I have the honor of sharing some ideas about teaching, learning, and AI with New Mexican Educators Rising members at the 2024 Conference. Here are some concepts and resources that might be useful. Ideas for using LLMs in Learning Ideas for using LLMS in Teaching Additional Resources Videos Santa Fe Institute: The Future of Artificial […]
Access resources here! Bad Audio of All Presentations: Bias in LLMs: It’s Not What You Think Full Paper: Warr, Melissa and Oster, Nicole Jakubczyk and Isaac, Roger, Implicit Bias in Large Language Models: Experimental Proof and Implications for Education (November 6, 2023). Available at SSRN: https://ssrn.com/abstract=4625078 or http://dx.doi.org/10.2139/ssrn.4625078 Beyond Cheating: Using LLMs in Teaching and Learning Higher Ed […]
Image (including embedded bias) created by ChatGPT 4 and Dall-E 3. Last week I wrote a post about the bias in ChatGPT–specifically how it adjusts writing scores in response to student descriptions. I illustrated how ChatGPT 3.5 scored a writing passage higher when it was told the imaginary writer preferred classical music, and lower for […]
Sometimes my attempts to understand ChatGPT go down strange paths. While talking with a friend about bias in AI yesterday (yes, this occurs frequently in my life), college rivalries came up. And what could be cooler than having ChatGPT confirm my firm belief that Brigham Young University is superior to the University of Utah? In […]
Note: Cover image (including embedded racial bias) from Dall-E 3 via ChatGPT4.0 I’ve been doing some random tests with ChatGPT and other large-language models (LLMs) (some perhaps a bit more meaningful than last week’s Benford’s Law…). Today’s exploration: If I tell ChatGPT that something is written by a student who likes rap music–vs classical music–will […]