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
- Teaching and Generative AI
- Guide to Teaching with Gen AI From the University of Oregon
- September 2023
- 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
- Acceptable Use of ChatGPT and Similar AI Tools
- UT Austin Information Security Office (ISO)
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?