Arizona State University continues to push boundaries. I’m excited to share two recent developments that intersect with my collaborative work at ASU over the past few years. These initiatives showcase our institution’s commitment to leveraging AI responsibly while prioritizing student success and ethical considerations.

The first is the AI Journey report, which “highlights ASU’s commitment to using AI to enhance student success, drive research breakthroughs and prepare a future-ready workforce.” My work (and that of our AI in Education, Learning Futures Collaborative) is mentioned, as is the research on bias in LLMs that Melissa, Nicole, and I have engaged in. This report, of course, covers much much more, since it seeks to capture all of the amazing things that are happening at ASU, in this space. You can learn more about this story at Shaping tomorrow: ASU launches a comprehensive review of our AI journey (thus far) or go directly to the report.

Also released last week was the HigherEd Language Model Evaluation Framework, a new approach for assessing AI tools in academia. Led by the AI Acceleration team, this framework combines automated testing via an Ethical AI Engine with human evaluation, aiming to set a new benchmark for ethical AI. As a collaborator, I contributed to discussions on how this dual approach could ensure AI tools align with institutional values and ethical standards in higher education. I’m glad I could play a small part in this important initiative. Huge shoutout to (Stella) Wenxing Liu, Varun Shourie, & Ishrat Ahmed for leading this effort.