black swan, hogging the limelight in traditional media and digital media. Indeed, it is ChatGPT. Although artificial intelligence had already been in the news and often masked under various other meanings, the ChatGPT phenomenon has once again brought this discipline and its positive and negative effects on our society to the forefront. Reactions to its launch, influenced mainly by its ease of access and use, have been varied, ranging from the enthusiasm of innovators and early adopters to the almost apocalyptic terror of the Terminator movie. Of the multiple applications of this tool, the most significant debate focuses on its implications in Education and Academia due to its tremendous power to generate texts that could very well pass for human creations. We are at the dawn of a technology that has gone from being a toy tool to bidding to become a disruptive innovation. Whether it succeeds or not will depend on many factors, but if it does not, it will be another one like it. Denying it or banning it will do absolutely nothing to stop the tsunami effect that has already begun. For all these reasons, we must first understand these technologies based on large language models and know their benefits and weaknesses, as well as what they really mean for a specific sector of activity, such as Education. After getting to know the technology and the tool, one would be in a position to use (or not) its potential and to prevent or detect its possible pernicious effects, presumably by changing and adapting processes that are probably profoundly rooted and that, therefore, forced to leave the comfort zone, which is always the cause of resistance to change and extreme reactions. These responses usually will not stop technology from reaching its productivity plateau when it becomes part of the daily life of a sufficient majority of users. This is always the cause of resistance to change and extreme reactions that will not usually stop technology from reaching its productivity plateau when it becomes part of the daily lives of a sufficient majority of users, especially when it is also a question of transversal tools that will spread their usage patterns among the different application domains.