Augmentation & AI

In-Class Agenda

• Discuss assigned readings and explore demo of LLMs for data work (links below).
• Groups present their Computing Cultural Data Assignment.

Assigned Materials

• Underwood, Ted. “Can Language Models Predict the next Twist in a Story?” The Stone and the Shell (blog), January 5, 2024. https://tedunderwood.com/2024/01/05/can-language-models-predict-the-next-twist-in-a-story/.
• Samora, Russell, and Michelle Pera-McGhee. “We Had an AI Attempt to Make a Data-Driven Story like We Do at The Pudding.” The Pudding, July 2024. https://pudding.cool/2024/07/ai.

Additional Materials

• Underwood, Ted. “Machine Learning and Human Perspective.” PMLA https://www.ideals.illinois.edu/handle/2142/109140.
• McGrath, Laura B. “Charisma (Embodiment): a Response to Tess McNulty.” Post45 (2019) https://post45.org/2019/05/charisma-embodiment-a-response-to-tess-mcnulty/.
• Lee, Benjamin Charles Germain. “The ‘Collections as ML Data’ Checklist for Machine Learning and Cultural Heritage.” Journal of the Association for Information Science and Technology (2023). https://doi.org/10.1002/asi.24765.
• Bender, Emily M., et al. “On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?” Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT ‘21), 2021, 610–623. https://doi.org/10.1145/3442188.3445922.

Additional links

• AI for Humanists Project https://aiforhumanists.com/
• Copied notebook from AI for Humanists with our novels data available here
• Additional local notebooks using Classification Models & LLMs. Be sure to install the necessary Python libraries into your virtual environment as well.

Assignments

Individual

Group

• Complete group assignment on Computing Cultural Data.