Summary and Schedule
Understand the opportunities and risks of using AI tools, including large language models, in research conducted on Sagehen HPC. This workshop covers the current AI landscape, Pomona College policies for AI use, data classification considerations, and guidance on whether to use local models on Sagehen or cloud-based AI services. You’ll learn responsible practices for protecting sensitive research data, ensuring research integrity, and using AI tools ethically. This workshop is part of the Pomona College HPC Workshop Series.
Pomona College HPC Context
This workshop is part of the Pomona College Research Computing Workshop Series for researchers using the Sagehen HPC cluster.
Prerequisites:
- Completed Workshop 13 (HPC Security Orientation)
- Understanding of data classification (Workshop 14) recommended
- Required for all users running AI/ML workloads on Sagehen
- A Sagehen HPC account (request from its-hpc@pomona.edu)
- Access to the OnDemand portal
For questions or support, contact the Research Computing team at its-hpc@pomona.edu.
Designed for all researchers and students, this workshop assumes no prior AI knowledge. You will gain practical understanding of how to responsibly leverage AI tools while protecting your research, respecting intellectual property, and adhering to Pomona College policies.
Acknowledgments
Developed by Andrew Wilson, Director of Research Computing and Digital Scholarship at Pomona College, with Andrei Motchenko, who tested, edited and produced screenshots for the workshop series.
| Setup Instructions | Download files required for the lesson | |
| Duration: 00h 00m | 1. The AI Landscape for Researchers |
What AI tools are available for research and academia? Why would you run AI models on HPC clusters instead of cloud services? |
| Duration: 00h 15m | 2. Types of AI Models |
What types of AI models are available for research? What are the computational requirements for different model types? How do open-source models compare to proprietary ones? |
| Duration: 00h 30m | 3. Pomona’s AI Use Policy |
What is Pomona’s policy on AI tool usage? What are the three data classification tiers? What are the consequences of policy violations? |
| Duration: 00h 45m | 4. Data Classification for AI |
How do you classify data for AI tool usage? What is the difference between PUBLIC, PROPRIETARY, and RESTRICTED data? Which AI tools are appropriate for each classification? |
| Duration: 01h 05m | 5. Sensitive Data and AI |
How do FERPA, HIPAA, and export controls affect AI tool choices? How do you protect sensitive data when using AI? What compliance frameworks apply to AI workflows? |
| Duration: 01h 25m | 6. Local vs Cloud AI |
When should I use cloud AI vs. local AI on Sagehen HPC? What are the tradeoffs in quality, speed, privacy, and cost? |
| Duration: 01h 40m | 7. Running Models on Sagehen HPC |
How do I set up AI tools on Sagehen HPC? What modules and environments are needed? How do I access GPUs and submit AI jobs? |
| Duration: 02h 05m | 8. Running Local LLMs on Sagehen HPC |
How do I set up and run open-source LLMs on Sagehen? How do I use Hugging Face models responsibly? How do I build a private AI pipeline for restricted data? |
| Duration: 02h 30m | 9. Responsible AI Practices |
How do I properly disclose AI tool usage in research? How do I verify AI-generated content for accuracy? What are hallucinations and how do I detect them? |
| Duration: 02h 50m | 10. Ethical Considerations and Next Steps |
How do AI systems encode bias and what are the consequences? How do you audit AI outputs for fairness? What are the broader ethical implications of AI in research? |
| Duration: 03h 10m | Finish |
The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.
Setup: Responsible Use of AI Tools on HPC
Before the Workshop
Software and Accounts
- Web browser (Chrome, Firefox, Safari, Edge)
- Optional: Pomona NetID for examples
- Optional: Access to Sagehen HPC (not required, but helpful for local AI demo)
No Installation Required!
This workshop uses cloud AI assistants and an optional local setup. No special software needs to be installed in advance.
Optional: Try the Tools in Advance
If you want to get familiar with external AI tools, the three most commonly used at Pomona are:
- ChatGPT (OpenAI): https://chatgpt.com
- Claude (Anthropic): https://claude.ai
- Gemini (Google): https://gemini.google.com
Each offers a no-cost tier. Sign in with a personal account for the workshop exercises — we will only ever use PUBLIC example data in them.
Product Names Change Faster Than This Lesson
Google’s assistant was called Bard until February
2024, when it was renamed Gemini;
bard.google.com now redirects to
gemini.google.com. Similarly, chat.openai.com
now redirects to chatgpt.com.
Expect names, tiers and model numbers to keep moving. Nothing in this workshop depends on a particular product — the rules you will learn are about the data you are handling, which is exactly why they outlast the tools.
During the Workshop
Tools We’ll Use
Workshop Structure
This is primarily a concepts and policy workshop, not a coding workshop.
Part 1: Understanding AI Tools (Classroom)
- Landscape of AI tools available
- How AI systems work (high-level)
- Cloud vs. local AI tradeoffs
Part 2: Data Governance (Classroom)
- Pomona’s data classification system
- Regulatory requirements (FERPA, HIPAA, export control)
- How to classify YOUR data
Key Concepts We’ll Cover
1. Data Classification (Core Skill)
You’ll learn to categorize your research data:
- PUBLIC: Safe with any AI tool
- PROPRIETARY: Local AI only or with written permission
- RESTRICTED: Local AI only + encryption
2. Tool Selection (Core Skill)
Given data classification, choose appropriate tool:
- ChatGPT/Claude/Gemini? (Only for PUBLIC)
- A local open-weight model on Sagehen? (For PROPRIETARY and RESTRICTED)
Before the Workshop: Self-Assessment
Optional: Rate your familiarity with these concepts:
AI Tools:
☐ Never used ChatGPT/Claude
☐ Used once or twice
☐ Regular user
☐ Power user
Data Privacy:
☐ Not familiar with FERPA/HIPAA
☐ Heard of them, unclear on details
☐ Familiar with basics
☐ Work with regulated data regularly
Research Background:
☐ First year graduate student
☐ Mid-career graduate student
☐ Faculty/postdoc
☐ Undergraduate researcher
Your AI Use Case:
☐ Haven't thought about using AI
☐ Considering using AI for research
☐ Already using AI
☐ Not sure if I should be using AI
This helps us pitch at the right level!
Getting Help Before the Workshop
Questions About:
- Sagehen access: its-hpc@pomona.edu
- Workshop content: Ask instructor before session
- Pomona AI policy: Contact your department chair or OVPR
Resources to Review (Optional)
- Use of AI Tools with Pomona College Data (campus login required; covered in Episode 3)
- FERPA Overview: https://www2.ed.gov/policy/gen/guid/fpco/ferpa/
- HIPAA Basics: https://www.hhs.gov/hipaa/
Accessibility
This workshop is designed to be inclusive:
- Visual aids and text slides
- Spoken descriptions of code examples
- Discussions don’t require technical background
- Hands-on activities are optional
Let instructors know if you need accommodations!
Contact for Setup Issues
Before the workshop, if you encounter any issues:
- Sagehen access problems: its-hpc@pomona.edu
- Browser/tech issues: Your local IT support
- Workshop-specific: Email instructor
Post-Workshop Resources
After the workshop, continue learning:
- Use of AI Tools with Pomona College Data (full text)
- Local model setup guide
- Compliance checklists
- Case studies and examples
These will be provided at the end of the workshop.