| ▲ | reagle 4 hours ago | |
- 2. Guiding Principles - 2.1. Be humble - 2.2. Be bold - 2.3. Put humanity front and center - 2.4. Lean into learning - 2.5. Teach with intentionality - 2.6. No one size fits all - 2.7. Augmentation not automation - 2.8. Think beyond the classroom and the campus - 3. Recommendations - 3.1. Adapt educational processes for an AI-aware world - 3.1.1. Revisit course goals - 3.1.2. Ensure durable learning through new course policies, structures, and forms of assessment - 3.1.3. Emphasize experiential and project-based learning - 3.1.4. Build structured in-person social learning into subjects - 3.1.5. Preserve and expand out-of-class research and career experiences - 3.1.6. Reconsider grades and incentives - 3.1.7. Expand in-person spaces for labs and in-person evaluation - 3.1.8. Provide AI use policies, with justification - 3.1.9. Exercise caution with AI detectors and online exam platforms - 3.1.10. Support responsible experimentation in the curriculum - 3.2. Center people, community, and the residential experience - 3.2.1. Define and communicate the value of residential education - 3.2.2. Strengthen social connection and personal wellbeing - 3.2.3. Encourage instructor disclosure around their own AI use - 3.2.4. Teach effective, responsible, and ethical use of AI - 3.2.5. Recognize and mitigate negative impacts of AI - 3.2.6. Acknowledge AI use in theses and other research work - 3.3. Build processes, teams, and tools for continuous reflection, iteration, and improvement - 3.3.1. Establish an ongoing AI and education committee - 3.3.2. Create school/college- or department-level AI Leads - 3.3.3. Fund AI Fellows and an AI Implementation Team - 3.3.4. Create an AI Pilot Fund - 3.3.5. Provide ongoing training and instructor support - 3.3.6. Develop metrics - 3.3.7. Ensure equitable technology access - 3.3.8. Protect sensitive data and preserve model choice - 3.3.9. Establish privacy, logging, and auditing policies - 3.3.10. Monitor AI costs and environmental impact - 4. Conclusion | ||