How will AI models that can generate text, images, audio, video and code change what students need to learn and the instructional processes that guide their learning? Do we need generative models designed specifically for educational purposes?

Speakers.
Dora Demszky: Assistant Professor of Education Data Science, Stanford University.
Noah Goodman: Associate Professor of Psychology, of Computer Science and by courtesy of Linguistics, Stanford University.
Percy Liang: Director, Center for Research on Foundation Models; Associate Professor of Computer Science, Stanford University.
Rob Reich: Professor of Political Science; Faculty Director, McCoy Family Center for Ethics in Society; Marc and Laura Andreessen Faculty Co-Director, Stanford Center on Philanthropy and Civil Society; Associate Director, Stanford HAI

The AI+Education Summit: AI in the Service of Teaching and Learning took place on Feb. 15, 2023. Learn about upcoming events here: https://hai.stanford.edu/events

No detectors “reliably distinguish between AI-generated and human-generated content.”

In a section of the FAQ titled “Do AI detectors work?”, OpenAI writes, “In short, no. While some (including OpenAI) have released tools that purport to detect AI-generated content, none of these have proven to reliably distinguish between AI-generated and… More.

Last week, OpenAI published tips for educators in a promotional blog post that shows how some teachers are using ChatGPT as an educational aid, along with suggested prompts to get started. In a related FAQ, they also officially admit what we already know: AI writing detectors don’t work, despite frequently being used to punish students with false positives.

In July, we covered in depth why AI writing detectors such as GPTZero don’t work, with experts calling them mostly snake oil. These detectors often yield false positives due to relying on unproven detection metrics. Ultimately, there is nothing special about AI-written text that always distinguishes it from human-written, and detectors can be defeated by rephrasing. That same month, OpenAI discontinued its AI Classifier, which was an experimental tool designed to detect AI-written text. It had an abysmal 26 percent accuracy rate.

CAMBRIDGE, MA —The Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard University announces the appointment of Dr. Kanaka Rajan, the first faculty member hired within the recently launched Kempner Institute. As a founding faculty member at the Kempner, Dr. Rajan will serve as an institute investigator. She will also have a dual appointment, serving as a member of the faculty in the Department of Neurobiology at Harvard Medical School.

Working jointly with the HMS Department of Neurobiology and the Kempner Institute, Dr. Rajan will support the intersecting research, scientific, and educational missions of both communities. Dr. Rajan starts in September 2023.

“We are thrilled to have Dr. Rajan join the Kempner, where she will play a key role in helping to shape and advance the institute’s research program,” said Kempner Co-Director Bernardo Sabatini. “She is a true leader in the field, using innovative techniques to tackle big, difficult questions, and expanding the possibilities for how we use artificial intelligence and machine learning to understand the enduring mysteries of the brain.”