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The Use of Artificial Intelligence in Cultural Heritage Studies—Threats and...
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The Use of Artificial Intelligence in Cultural Heritage Studies—Threats and Opportunities

A special issue of Heritage (ISSN 2571-9408). This special issue belongs to the section "Cultural Heritage".

Deadline for manuscript submissions: 31 December 2024 | Viewed by 8825

Special Issue Editors

Dr. Dirk Spennemann

E-Mail Website
Guest Editor
Institute for Land Water and Society, Charles Sturt University, P.O. Box 789, Albury, NSW 2640, Australia
Interests: micronesian history and heritage; heritage conservation; heritage management
Special Issues, Collections and Topics in MDPI journals
Dr. Peter J. Cobb

E-Mail Website
Guest Editor
School of Humanities, University of Hong Kong, Hong Kong, China
Interests: Mediterranean classical and near Eastern Archaeology; late Bronze and Iron Ages of the Eastern Mediterranean

Special Issue Information

Dear Colleagues,

Artificial Intelligence (AI) is poised to become the greatest cross-sectorial disruptor since the development of the internet in the mid-1990s. Developments are occurring on a wide front, from models developed and trained to automatically classify text from fragments and provide solutions for interpretation to models that can classify coins or pottery fragments and aid in the reconstruction of pottery vessels from fragments. In combination with CT scans, AI models have been used to extract text from carbonised scrolls that were too fragile to be unrolled. Generative AI language models such as ChatGPT have become a common tool to summarise text and provide ready answers to questions that can be asked in a person’s normal language pattern.

This Special Issue aims to bring together a range of contributions:

  • Papers that report on or evaluate current uses of Artificial Intelligence in cultural heritage studies;
  • Proof-of-concept papers that report on pilot studies which explore innovative uses of AI;
  • Conceptual papers that explore potential emerging uses and applications;
  • Papers that address social concerns related to the use and potential abuse of generative AI systems in heritage studies.

Welcome are all contributions that address a wide range of aspects of the actual or potential use of Artificial Intelligence in the field of cultural heritage studies, such as

The use of neural networks and AI in the classification and interpretation of

  • Artefacts, objects and other material culture;
  • Building components;
  • Damaged buildings;
  • Archaeological sites (for ex interfacing with remote sensing);
  • Handwriting analysis for archival studies.

The use of neural networks and AI in the restoration and reconstruction of

  • Artefacts and objects;
  • Paintings and mosaics;
  • Incomplete texts and inscriptions;
  • Buildings ruins;
  • Heritage structures damaged by natural disasters (e.g., fire).

The use of generative AI chatbots in

  • Museum studies;
  • Public archaeology;
  • Heritage education;
  • Professional development.

The potential dangers of AI

  • Deskilling of professionals (loss of critical thinking skills);
  • Deep fakes of images and audio recordings;
  • Falsification of manuscripts;
  • Falsified artefacts;
  • Creation of false narratives and alternative histories.

Dr. Dirk Spennemann
Dr. Peter J. Cobb
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Heritage is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Artificial Intelligence
  • cultural heritage
  • neural networks

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Published Papers (3 papers)

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27 pages, 443456 KiB  
Article
ImageOP: The Image Dataset with Religious Buildings in the World Heritage Town of Ouro Preto for Deep Learning Classification
by André Luiz Carvalho Ottoni and Lara Toledo Cordeiro Ottoni
Heritage 2024, 7(11), 6499-6525; https://doi.org/10.3390/heritage7110302 - 20 Nov 2024
Viewed by 588
Abstract
Artificial intelligence has significant applications in computer vision studies for cultural heritage. In this research field, visual inspection of historical buildings and the digitization of heritage using machine learning models stand out. However, the literature still lacks datasets for the classification and identification [...] Read more.
Artificial intelligence has significant applications in computer vision studies for cultural heritage. In this research field, visual inspection of historical buildings and the digitization of heritage using machine learning models stand out. However, the literature still lacks datasets for the classification and identification of Brazilian religious buildings using deep learning, particularly with images from the historic town of Ouro Preto. It is noteworthy that Ouro Preto was the first Brazilian World Heritage Site recognized by UNESCO in 1980. In this context, this paper aims to address this gap by proposing a new image dataset, termed ImageOP: The Image Dataset with Religious Buildings in the World Heritage Town of Ouro Preto for Deep Learning Classification. This new dataset comprises 1613 images of facades from 32 religious monuments in the historic town of Ouro Preto, categorized into five classes: fronton (pediment), door, window, tower, and church. The experiments to validate the ImageOP dataset were conducted in two stages: simulations and computer vision using smartphones. Furthermore, two deep learning structures (MobileNet V2 and EfficientNet B0) were evaluated using Edge Impulse software. MobileNet V2 and EfficientNet B0 are architectures of convolutional neural networks designed for computer vision applications aiming at low computational cost, real-time classification on mobile devices. The results indicated that the models utilizing EfficientNet achieved the best outcomes in the simulations, with accuracy = 94.5%, precision = 96.0%, recall = 96.0%, and F-score = 96.0%. Additionally, superior accuracy values were obtained in detecting the five classes: fronton (96.4%), church (97.1%), window (89.2%), door (94.7%), and tower (95.4%). The results from the experiments with computer vision and smartphones reinforced the effectiveness of the proposed dataset, showing an average accuracy of 88.0% in detecting building elements across nine religious monuments tested for real-time mobile device application. The dataset is available in the Mendeley Data repository. Full article
(This article belongs to the Special Issue The Use of Artificial Intelligence in Cultural Heritage Studies—Threats and Opportunities)
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19 pages, 311 KiB  
Article
Will Artificial Intelligence Affect How Cultural Heritage Will Be Managed in the Future? Responses Generated by Four genAI Models
by Dirk H. R. Spennemann
Heritage 2024, 7(3), 1453-1471; https://doi.org/10.3390/heritage7030070 - 11 Mar 2024
Cited by 5 | Viewed by 4741
Abstract
Generative artificial intelligence (genAI) language models have become firmly embedded in public consciousness. Their abilities to extract and summarise information from a wide range of sources in their training data have attracted the attention of many scholars. This paper examines how four genAI [...] Read more.
Generative artificial intelligence (genAI) language models have become firmly embedded in public consciousness. Their abilities to extract and summarise information from a wide range of sources in their training data have attracted the attention of many scholars. This paper examines how four genAI large language models (ChatGPT, GPT4, DeepAI, and Google Bard) responded to prompts, asking (i) whether artificial intelligence would affect how cultural heritage will be managed in the future (with examples requested) and (ii) what dangers might emerge when relying heavily on genAI to guide cultural heritage professionals in their actions. The genAI systems provided a range of examples, commonly drawing on and extending the status quo. Without a doubt, AI tools will revolutionise the execution of repetitive and mundane tasks, such as the classification of some classes of artifacts, or allow for the predictive modelling of the decay of objects. Important examples were used to assess the purported power of genAI tools to extract, aggregate, and synthesize large volumes of data from multiple sources, as well as their ability to recognise patterns and connections that people may miss. An inherent risk in the ‘results’ presented by genAI systems is that the presented connections are ‘artifacts’ of the system rather than being genuine. Since present genAI tools are unable to purposively generate creative or innovative thoughts, it is left to the reader to determine whether any text that is provided by genAI that is out of the ordinary is meaningful or nonsensical. Additional risks identified by the genAI systems were that some cultural heritage professionals might use AI systems without the required level of AI literacy and that overreliance on genAI systems might lead to a deskilling of general heritage practitioners. Full article
(This article belongs to the Special Issue The Use of Artificial Intelligence in Cultural Heritage Studies—Threats and Opportunities)

Other

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22 pages, 520 KiB  
Systematic Review
Artificial Intelligence at the Interface between Cultural Heritage and Photography: A Systematic Literature Review
by Carmen Silva and Lídia Oliveira
Heritage 2024, 7(7), 3799-3820; https://doi.org/10.3390/heritage7070180 - 17 Jul 2024
Cited by 1 | Viewed by 2190
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue The Use of Artificial Intelligence in Cultural Heritage Studies—Threats and Opportunities)
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