University IT
Choosing AI Tools Wisely: A Practical Evaluation Framework
Important note: This training may demonstrate AI tools that are not approved for use with Stanford data. Inclusion in this session does not imply institutional approval. Participants should refrain from entering Stanford data into unapproved tools. An up-to-date list of approved and reviewed tools is available on the GenAI Evaluation Matrix page.
| Code | Date | Delivery | Cost |
|---|---|---|---|
| ITS-1016 |
|
Live Online : 1 session | $300 |
Before each live online session, Tech Training will provide a Zoom link for live online classes, along with any required class materials.
Explore a structured approach to evaluating AI tools for your work. Practice applying criteria that account for capability, privacy, cost, and fit so you can make more confident, informed decisions about the AI tools you use.
Lionel Levine
Dr. Lionel Levine is an independent educator and researcher specializing in the intersection of computer science, data analytics, and healthcare. Learn more about Lionel Levine
- Program Description
In a landscape crowded with AI tools, knowing which ones to trust, adopt, or set aside is a skill in itself. This three-hour session offers a practical framework for evaluating AI tools with intention and rigor. Learners will work through real-world scenarios to assess tools across multiple dimensions, including functionality, data privacy, organizational fit, and cost considerations. Whether you are exploring tools for the first time or revisiting choices already made, this session gives you a repeatable process you can apply well beyond the classroom.
- Learning Objectives
Learners will have the opportunity to:
- Explore a structured framework for evaluating AI tools across key criteria such as capability, privacy, compliance, and cost
- Practice applying evaluation criteria to AI tools relevant to your work context
- Work with comparison approaches that surface trade-offs between competing tools
- Experiment with prompting and testing strategies to assess tool performance before committing to adoption
- Develop a personal or team-level evaluation checklist you can use in future tool decisions- Topic Outline
- The AI tool landscape: categories, capabilities, and common use cases
- Key evaluation dimensions: functionality, data handling, access and licensing, and organizational fit
- Privacy and compliance considerations for AI tools at Stanford
- Hands-on tool comparison exercises using a structured rubric
- Testing strategies: how to put a tool through its paces before adopting it
- Building a reusable evaluation checklist for individual or team use
- Credits
- 3 Professional Development Units (PDU)
- 0.3 Continuing Education Units (CEU
- 3 Professional Development Hours (PDH)
- Stanford Technology Training Program Certificate of Completion Awarded
Custom training workshops are available for this program
Technology training sessions structured around individual or group learning objectives. Learn more about custom training
Special Group Rates
For groups of 5 or more within the same team or department, special rates are available. Please contact techtraining@stanford.edu for more details.
University IT Technology Training sessions are available to a wide range of participants, including Stanford University staff, faculty, students, and employees of Stanford Hospitals & Clinics, such as Stanford Health Care, Stanford Health Care Tri-Valley, Stanford Medicine Partners, and Stanford Medicine Children's Health.
Additionally, some of these programs are open to interested individuals not affiliated with Stanford, allowing for broader community engagement and learning opportunities.
