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# System prepended metadata

title: mk planning doc

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# mk planning doc
[aiLab-ay23-24-round-up](/Z0YNX_9nRUqKJfgkf7TTUw)

## outline 

- thing of this as dispatches from the field.... less presenting as experts on AI, and more as people who tried or witnessed a few unusual experiments with AI in the classroom and want to present these results to spark some thinking about what might come next.
- the systematic support approach has been... while we are concerned with a number of small innovations
- some reports on our experience with AI over what we'll call
    - year 0 (when chatGPT was released and we were helping faculty survive)
    - year 1 (where we are right now, where we are supporting all faculty in ways we'll outline while preparing for the future, which we'll call)
    - year 2 and beyond 
- but first
    - what is the Bok?
    - what is the LL?
- as the center for teaching and learning, we are interested in BOTH
    - teacher use of AI
    - student use of AI
    - worker use of AI
    - and the LL for reasons we'll explain, it's often difficult to draw strict lines between these, but, basically....
        - teacher's are experts, but perhaps don't have time because they are in a one to many relationship with their students
        - students are not yet experts, and we value their learning from their work more than the products of that work
        - workers have varying degrees of expertise, and we pay them for their work (and hence value the products of that work)
- so over this year the Bok Center has a whole has provided
    - training and resources
        - training on the sandbox
        - help with syllabus language
        - "chatGPT-proofing" assignments (where possible)
        - everyone should check out our website for more
- in the LL, we have worked with a small number of courses hoping to do something more experimental with AI
    - a TDM course where students, instead of writing dialogue, created personas as slackbots and then set the bots chatting in a Slack channel [NEED STILLS]
    - A Slavic course on ballet where students used Computer Vision to identify the poses of famous ballets (or of themselves) in order to use that data to constrain the output of the AI Image Generation tool, Stable Diffusion [NEED STILLS]
    - A upper level seminar for Art Film and Visual Studies students working on Senior Theses, who are submitting their work in progress to OpenAI's Vision API in google colabs to spark their imaginations with AI feedback [NEED STILLS IF THEY EXIST]
    - an EMR (ethnicity, migration and rights) course on Race and AI where students interacted with various APIs in google colab (or the major developer sandboxes) to see a little more of what happens "under the hood"--and to start creating recursive operations [NEED STILLS on the recursive colab]
    - a complit lit course where students use AI to generate poetry, and we showed them how to create a slack-bot ensemble to handle different personas in the literary production circuit 
    - a course on entrepreneurship where students got a half hour long zoom meeting with Hunt Lambert, former DCE dean and entrepreneur himself, where we created a feedback bot based on the transcriptions of his responses [insert ]
    - internal slackbots for our studio like
        - log-every-minute-bot
        - log-every-minute-in-french-bot
        - get alt-text for images airtable script
        - summarize channel
        - annotate messages in threads (critics, translators, jargon-explainers)
        - get-and-describe-the-loudest-2-seconds-of-this-event-with-gif-output
    - and most interestingly, A comparative Literature course where...
    - 

others?


takeaways
- where is teaching and learning headed?
- where is knowledge-work headed?
- where is coding/tech-literacy headed?
    - rise of colab
    - shift in percentage of student-workers capable of contributing