AI Interest Group for Libraries, Archives, and Museums
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Learning Materials

, Filed Under: Learning Materials

Reference and Research Support

On October 25, 2023, we held the second session of the AI Interest Group. The topic was Reference and Research Support.

Aaron Choate, the Director of Research and Strategy at UT Libraries and the Chair of the AI Interest Group, led the panel discussion.

We were honored to have the following panelists contribute their insights:

  • Jim Kuhn, Associate Director for Technical and Digital Services at the Harry Ransom Center
  • Joe Dobbs, Head of User Services at Perry Castañeda Library
  • Soo Young Rieh, Senior Associate Dean for Academic Affairs and Professor of UX Design and Research in the School of Information
  • Karina Sanchez, Scholars Lab Librarian

The session sparked an insightful conversation on the applications of AI in reference and research services. We are so pleased with the rich exchange of ideas and the depth of the conversation, and look forward to continuing the discussion in our future sessions! If you are interested in attending, please fill out a form on our Events page.

Here are some of the materials we distributed in advance of the second meeting:

  • Topic: Reference and Research Support
  • Date: October 25, 2023

Videos

  • The Importance of Open Models in AI and Implications for the Future of Oversight
    • Link: Video recording 
    • Hosted by Good Systems: A UT Grand Challenge 
    • Speaker: Ben Brooks, Stability AI 
    • Duration: 01:03:13
    • Description from video: Open models play a vital role in helping to promote transparency, security, and competition in AI. However, open models are highly capable and widely available, posing a challenge for regulators and policymakers considering the future of oversight. In his talk, Ben Brooks (Head of Public Policy for Stability AI) will discuss recent developments in open models, AI regulation, and practical steps that policymakers can take to mitigate emerging risks while continuing to foster open and grassroots innovation.
    • Oct. 4, 2023 

Websites, Papers, Other

  • AI and science: what 1,600 researchers think
    • Authors: Richard Van Noorden & Jeffrey M. Perkel
    • Nature, September 27, 2023
    • “Machine-learning statistical techniques are now well established, and the past few years have seen rapid advances in generative AI, including large language models (LLMs), that can produce fluent outputs such as text, images and code on the basis of the patterns in their training data. Scientists have been using these models to help summarize and write research papers, brainstorm ideas and write code, and some have been testing out generative AI to help produce new protein structures, improve weather forecasts and suggest medical diagnoses, among many other ideas.”  Link to highlight. 
  • Generative AI, scholarly and cultural language models, and the return of content
    • Author: Lorcan Dempsey 
    • June 28, 2023
    • “There is now a diverse and expanding universe of LLMs. There are foundation models from large established players (e.g. Google and Microsoft, individually and in its support for OpenAI) and from several startups (e.g. Anthropic), some of which are developing into platforms for others. There are platforms which make these and other models available in managed environments (e.g. Amazon, Microsoft, Fixie). There is a flourishing ecosystem around open source LLMs which are growing in capabilities, some targeted at more affordable computational environments (many of these are aggregated on Hugging Face, an important AI provider of infrastructure and services).  And then there is a variety of domain specific initatives developing models, or training more general models, for specialised communities or applications (e.g. medicine, finance, biosciences).” Link to highlight. 
  • An initial interpretation of the U.S. Department of Education’s AI report: Implications and recommendations for academic libraries
    • Author: Dr. Leo S. Lo, Dean and Professor of the College of University Libraries and Learning Services, University of New Mexico
    • Online pub date: June 18, 2023
    • The Journal of Academic Librarianship (Volume 49, Issue 5, September 2023, 102761)
    • “Now is the time for academic libraries to step up and take action. I call on library leaders to embrace the opportunities presented by AI, to engage in meaningful collaboration with other stakeholders, and to lead the way in ensuring that AI is used effectively and ethically in our libraries. I also call on librarians to enhance their AI literacy, to get involved in the design and implementation of AI tools, and to be prepared to confront the challenges that AI presents” Link to highlight.  

Archives and Special Collections 

  • LUSTRE: The overall aim of the LUSTRE project is to connect policy makers with Computer Scientists, Digital Humanists and professionals in the GLAM sector (Galleries, Libraries, Archives and Museums). https://lustre-network.net/outputs/ 

Policies and Values 

Thank you to Jim Kuhn, Corey Halaychik, and Michele Ostrow for contributing to the materials we sent out this month!

, Filed Under: Learning Materials

Introduction and Road Map

On September 28, 2023, we held the first meeting of the AI Interest Group, a dynamic assembly of Libraries, Archives, and Museum (LAM) staff from across campus; iSchool faculty; and other Artificial Intelligence (AI) enthusiasts. Our first meeting had two objectives. The first objective was to ascertain the levels of the group’s current knowledge about Artificial Intelligence (AI). The second objective was to find out what interested the group about the potential for AI in LAMs on the UT Austin campus.

After the first session, we planned a roadmap of topics for future meetings that will take place over the course of this school year. These will focus on the intersections of AI and the following library, archive, and museum domains:

  • Reference and Research Support
  • Metadata, Cataloging, and Technical Services
  • Archives and Collections
  • Information and Digital Literacy
  • Systems and DevOps
  • Ethical Considerations

If you are interested in attending future sessions, please fill out a form on our Events page.

Here are some of the resources we sent to the group in advance of that first meeting:

  • Topic: Brainstorming, narrowing down interests, introductions
  • Date: September 28, 2023 

Videos

  • A guide to using ChatGPT effectively:
    • Presented by: Sara Brumfield and Ben Brumfield
    • Title: “Prompt Writing and Interacting with ChatGPT for Librarians and Archivists” 
    • Date: June 22, 2023  
    • Watch here 
    • Duration: 00:58:37 
    • Hosted by From the Page. 
  • ALA Core Presentation
    • Presented by: Greg Ritter and Mary Strain (Amazon Web Services)
    • Title: “AI and Machine Learning: Transforming the Modern Campus and Library” 
    • Date: July 21, 2023.  
    • Watch here | Slides
    • Duration: 01:01:29
  • Developing an IT Support-AI at MIT, using Langchain
    • Presented by: Julius Heitkoetter, MIT Department of Physics
    • Title: “AI Augmented Support for Computing Services,”
    • Date: August 4, 2023
    • Watch here
    • Duration: 00:11:32
    • GitHub repository  
  • Adoption of LLMs in teaching
    • Presented by: Christopher Capozzola, MIT Department of Physics
    • Title: “How LLMs Are Changing Teaching at MIT” 
    • Date: August 4, 2023  
    • Watch here 
    • Duration: 00:18:51
  • AI and Academic Libraries
    • Panel organized by Lorraine Harricombe
    • Title: “From Gutenberg to ChatGPT: Will AI change the mission of academic and research libraries?”
    • International Federation of Library Associations and Institutions (IFLA) Academic & Research Libraries (ARL) “Hot Topics” session
    • Date: Aug 22, 2023
    • Watch and access slides here

Websites, Papers, Other

  • AI4LAM: AI for Libraries, Archives & Museums
    • AI4LAM is an international, participatory community focused on advancing the use of artificial intelligence in, for and by libraries, archives and museums. (Description from website)
    • Sign up for the AI4LAM Slack group

Food for thought from a session from the 2022 AI4LAM Conference: 

A Proposed Framework for Operationalising AI in LAMs

  • Facilitators: Abigail Potter and Meghan Ferriter, LC Labs/Digital Strategy Division/Office of the Chief Information Officer Library of Congress
  • Abstract: Libraries, archives, museums and other public cultural heritage organisations have shared challenges in operationalizing AI technologies in ways that help them achieve their goals and be responsible stewards of heritage collections. Through research, experimentation and collaboration the LC Labs team has developed a set of tools to document, analyse, prioritise and assess AI technologies in a LAM context. This framework is in draft form and in need of additional use cases and perspectives.

Sample Elements and Prompts from the framework:

  • Organizational Profile: How will or does your organization want to use AI or Machine learning?
  • Define the Problem you are trying to solve.
  • Write a user story about the AI/ML task or system your are planning/doing
  • Risks and Benefits: What are the benefits and risks to users, staff and the organisation when an AI/ML technology is/will be used?
  • What systems or policies will/do the AI/ML task or system impact or touch?
  • What are the limitations of future use of any training, target, validation or derived data?
  • Data Processing Plan: What documentation are/will you require when using AI or ML technologies
  • What existing open source or commercial platforms offer pathways into use of AI?
  • What are the success metrics and measures for the AI/ML task?
  • What are the quality benchmarks for the AI/ML output? What could come next?