dc.contributor.author |
Mannheimer, Sara |
|
dc.contributor.author |
Rossmann, Doralyn |
|
dc.contributor.author |
Clark, Jason |
|
dc.contributor.author |
Shorish, Yasmeen |
|
dc.contributor.author |
Bond, Natalie |
|
dc.contributor.author |
Kettler, Hannah Scates |
|
dc.contributor.author |
Sheehey, Bonnie |
|
dc.contributor.author |
Young, Scott W. H |
|
dc.date.accessioned |
2024-12-08T23:30:28Z |
|
dc.date.available |
2024-12-08T23:30:28Z |
|
dc.date.issued |
2024-03-06 |
|
dc.identifier.issn |
2161 3974 |
|
dc.identifier.uri |
https://doi.org/10.7191/jeslib.860 |
|
dc.identifier.uri |
https://sadil.ws/handle/123456789/4614 |
|
dc.description |
6 p. |
sm |
dc.description.abstract |
Librarians and archivists are often early adopters and experimenters with new technologies. Our field
is also interested in critically engaging with technology, and we are well-positioned to be leaders in the
slow and careful consideration of new technologies. Therefore, as librarians and archivists have begun
using artificial intelligence (AI) to enhance library services, we also aim to interrogate the ethical issues
that arise while using AI to enhance collection description and discovery and streamline reference
services and teaching. The IMLS-funded Responsible AI in Libraries and Archives project aims to create
resources that will help practitioners make ethical decisions when implementing AI in their work. The
case studies in this special issue are one such resource. Seven overarching ethical issues come to light
in these case studies—privacy, consent, accuracy, labor considerations, the digital divide, bias, and
transparency. This introduction reviews each issue and describes strategies suggested by case study
authors to reduce harms and mitigate these issues |
sm |
dc.description.sponsorship |
Institute of Museum and Library Services |
sm |
dc.language.iso |
en |
sm |
dc.publisher |
Journal of eScience Librarianship |
sm |
dc.relation.ispartofseries |
;Vol 13, No.1 |
|
dc.subject |
Responsible AI |
sm |
dc.subject |
Artificial Intelligence |
sm |
dc.subject |
Privacy |
sm |
dc.subject |
Consent |
sm |
dc.subject |
Accuracy |
sm |
dc.subject |
Labor |
sm |
dc.subject |
Digital divide |
sm |
dc.subject |
Bias |
sm |
dc.subject |
Transparency |
sm |
dc.title |
Introduction to the Special Issue: Responsible AI in Libraries and Archives |
sm |
dc.type |
Article |
sm |