Artificial intelligence has inspired a significant number of studies on the interface between cultural heritage and photography. The aims of these studies are, among others, to streamline damage monitoring or diagnoses for heritage preservation, enhance the production of high-fidelity 3D models of cultural assets, or improve the analysis of heritage images using computer vision. This article presents the results of a systematic literature review to highlight the recent state of these studies, published in the last five years and available in the Scopus, Web of Science, and JSTOR databases. The aim is to identify the potential and challenges of artificial intelligence through the connection between cultural heritage and photography, the latter of which represents a relevant methodological aspect in these investigations. In addition to the advances exemplified, the vast majority of studies indicate that there are also many obstacles to overcome. In particular, there is a need to improve artificial intelligence methods that still have significant flaws. These include inaccuracy in the automatic classification of images and limitations in the applications of the results. This article also aims to reflect on the meaning of these innovations when considering the direction of the relationship between cultural heritage and photography.

In the area of human-computer interaction, over the last decade, there has been a growing interest on emotional factors, valuing above all the user experience. Emotions play a crucial role - in terms of both performance and influence - in areas such as attention, motivation, memory, decision-making and behavior. Therefore, not only emotion influences the interaction with websites but they also trigger emotional responses, and these responses can determine which website users choose. Therefore, were analyzed the emotional responses triggered in the interaction with Duolingo's interface (a learning languages website) taking into account the different components of emotional design, using data gathering instruments such as eye tracking and self-reporting methods. In this way, the present work intended to contribute to the design of interfaces that appeal in a greater extent to the users' emotions, in order to improve their user experience while increasing their level of engagement. Over the years, the focus of research in the field of human-computer interaction has been usability, which traditionally emphasizes the ease of use and functionality based on observed cognitive activity. Only recently, and prompted by Norman (2004), the role of aesthetic and affective aspects of interface design (Dillon, 2002; Norman, 2004) become more prominent leading to a growing interest on emotional factors. Works such as Jordan (2000), Desmet (2002) and Norman (2004) advocate a greater focus on pleasure and emotion in the user experience design of a product. “Emotions play an important role in how the user perceived the product (…) to achieve a meaningful relationship to a product.” (Fossdal & Berg, 2016, p. 95) Furthermore, emotions dominate decision-making process (Baumeister, Dewall, & Zhang, 2007; Polignano, 2015), direct attention and enhance particular memories over others (Reeves & Nass, 1998), being thus closely linked to attitudes, motivations and users' decisions (Koshkaki & Solhi, 2016). Consequently emotions influence all aspects of our interactions with cara membuat website (Forlizzi & Battarbee, 2004) (Emanuel, Rodrigues, & Martins, 2015; Yin, Zhang, & Li, 2014). Moreover, these trigger complex social and emotional responses identical to that emotional responses experienced when interacting with people (Desmet, 2002). In particular, the positive emotions can increase users' motivation and fixation (Isen, 1993). Emotions can be thereby considered in the field of human-computer interaction, as important factors to take into account for the construction of affective, satisfactory and efficient interfaces (Eskimez, Sturge-Apple, Duan, & Heinzelman, 2016).

Objetivo: Presentar el monográfico que aborda los nuevos escenarios de la sociedad digital ante el reto de la Inteligencia Artificial Generativa (IA), destacando sus implicaciones tecnológicas, éticas, epistemológicas y sociales. El artículo busca presentar los estudios seleccionados, enfatizando sus contribuciones a sectores como la educación, los medios de comunicación y la bibliotecología, y proponiendo pautas para la integración responsable de estas herramientas. Método: La investigación adopta un enfoque interdisciplinario, combinando métodos cualitativos y cuantitativos, basados en el análisis de estudios empíricos y teóricos desarrollados por investigadores de varios países, entre ellos Brasil, España, Italia y Portugal. El universo abarca aplicaciones de IA en contextos educativos, mediáticos e institucionales. Resultado: Los principales resultados destacan la democratización del acceso a la creación de contenidos a través de la IA generativa, la transformación de los paradigmas tradicionales de producción y evaluación del conocimiento, y los desafíos relacionados con el sesgo algorítmico, el impacto energético y las desigualdades sociales. También se destaca el potencial de la IA para personalizar los servicios educativos y bibliotecarios, al tiempo que se alerta sobre cuestiones éticas y epistemológicas. Conclusiones: El principal aporte de la monografía es ofrecer una visión estructurada sobre las implicaciones transversales de la IA generativa, sistematizando avances y desafíos. El texto propone marcos normativos y colaborativos que garanticen una implementación equitativa, sostenible y responsable de estas tecnologías. Se refuerza la importancia de un diálogo ético e interdisciplinario para alinear los avances tecnológicos con los valores sociales. PALABRAS CLAVE: Inteligencia Artificial. Ética. Educación. Sostenibilidad. Equidad.

This study aims to understand the interactions and communication processes taking place during Joint Media Engagement (JME) sessions involving older adults/grandparents and (grand)children in the collaborative use of tablets and tablets’ Apps. In this paper, the exploratory methodologies to be implemented during empirical studies are described, as well as the development of scripts for the pre and post JME session's interviews. It is also addressed the development and validation of indicators, scales and surveys to assess grandparents/older adults and (grand)children's digital literacy and the quality of intergenerational relationship. Moreover, the paper presents the results of the pre-pilot interviews and a JME session with a grandmother and granddaughter, in which they used a tablet App to build their family tree