This article equips readers with processes to identify ethical artificial intelligence solutions that may benefit libraries, archives, and museums. It provides definitions of common artificial intelligence concepts and terms. It then describes existing and potential use cases for artificial intelligence solutions. It concludes with an in-depth discussion on how to interrogate artificial intelligence models for potential ethical issues and how to remediate those issues before implementation.
D’IgnazioCatherineKleinLauren F.2020. Data Feminism. Cambridge, MA: The MIT Press. doi:10.7551/mitpress/11805.001.0001.
5.
Eitel-PorterRay. 2021. “Beyond the Promise: Implementing Ethical AI.” AI and Ethics1 (1): 73–80. doi:10.1007/s43681-020-00011-6.
6.
FjeldJessicaAchtenNeleHilligossHannahNagyAdamSrikumarMadhulika. 2020. “Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-Based Approaches to Principles for AI.” SSRN Scholarly Paper 3518482. Social Science Research Network, January15, 2020. doi:10.2139/ssrn.3518482.
HutchinsonTim. 2020. “Natural Language Processing and Machine Learning as Practical Toolsets for Archival Processing.” Records Management Journal30 (2): 155–74. doi:10.1108/RMJ-09-2019-0055.
9.
JaillantLise. 2022. Archives, Access and Artificial Intelligence: Working with Born-Digital and Digitized Archival Collections. 1st ed. Transcript Verlag. https://www.jstor.org/stable/jj.11425482.
10.
JaillantLise, ed. 2025. Navigating Artificial Intelligence for Cultural Heritage Organisations. UCL Press.
PadillaThomas. 2019. “Responsible Operations: Data Science, Machine Learning, and AI in Libraries. OCLC Research Position Paper.” OCLC Online Computer Library Center, Inc. https://eric.ed.gov/?id=ED603715.
