Generative AI and Information Literacy

How does Generative AI relate to Information Literacy? 

This research guide provides an overview of how Generative AI tools and processes are changing our global information ecosystem. It addresses key issues such as misinformation, bias, and ethical challenges for the purpose of furthering inquiry into information literacy in light of these new technologies. 

We foreground these questions in this guide:

1. What questions should we be asking about Gen-AI tools and human information and learning?
2. What do we give up or cede when we use AI tools?

Common terms used in this guide:

Artificial Intelligence (AI): "The capacity of computers or other machines to exhibit or simulate intelligent behavior." (Oxford English Dictionary, n.d.)

Generative AI (Gen-AI): A type of AI technology that generates content such as text, images, audio, and video. Also sometimes referred to as a generator.

Large Language Model (LLM): A complex model trained on vast amounts of data that generates language that resembles human-generated language. Open AI's GPT series (powering ZotGPT, Microsoft CoPilot, and PapyrusAI), Google's Gemini, and Meta's LLaMA are examples of LLMs.

Chatbot: A computer program that uses an LLM to simulate a conversation with human users, typically through typed text in a software application.

Algorithm: A set of instructions or rules for performing a computation. Developers typically design algorithms used in AI to progressively iterate themselves, which we can consider a form of machine learning.

Training: The process of supplying algorithms with large data sets, and then "teaching" them to develop progressively sophisticated outputs for their intended purpose.

Definitions are adapted from the "Defining AI and Chatbots" page of the Artificial Intelligence Teaching Guide, Stanford Teaching Commons

The following 5-minute video provides an overview of what LLMs are and how they work in Generative AI chatbots like Google Bard (now Gemini), ChatGPT, and ZotGPT. 

How LLMs and chatbots work

Nield, David. “How ChatGPT and Other LLMs Work—and Where They Could Go Next.” Wired, April 30, 2023. https://www.wired.com/story/how-chatgpt-works-large-language-model/.

Roose, Kevin. “How Does ChatGPT Really Work?” The New York Times, March 28, 2023. https://www.nytimes.com/2023/03/28/technology/ai-chatbots-chatgpt-bing-bard-llm.html.

Stöffelbauer, Andreas. “How Large Language Models Work.” Data Science at Microsoft, October 24, 2023. https://medium.com/data-science-at-microsoft/how-large-language-models-work-91c362f5b78f.

Wolfram, Stephen. “What Is ChatGPT Doing … and Why Does It Work?” Stephen Wolfram Writings, February 14, 2023. https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/.

How are LLMs trained?

Dodge, Jesse, Maarten Sap, Ana Marasović, William Agnew, Gabriel Ilharco, Dirk Groeneveld and Matt Gardner. “Documenting the English Colossal Clean Crawled Corpus.” ArXiv abs/2104.08758 (2021): n. pag.

Schaul, Kevin, Szu Yu Chen, and Nitasha Tiku. “Inside the Secret List of Websites That Make AI like ChatGPT Sound Smart.” Washington Post, April 19, 2023. https://www.washingtonpost.com/technology/interactive/2023/ai-chatbot-learning/.