Artificial intelligence and other technologies as allies in the enjoyment of art and museums

Authors

DOI:

https://doi.org/10.31637/epsir-2024-438

Keywords:

AI, museums, archives, cultural heritage, spreading, robotics, citizen, Ethics

Abstract

Introduction: Cultural heritage, defined as the set of tangible and intangible assets that constitute the legacy of a community, is invaluable to society. This legacy includes both tangible and intangible assets and forms the basis of cultural identity and social and economic development. Artificial intelligence (AI) and other technologies emerge as powerful tools for the management of cultural heritage, offering extensive possibilities for its preservation, promotion, dissemination, and accessibility. Methodolog: This research is based on the review and critical analysis of scientific and grey literature on the use of AI in museums and museological projects. Despite the still limited scientific contributions in this field, various applications and projects incorporating new technologies and AI in the management of cultural heritage were explored. Results: The literature review revealed several promising opportunities for AI in cultural heritage. A key use is AI's ability to analyze large amounts of data, which can uncover patterns and relationships not evident at first glance. Another significant use is the identification and classification of objects, where machine learning algorithms can be trained to recognize different types of objects with specific characteristics. Additionally, AI can be combined with other technologies to innovate the museum experience, providing interactive and personalized experiences for visitors. Discussion: Although the implementation of AI in cultural heritage management is in its early stages, its potential is considerable. AI's ability to handle large volumes of data and perform identification and classification tasks can significantly transform the management and exhibition of cultural heritage. Combining AI with other technologies offers new forms of interaction and enjoyment of heritage by citizens. Conclusions: AI has great potential in the management and enjoyment of cultural heritage. Although current contributions are limited, the opportunities for its use in the management, promotion, and exhibition of art and cultural heritage are promising. It is crucial to continue researching and developing AI applications to maximize its benefits and contribute to the development and preservation of cultural heritage.

Downloads

Download data is not yet available.

Author Biography

Pilar Irala, Universidad San Jorge

Ph.D. in Art History and Ph.D. in Communication. Associate Professor at San Jorge University. Curator and photographer. She has directed the Jalón Ángel Archive since 2011. Her research focuses on the relationships between photography, visual rhetoric and narrative, historical-photographic heritage, and Jalón Ángel. She conceptualized the theoretical framework of the Barthes syndrome in "El Síndrome de Barthes. La construcción retórica de la imagen fotográfica" (Fragua, 2019). Her latest book is “Jalón Ángel (1898-1976), más allá del fotógrafo,” Tirant Lo Blanch (2022). Some of her curations include "Iron Kids" by Diego Ibarra (Córdoba Biennial, 2019); "Cazadores de Imágenes" (2021, 2022, and 2023); and "Los desastres de las Guerras" (Ibercaja Foundation, 2023).

References

Canella, C. (2022). Museos interactivos, exposiciones y tecnología. intuiface. https://acortar.link/aXrd4I

Comisión Europea (2021). CORDIS Results pack on digital cultural heritage, Oficina de Publicaciones de la Unión Europea. https://acortar.link/WTKvH0

Comisión Europea (2023). Development of a Decision Support System for Improved Resilience & Sustainable Reconstruction of historic areas to cope with Climate Change & Extreme Events based on Novel Sensors and Modelling Tools. Cordis https://cordis.europa.eu/project/id/821054

Descubre Fundación (2022, noviembre). Diseñan un sistema ‘inteligente’ para la reconstrucción de restos arqueológicos. https://acortar.link/wywRLY

Eve (2023, enero). Inteligencia artificial y el futuro de los museos. https://acortar.link/frrnLv

Eve (2022, abril). Creación de apps móviles para museos. https://acortar.link/KDZLjb

Gobierno de España (2023). Plan de Recuperación, Transformación y Resiliencia. https://acortar.link/S4EMkJ

González, Diana M. (2022). Modelos de gestión de museos con Inteligencia Artificial en I Congreso Internacional de Museos y Estrategias Digitales CIMED [Conferencia]. UPV. https://acortar.link/Rtu6Y7 DOI: https://doi.org/10.4995/CIMED21.2021.12401

Hyperion Project (2024). https://www.hyperion-project.eu/

Ley 3/1999, de 10 de marzo, del Patrimonio Cultural Aragonés.

Louvre Museum (2019, octubre). "Mona Lisa Beyond the Glass": the Louvre's first Virtual Reality experience. En Louvre. https://acortar.link/8pJY21

Museo Nacional del Prado (2023, junio). El BSC y el Museo del Prado enseñan a la IA a mirar e interpretar las obras de arte. https://acortar.link/rNQSm2

Parlamento Europeo (2020). ¿Qué es la inteligencia artificial y cómo se usa? Noticias del Parlamento Europeo. https://acortar.link/h55eu

Patrimonio Global (2023, julio). Inteligencia artificial (IA) y Patrimonio Cultural. Patrimonio Global. https://acortar.link/eP8LGb

Smithsonian Museum (2018). Smithsonian Launches Pilot Program of “Pepper” Robots. https://acortar.link/x79LA8

Vallejo, N. (2015, julio). 15 ejemplos de tecnología en Museos. ojulearning. https://acortar.link/G4xygP

UFV (2022, noviembre). Investigadores de la UFV desarrollan una herramienta de Inteligencia Artificial que reconstruye monumentos y piezas artísticas en tiempo real, ARQGAN. https://acortar.link/hdSZGX

UNESCO (2022). Recomendación sobre la ética de la inteligencia artificial. https://acortar.link/NEU6e5

Published

2024-07-30

How to Cite

Irala, P. (2024). Artificial intelligence and other technologies as allies in the enjoyment of art and museums. European Public & Social Innovation Review, 9, 1–13. https://doi.org/10.31637/epsir-2024-438

Issue

Section

INNOVATING IN ARTISTIC FORMULATIONS