AI in Research Program

Empowering the CMU community to use AI tools in research responsibly. The AI in Research (AIR) Program is a new initiative from CMU Libraries that provides expertise, training, and a community of practice around the effective and responsible use of generative AI (GenAI) and other AI-powered tools to facilitate academic research. The program helps researchers explore AI tools, adopt best practices, and connect with peers using similar tools in scholarly work.

Program Scope

The program is designed for researchers interested in applying out-of-the-box AI tools – such as research assistants, data summarizers, or coding assistants – within the research process. Our services focus on helping researchers use these tools responsibly, rather than developing the AI models behind them.

Tool Assessment & Guidance

With new tools emerging constantly, it can be difficult to know which ones are effective or appropriate for your research. We are developing a Tool Assessment Framework to help CMU researchers understand whether a given AI-powered tool is suitable for their research needs. This framework helps to guide researchers as they explore AI-powered tools by considering factors such as:

• Functionality and mechanism
• Data sources and documentation
• Output quality and reproducibility
• Transparency, ethics, and privacy

This evolving framework aims to help students and researchers better understand a tool’s strengths, limitations, and potential risks before integrating it into your workflows.

Training & Capacity Building

Our growing suite of training workshops and resources is designed to help researchers across all disciplines understand the foundations of using GenAI and other AI-powered tools effectively and responsibly:

• What LLMs are good and bad at
• Prompt design strategies
• Avoiding common pitfalls (e.g., hallucinations, citations errors)
• Improving reproducibility and transparency

Workshops are open to students, faculty and staff from all disciplines. Individuals with all skill levels and backgrounds are welcome, whether you’re just getting started or looking to deepen your AI literacy.

Resources:

• Artificial Intelligence Research LibGuide: Provides essential definitions of key artificial intelligence concepts and connects researchers to CMU Libraries' specialized resources, including research tools, datasets, and scholarly articles.
• Generative AI LibGuide: Provides essential resources for understanding and effectively using AI tools in academic settings, covering prompt engineering techniques, ethical considerations, citation practices, and CMU-specific guidelines to support teaching, learning, and research applications.
• TDM Guide: Libraries resources for Text and Data Mining.
• Best Practices for Large Language Models: A curated selection of examples to get the best out of AI chatbots.
• POEM: Metaliteracies.
• CLEAR: A framework for prompt engineering.
• Anthropic's Prompt Engineering Tutorial: An interactive tutorial that helps you understand how to engineer optimal prompts within Claude.