AI Resources

TEACHING WITH AI HANDOUTS

  • Here is a massive spreadsheet by Sarah Wood that lists most of the AI models and API tools and scores them for a variety of privacy and environmental issues. It scores them for appropriate use for elementary, middle and high school, but very useful for higher education too.
  • European Data Protection Board Report (April 2025) on AI Privacy Risks & Mitigations Large Language Models (LLMs)
  • Incogni Report: Gen AI and LLM Data Privacy Ranking 2025 (June 2025)
    • Le Chat by Mistral AI is the least privacy-invasive platform, with ChatGPT and Grok following closely behind.
    • Platforms developed by the biggest tech companies turned out to be the most privacy invasive, with Meta AI (Meta) being the worst, followed by Gemini (Google) and Copilot (Microsoft). DeepSeek was also indicated as one of the most privacy invasive.
    • GeminiDeepSeekPi AI, and Meta AI don’t seem to allow users to opt out of having prompts used to train the models.
    • ChatGPT turned out to be the most transparent about whether prompts will be used for model training and had a clear privacy policy. 
    • All investigated models collect users’ data from “publicly accessible sources, ” which could include personal information.
  • Americans for Responsible Innovation AI Transparency Rankings
  • Jon Ippolito’s App “What Uses More” allows you to compare the environmental footprint of digital tasks.
  • From the Penn State Institute of Energy and the Environment: Why AI uses so much energy—and what we can do about it
  • Energy and AI from the International Energy Agency (April 2025)
  • MIT Technology Report (May 2025): We did the math on AI’s energy footprint. Here’s the story you haven’t heard: The emissions from individual AI text, image, and video queries seem small—until you add up what the industry isn’t tracking and consider where it’s heading next.
  • Adam Masley Response to MIT Report.
  • Resources and AI policies in your course Stanford syllabus sample language
  • Menus, not traffic lights: A different way to think about AI and assessments by Danny Liu.
  • A great set of statements, sample syllabi statements and more from Ohio University CTLA
  • Sample syllabus AI policy statements from Penn State
  • Lance Eaton’s huge list of AI policies or the sortable spreadsheet.
  • Sample syllabus policy statements from Northern Illinois University CITL
  • Institutional Policies & Guidance collected by Joe Sabado.
  • If you have any sort of institutional policy or framework for AI, you could create a customized bot for faculty on your campus to create a syllabus policy specifically for their course but aligned with your campus policy. You could write this yourself, but try this:
  • Write code for an interactive interface that will produce a Generative AI syllabus policy for a college course that is both customized for individual faculty needs in that course and aligned with the university or college framework or policy. [Attach or provide a link to the campus policy or framework.] Start by asking faculty a few question about how they want to approach AI usage in their course, and offer the option of uploading a syllabus or learning goals. Offer some options based on the university framework and then provide a draft syllabus for the faculty member.