Composing with AI

Readings

Before students can get something out of LLMs, they really need to understand how these systems work, how critics understand them, and where they come from. Our reading list had iconic hits and some personal favorites: Stochastic Parrots, Blurry Jpeg (everyone needs a good image to make the technical and unexplainable concrete), Kirschenbaum’s Textpocalpyse, as well as a few of my favorites, readings from Joseph Weizenbaum about the first chatbot, ELIZA, and Alan Turing, who instigated the quest for an intelligent seeming bot.

The magic of the “Chat” part of ChatGPT is that it takes advantage of the ELIZA effect, which names a human tendency to imagine or assign to non-human things sentience. The typical example would be the person who is cursing at their car. But a better example might be the person who is growing more and more frustrated while trying to get their Amazon Alexa or Apple Siri to understand their request. Before they know it, they are abusing Alexa (Fan 2022) and telling it to “shut up” as though it had the ability to understand the emotional force behind that phrase.

At the heart of this misapprehension, treading the bot is a person, is a fundamental misunderstanding of how LLMs operate. While the code is hidden and the precise functioning of the LLM obscured, the general notion of a bot producing content based on a predictive model is fairly straightforward. When students read “Stochastic parrots,” they develop a clearer expectation for the results of their prompts.