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As the ‘Clearinghouses’ section below demonstrates, there is a large and growing number of resources available on the web for AI in higher education. The list below has been curated for relevance to 91Թand its context of an international liberal arts education. This list is updated continuously, so please send any suggestions to aiataup.edu.

Intros & background

How generative AI works
  • (Andrej Karpathy) ()
Overviews of the generative AI landscape
  • in higher ed
    • (Hanover Research & IHE)
  • in the broader environment
    • (Imagining the Digital Future Center - Elon University)
Practical overviews for AI in teaching/learning
  • (Anna Mills)
Generative AI tutorials for faculty

(metaLAB (at) Harvard)

Course planning and teaching

Syllabus statements and course design
  • Crowd-sourced list of (Lance Eaton)
  • (Lance Cummings)
  • (Oregon State University)
  • (support for different stages/aspects in course/syllabus design)
  • (Carroll College) -- based on key principles: Clarify, Communicate, Uphold, Engage
  • (U Wisconsin)
  • (Inside Higher Ed)
For faculty teaching writing

(MLA-CCCC Joint Task Force on Writing and AI)

Discussions with students about AI
  • Academic integrity: objects for discussion with colleagues & students
    • : "Detection tools for AI-generated text do fail, they are neither accurate nor reliable (all scored below 80% of accuracy and only 5 over 70%)."
Assignments and teaching modules to reuse/adapt/reflect upon
  • (metaLAB (at) Harvard)
  • (Ethan R. Mollick, Lilach Mollick)
For faculty teaching writing

(MLA-CCCC Joint Task Force on Writing and AI)

Technical guidance for using AI in teaching

Clearinghouses of information/resources

  • (Lance Eaton)
  • (Anna Mills) – see in particular
  • Policies (see “Policy development” below)
AI in libraries
  • (AI projects, data sets, resources for libraries, archives and museums)
Tools
  • (Dan Fitzpatrick)
  • (Anthropic/Claude)
Products & licensing

Discussion & keeping up

Discussion with global peers
  • (requires EDUCAUSE account – 91Թfaculty & staff can create accounts)
  • AI & Libraries
    • (meeting notes and recordings)
Blogs & newsletters
  • (Lance Eaton)
  • (Ethan Mollick)
  • newsletter (Amherst College)
  • (Jeremy Caplan)
Perspectives (could be a focus for class discussion)

Developing higher ed AI initiatives

We’ve found the resources listed here useful in shaping the AI@91Թinitiative. 91Թcolleagues may find these useful as well in thinking about how they can contribute to the initiative or its goals.

Developing campus-level strategy and initiatives
  • Broad principles for AI in higher ed
    • (UN lnternet Governance Forum, Kyoto, Oct 2023)
    • (Russel Group of leading UK universities)
  • Organizational assessment
    • (Joe Sabado)
  • Developing a strategy
    • (MIT strategy guide for addressing AI at higher ed institutions)
Policy development
  • Governmental policy frameworks & recommendations
    • Europe
      • EU AI Act
    • France
    • United States
  • Higher ed frameworks & recommendations for policy development
    • – based on this study:
  • Examples of existing policies
    • Lists of existing policies
      • (Joe Sabado)
  • Specific examples of note
    • (metaLAB (at) Harvard)
    • (College Unbound / Lance Eaton)
    • Policies and syllabus guidelines at AMICAL Consortium institutions
  • Templates for developing your own policy
    • (Joe Sabado)
AI literacy frameworks
  • (Barnard College’s scaled framework for moving up a scale: Understand → Use → Analyze → Create)
AUP-relevant examples of campus-level initiatives
  • Liberal arts colleges
    • Amherst College:
    • Davidson College:
  • Larger universities
    • (University of Toronto)
  • AMICAL Consortium institutions
    • (recording and links to resources mentioned)
    • (Forman Christian College)