This course requires us to be present for each other. This doesn’t mean speaking during seminar. You really don’t have to if you don’t feel like it. What’s the point of requiring you to? That said, it is important that we are there for each other, helping each other out, doing our part, asking questions when we don’t understand something, answering them when we do. For the duration of the semester we are a collective, the team we have—Yankees or Bad News Bears, we are what we got.
Working in pairs, you will lead discussion once during the semester. To prepare for the section you choose, you are encouraged to seek and prepare additional material that compliments that week’s readings. You are welcome to consult me on possible avenues of ancillary research.
Breaking Down a Text or Corpus Analysis Paper
On the fourth week of class you will annotate one article from a digital humanities journal working in pairs. Your job is to highlight concepts and words you don’t understand, and to try to help each other fill those gaps.
Before Spring break we will look at a dozen of pain-point keywords that surfaced from the annotation exercise and in class discussions. The exercise is take-home, and we will discuss the results in class after Spring Break.
(Editing the) Final Paper
The final paper for this class may be the strangest final paper you have submitted for a grade in your whole life. You won’t be writing this one alone. You won’t be writing it with another person either, not directly in any case. You also won’t even be writing the first draft. No, AI will do that. The way this works is simple: pick a topic related to your current research. Using GPT3, or GPT4 (if it’s out already) you will have the machine write the first pass. Your job is to correct and edit the work to bring it up to your standards. You will submit the original AI draft, and your final version.
Find a Useful Method
To earn the bonus round points—an additional 20% that all but guarantees you will receive the highest honors in this class—you must convince me of a use for AI text or image generation in Humanities research. Let me break that challenge down for you:
- “You must convince me”: Convincing yourself or each other won’t be enough. I lean skeptic, but I always welcome a good argument.
- “AI text or image generation”: Right now this usually evokes something like ChatGPT or Midway at the consumer level. I want you to go beyond these consumer tools and look at the underlying machine learning, labor structure and language models themselves. You are welcome to imagine that you command some resources—smaller than Google, of course.
- “in Humanities research”: the method has to potentially contribute to the research agenda of an existing researcher in the Humanities at large.