Doing 3D: Implementations and Best Practices in Applying 3D Technologies Across Higher Education

Presentation for the 2018 American Library Association Annual Conference, Library and Information Technology Association session. This presentation describes current methods for 3D scanning and modeling, and how this technology has been implemented through three different projects involving higher education

Introduction to the Special Issue: Responsible AI in Libraries and Archives

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

Introduction to the Special Issue: Responsible AI in Libraries and Archives

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.This article is published as Mannheimer, Sara, Doralyn Rossmann, Jason Clark, Yasmeen Shorish, Natalie Bond, Hannah Scates Kettler, Bonnie Sheehey, and Scott WH Young. "Introduction to the Special Issue: Responsible AI in Libraries and Archives." Journal of eScience Librarianship 13, no. 1 (2024). doi: https://doi.org/10.7191/jeslib.860. Copyright © 2024 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

Cultivating Accountability by Eliciting Upward Feedback

In many work environments, regular staff performance evaluations are the norm, and this practice has real impact on staff promotion opportunities and raises. However, this process is typically top down, i.e., the supervisor evaluates the supervisee. Often employees do not have the opportunity to evaluate their supervisor in turn. This norm of personnel evaluation potentially creates barriers for staff to express their needs as workers, as well as for supervisors to listen, learn, and grow. This presentation will outline how two newer middle managers at different institutions approached seeking upward feedback from their direct reports. They will discuss what inspired them, how they implemented upward feedback opportunities, what feedback they received from their colleagues, and their reflections since then. For both managers, this process provided crucial feedback and set a precedent to repeat the feedback loop throughout their careers to foster a more open, inclusive, and equitable work environment. We will draw upon published research on mechanisms of accountability within organizations (particularly within relationships with power differentials) while narrating our own lived experiences. Throughout we will create opportunities for reflection from attendees by posing questions in an Etherpad, such as: We must make explicit both to whom and for what we owe accountability. What are managers accountable to their direct reports for? What are some necessary conditions for direct reports to feel safe enough to be candid when offering feedback to their managers? How can managers create these conditions? How do we operationalize accountability to direct reports? How do we design trustworthy processes, independent of the individuals occupying management roles? </p

Cultivating Accountability by Eliciting Upward Feedback

Session proposal, slides (including speaker notes), interactive questions for reflection with participants, and speaker responses to Q&amp;A for our Conference on Academic Library Management (CALM) 2021 presentation

Annotated Bibliography

This project reflects the work building the annotated bibliography. It includes the published states of the bibliography and the running - crowdsourced - bibliography for developmen

Vancouver Statement on Collections as Data

Arabic translation Spanish translation French translation Since the Santa Barbara Statement on Collections as Data (2017) was published, engagement with collections-as-data has grown internationally. Institutions large and small, individually and collectively, have invested in developing, providing access to, and supporting responsible computational use of collections as data. An updated statement was needed in light of increased community implementation of collections as data in context of an ever more complex data landscape. The Vancouver Statement suggests a set of principles for thinking through questions that collections-as-data work produces, as part of an expanding global, interprofessional, and interdisciplinary effort to empower memory, knowledge, and data stewards (e.g., practitioners and scholars) who aim to support responsible development and computational use of collections as data. This stewardship role only grows in importance as artificial intelligence applications, trained on vast amounts of data, including collections as data, impact our lives ever more pervasively. The Vancouver Statement is the product of diverse contributions from the participants of the working event, Collections as Data: State of the Field and Future Directions, held April 25-26, 2023 at Internet Archive Canada in addition to asynchronous community feedback. Professional translation of the Vancouver Statement was provided by Transolution. Special thanks go to Gimena del Rio Riande and Gaëlle Béquet for additional review of statement translations