Using AI in Research

Two people consulting about AI

How we can help: literacy, learning, and engagement

At Yale Library, we offer support and AI-powered tools to improve access to collections and unlock new research possibilities. We can help you get started with AI, evaluate the outputs of AI systems, and provide tailored advice on effectively integrating AI tools into your research, teaching, and learning. Whether you are embarking on your first AI project or seeking to deepen your understanding of AI’s potential, we are here to support you. Let us help you build AI fluencies, thoughtfully integrate AI into your work, and connect you with others working in similar areas.

Workshops and Instruction

AI instruction sessions recently offered by Yale Library include:

If you would be interested in attending future sessions of any of these, or to suggest other instruction topics, please contact us at lauren.dimonte@yale.edu. Share your suggestions for this page, and other AI programming you’d like to see the library offer. We are interested in hearing about your AI experiences to date, and how we can best support you. We welcome and appreciate all feedback.

Interested in upcoming workshops? Sign up for the DHLab’s newsletter.

Yale Library AI Initiatives

About Artificial Intelligence

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. Common AI tasks include problem-solving, understanding natural language, recognizing patterns, and making decisions. AI systems are typically designed to perform tasks that usually require human intelligence, such as visual perception, speech recognition, decision-making, and language translation.

Our Goals for the Future

Recognizing the enormous potential and opportunities of AI, as well as the many questions still to be answered, Yale Library’s work in AI is guided by these goals:

Promote the ethical and effective use of AI in research and learning
Use AI to enhance library services and increase engagement with collections
Meaningfully contribute to Yale’s leadership in AI
Support and enhance AI literacy for Yale students, faculty, and staff

Academic disciplines and departments as well as individual faculty differ widely in the ways they use AI. For an overview of AI research, current uses, and goals at Yale, read the June 2024 report of the Yale Task Force on AI. If you have specific questions about permissible uses of AI in class assignments, contact your course instructor.

AI Research in Digital Collections

Digital Collection Application (in development; seeking instructors to collaborate)

Yale Library is developing an AI application that allows researchers to pull items from Digital Collections and apply Large Language Models (LLMs) to perform tasks like summarization, translation, and entity extraction. Although it’s still in a beta phase, this application shows potential to transform research in Yale Library’s large and rapidly growing digital collections. The library is looking to partner with instructors to help test the application’s functionality and shape its development. Interested instructors may with to use the tool to support their students’ engagement with digitized special collections, or to help students learn more about how LLMs work. Are you an instructor who would like to help us take the application to the next level? We can provide you with funding for a research assistant to support integrating the application to a course. Contact Lauren Di Monte at lauren.dimonte@yale.edu for more information.

AI and Environmental Sustainability

Use of TinyML

The library is convening conversations and explorations around the use of TinyML, a type of machine learning that allows models to run on smaller, less powerful devices. This is part of an effort to explore more sustainable ways of using AI tools for research, and it continues conversations already happening in Digital Humanities around minimal computing.

Computational Methods and Data Support

Using and Developing AI Tools

The Computational Methods and Data team offering help and expertise on using AI tools and developing AI tools for research. Students and researchers can use the DH Lab’s Machine Learning Cube, which can support GPU-accelerated machine learning projects. The team has also created the Resources for Digital Humanities: Machine Learning Words and Concepts guide, and is expanding its program of AI-related instruction.

Library Staff Initiatives

Organizational Learning

Library staff are engaging in research, learning, and projects to understand how AI might impact library work in areas like metadata, evidence synthesis, provenance research, and resource discovery.

Also in development is an organizational learning plan that will maximize staff readiness to engage with AI across Yale Library. The program is designed to:

Build shared knowledge and a shared vocabulary around AI concepts, tools, methods, and outputs
Motivate staff to explore the implications of AI within their domains and for current practices
Surface new or priority areas of organizational learning and development related to AI
Contribute towards the development of an AI competency framework for Yale Library

AI Support Triage Model (in development)

The library is collaborating with the Poorvu Center for Teaching and Learning on a triage model to improve support for faculty and students through shared review and responses to questions.