Mitigating Bias in GLAM Search Engines: A Simple Rating-Based Approach and Reflection
Galleries, Libraries, Archives and Museums (GLAM) institutions are increasingly opening up their digitised collections and associated data for engagement online via their own websites/search engines and for reuse by third parties. Although bias in GLAM collections is inherent, bias in the search engines themselves can be rated. This work proposes a bias rating method to reflect on the use of search engines in the GLAM sector along with strategies to mitigate bias. The application of this to an existing large art collection shows the applicability of the proposed method and highlights a range of existing issues.- doi
- 10.1145/3603163.3609043
- isbn
- 979-8-4007-0232-7
- name
- Mitigating Bias in GLAM Search Engines: A Simple Rating-Based Approach and Reflection
- source
- acm_url
- https://dl.acm.org/doi/10.1145/3603163.3609043
- authors
- Xinran Tian, Bernardo Pereira Nunes, Katrina Grant, Marco Antonio Casanova
- doi_url
- https://doi.org/10.1145/3603163.3609043
- license
- © Copyright held by the owner/author(s). Publication rights licensed to ACM.
- summary
- Galleries, Libraries, Archives and Museums (GLAM) institutions are increasingly opening up their digitised collections and associated data for engagement online via their own websites/search engines and for reuse by third parties. Although bias in GLAM collections is inherent, bias in the search engines themselves can be rated. This work proposes a bias rating method to reflect on the use of search engines in the GLAM sector along with strategies to mitigate bias. The application of this to an existing large art collection shows the applicability of the proposed method and highlights a range of existing issues.
- published
- 2023-09-04
- conference
- HT '23: 34th ACM Conference on Hypertext and Social Media, Rome, Italy, September 4-8, 2023
- open_access
- true
- acm_html_url
- https://dl.acm.org/doi/full/10.1145/3603163.3609043
- displayAuthor
- Xinran Tian, Bernardo Pereira Nunes, Katrina Grant, Marco Antonio Casanova
- displayPublishTime
- 2023-09-04
Powered by Seed HypermediaOpen App