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Envisioning Archival Images with Artificial Intelligence

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Data publikacji: 25.11.2024

Archeion, 2024, 125, s. 33-54

https://doi.org/10.4467/26581264ARC.24.007.20202

Autorzy

Jessica Bushey
San José State University
, Stany Zjednoczone Ameryki
https://orcid.org/0000-0002-8569-5360 Orcid
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Wszystkie publikacje autora →

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Tytuły

Envisioning Archival Images with Artificial Intelligence

Abstrakt

The literature review explores the role of Artificial Intelligence (AI) in enhancing access to and management of photographic archives. As digital and analog photographs proliferate in archival institutions, traditional approaches to organizing and describing these materials are increasingly inadequate. The review highlights the potential of AI, particularly computer vision (CV), to address the challenges associated with processing large volumes of digital images. CV algorithms, such as object detection and image classification, can automate tasks like image metadata generation, offering archivists new tools for organizing collections more efficiently. However, the adoption of AI in archival practice raises important ethical concerns, particularly regarding biases inherent in AI training datasets and technologies like facial recognition. Through various case studies, the review demonstrates that interdisciplinary collaboration between archivists, AI specialists, and scholars is crucial to developing effective AIdriven solutions. Projects like CAMPI and the Finnish Wartime Photograph Archive illustrate the practical benefits of AI, while emphasizing the need for archivists to develop AI and visual literacy. This review serves as a foundational resource for archival scholars and practitioners interested in utilizing AI to improve access to photographic archives.

Referencje

Pobierz bibliografię

Angelova L., Ogden B., Craig J., Chandrapal H., Manandhar D., Deep discoveries: A towards a national collection foundation project final report, 2021, https://doi.org/10.5281/zenodo.5710412 [access: 7.11.2024].

CrossRef

Archives, Access and Artificial Intelligence: Working with Born-Digital and Digitized Archival Collections, ed. L. Jaillant, Bielefeld 2022.

Arnold T., Ayers N., Madron J., Nelson R, Tilton L., Visualizing a Large Spatiotemporal Collection of Historic Photography with a Generous Interface. Presented at the 5th Workshop on Visualization for the Digital Humanities, 2020, https://doi.org/10.48550/arXiv.2009.02242 [access: 7.11.2024].

CrossRef

Arnold T., Leonard P., Tilton L., Knowledge Creation Through Recommender Systems, “Digital Scholarship in the Humanities” 2017, vol. 32, pp. 151–157, https://doi.org/10.1093/llc/fqx035 [access: 7.11.2024].

CrossRef

Arnold T., Tilton L., Distant Viewing: Computational Exploration of Digital Images, Cambridge 2023. Aske K., Giardinetti M., (Mis)matching Metadata: Improving Accessibility in Digital Visual Archives through the EyCon Project, “Journal on Computing and Cultural Heritage” 2023, vol. 16, issue 4, article 76, pp. 1–20, https://doi.org/10.1145/3594726 [access: 7.11.2024].

CrossRef

Bakker R., Rowan K., Hu L., Guan B., Liu P., Li Z., He R., Monge C., AI for archives: Using facial recognition to enhance metadata, “Works of the FIU Libraries” 2020, vol. 93, pp. 1–15, https://digitalcommons.fiu.edu/glworks/93 [access: 7.11.2024].

Bushey J., Born digital images as reliable and authentic records, master’s thesis: University of British Columbia, 2005, https://doi.org/10.14288/1.0092057 [access: 7.11.2024].

CrossRef

Bushey J., He Shoots, He Stores: New Photographic Practice in the Digital Age, “Archivaria” 2008, vol. 65, issue 1, pp. 125–149, https://archivaria.ca/index.php/archivaria/article/view/13172 [access: 7.11.2024].

Bushey J., The archival trustworthiness of digital photographs in social media platforms, doctoral thesis: University of British Columbia, 2016, https://doi.org/10.14288/1.0300440 [access: 7.11.2024].

CrossRef

Chumachenko K., Mannisto A., Iosifidis A., Raitoharju J.Machine learning based analysis of Finnish world war II photographers, “IEEE Access” 2020, vol. 8, pp. 144184-144196, https://doi.org/10.1109/ACCESS.2020.3014458 [access: 7.11.2024].

CrossRef

Colavizza G., Blanke T., Jeurgens C., Noordegraaf J., Archives and AI: An overview of current debates and future perspectives, “Journal on Computing and Cultural Heritage” 2021, vol. 15, no. 1, article 4, pp. 1–15, https://doi.org/10.1145/3479010 [access: 7.11.2024].

CrossRef

Conway P., Punzalan R.L., Fields of Vision: Toward a New Theory of Visual Literacy for Digitized Archival Photographs, “Archivaria” 2011, vol. 71, pp. 63–97, https://archivaria.ca/index.php/archivaria/article/view/13331 [access: 7.11.2024].

Cox J., Tilton L., The digital Public Humanities: Giving New Arguments and New Ways to Argue, „Review of Communication” 2019, vol. 19, issue 2, pp. 127–146, https://doi.org/10.1080/15358593.2019.1598569 [access: 7.11.2024].

CrossRef

Delaney J.An Inconvenient Truth? Scientific Photography and Archival Ambivalence, “Archivaria” 2008, vol. 65, pp. 75–95, https://archivaria.ca/index.php/archivaria/article/view/13169 [access: 7.11.2024].

Dentler J., Workshop Report: Multimodal Visual Similarity Algorithms and Digitized Photo Archives. EyCon Visual AI and Early Conflict Photography, Blog Post, 2023, https://eycon.hypotheses.org/1539 [access: 7.11.2024].

Eiler F., Graf S., Dorner W., Artificial intelligence and the automatic classification of historical photographs [in:] Proceedings of the Sixth International Conference on Technological Ecosystems for Enhancing Multiculturality, ed. F.J. García-Peñalvo, New York 2018, pp. 852–856, https://doi.org/10.1145/3284179.3284324 [access: 7.11.2024].

CrossRef

Fewster K., Case Study: Testing computational Archival Science frameworks using AI tools in analyzing the Spelman College Archives photograph collection, InterPARES Trust AI, 2024, https://interparestrustai.org/assets/public/dissemination/ProctorCaseStudy.pdf [access: 7.11.2024].

Fewster K., Case Study: The Endangered Archives Programme’s use of AI tools in evaluating Jacques Toussele’s Cameroonian photography archives, InterPARES Trust AI, 2024, https://interparestrustai.org/assets/public/dissemination/ZeitlynInterviewCaseStudy.pdf [access: 7.11.2024].

Han X.Y., Papyan V., Prokop E., Donoho D.L., Johnson C.R., Chapter 1: Artificial intelligence and discovering the digitized photoarchive [in:] Digital Humanities Research, ed. L. Jailant, Bielefeld 2022, pp. 29–60, https://doi.org/10.14361/9783839455845-002 [access: 7.11.2024].

CrossRef

Leary W.H., The archival appraisal of photographs: a RAMP study with guidelines, Paris 1985, https://unesdoc.unesco.org/ark:/48223/pf0000063749 [access: 7.11.2024].

Lincoln M., Corrin J., Davis E., Weingart S.B., CAMPI: computer-aided metadata generation for photo archives initiative, Pittsburgh 2020, https://doi.org/10.1184/R1/12791807.v2 [access: 7.11.2024].

CrossRef

Long D., Magerko B., What is AI literacy? Competencies and design considerations [in:] CHI’20 : proceedings of the 2020 CHI Conference on Human Factors in Computing Systems: April 25–30, 2020, Honolulu, HI, USA, New York 2020, pp. 1–16.

Mallick S., EyCon: What are we doing with Machine Learning and Computer Vision, EYCON Blog Post, 2022, https://eycon.hypotheses.org/1020 [access: 7.11.2024].

Mannheimer S., Rossmann D., Clark J., Shorish Y., Bond N., Scates Kettler H., Sheehey B., Young S.W.H., Introduction to the Special Issue: Responsible AI in Libraries and Archives, “Journal of eScience Librarianship” 2024, vol. 13, no. 1, https://publishing.escholarship.umassmed.edu/jeslib/article/id/860/ [access: 7.11.2024].

Milleville K., Broeck A.V.D., Vanderperren N., Vissers,R., Priem M., Van De Weghe N., Verstockt S., Enriching image archives via facial recognition, “Journal on Computing and Cultural Heritage” 2023, vol. 16, no. 4, pp. 1–18, https://doi.org/10.1145/3606704 [access: 7.11.2024].

CrossRef

O’Donnell L., Towards Total Archives: The Form and Meaning of Photographic Records, “Archivaria” 1994, vol. 38, pp. 105–118, https://archivaria.ca/index.php/archivaria/article/view/12028 [access: 7.11.2024].

Oestreicher C., Reference and Access for Archives and Manuscripts, Chicago 2020.

Proctor J., Marciano R., An AI-assisted framework for rapid conversion of descriptive photo metadata into linked data [in:] IEEE International Conference on Big Data (Big Data), 2021, pp. 2255–2261, https://doi.org/10.1109/BigData52589.2021.9671715 [access: 7.11.2024].

CrossRef

Ritzenthaler M.L., Vogt-O’Connor D., Photographs: archival care and management, Chicago 2006, https://search.worldcat.org/title/Photographs-:-archival-care-and-management/oclc/70175019 [access: 7.11.2024].

Rockembach M., AI Literacy: A Muse for Records Management and Archival Professionals [in:] Artificial Intelligence and Documentary Heritage. SCEaR Newsletter 2024, Special Issue 2024, eds. L. Duranti, C. Rogers, 2024, pp. 90–95, https://interparestrustai.org/assets/public/dissemination/SCEaRNewsletter SpecialIssue2024ArtificialIntelligence.pdf [access: 7.11.2024].

Schwartz J.M., Coming to Terms with Photographs: Descriptive Standards, Linguistic “Othering” and the Margins of Archivy, “Archivaria” 2002, vol. 54, pp. 142–171, https://archivaria.ca/index.php/archivaria/article/view/12861 [access: 7.11.2024].

Schwartz J.M., Records of Simple Truth and Precision: Photography, Archives, and the Illusion of Control, “Archivaria” 2000, vol. 50, pp. 1–40, https://archivaria.ca/index.php/archivaria/article/view/12763 [access: 7.11.2024].

Schwartz J.M., “We Make Our Tools and Our Tools Make Us”: Lessons from Photographs for the Practice, Politics, and Poetics of Diplomatics, “Archivaria” 1995, vol. 40, pp. 40–74, https://archivaria.ca/index.php/archivaria/article/view/12096 [access: 7.11.2024].

Wevers M., Smits T., The visual digital turn: Using neural networks to study historical images, “Digital Scholarship in the Humanities” 2020, vol. 35, issue 1, pp. 194–207, https://doi.org/10.1093/llc/fqy085 [access: 7.11.2024].

CrossRef
Netography

AEOLIAN Network. Homepage, https://www.aeolian-network.net/ [access: 7.11.2024].

AURA Network. Homepage, https://www.aura-network.net/ [access: 7.11.2024].

Github. katerynaCh / Finnish-WW2-photographers-analysis, https://github.com/katerynaCh/Finnish-WW2-photographers-analysis [access: 7.11.2024].

InterPARES Trust AI. Home Page, https://interparestrustai.org/ [access: 7.11.2024].

LUSTRE. Home Page, https://lustre-network.net/team/ [access: 7.11.2024].

The EyCon project (eng.). (n.d.), https://eycon.hypotheses.org/ [access: 7.11.2024].

Informacje

Informacje: Archeion, 2024, 125, s. 33-54

Typ artykułu: ORIGINAL_RESEARCH_ARTICLE

Tytuły:

Angielski: Envisioning Archival Images with Artificial Intelligence
Polski: Wizja archiwizacji obrazów za pomocą sztucznej inteligencji

Autorzy

https://orcid.org/0000-0002-8569-5360

Jessica Bushey
San José State University
, Stany Zjednoczone Ameryki
https://orcid.org/0000-0002-8569-5360 Orcid
Kontakt z autorem
Wszystkie publikacje autora →

San José State University
Stany Zjednoczone Ameryki

Publikacja: 25.11.2024

Status artykułu: Otwarte __T_UNLOCK

Licencja: CC-BY-NC-ND  ikona licencji

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Finansowanie artykułu:

External funding provided through: AI for Trust in Records and Archives. Partnership Grant (2021–2026). Social Sciences and Humanities Council of Canada.

Udział procentowy autorów:

Jessica Bushey (Autor) - 100%

Korekty artykułu:

-

Języki publikacji:

Angielski

Liczba wyświetleń: 3626

Liczba pobrań: 914

Wizja archiwizacji obrazów za pomocą sztucznej inteligencji

Envisioning Archival Images with Artificial Intelligence

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