- 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

MIT's Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training