Looking Back at 2024

Clarote & AI4Media / Better Images of AI / User/Chimera / CC-BY 4.0

Thank you all for the kindness, support, and generosity you’ve shown me this year. I published 45 essays in 2024 and thousands of you read and shared them. For that, I am truly humbled. My work life changed rapidly this year. In addition to my teaching, I also took on the additional role as an assistant director of academic innovation at the University of Mississippi. Instead of being a cheerleader for AI in education, I’ve used the opportunity to raise critical questions about what AI means for learning.

This work fed into my other job, directing the AI Institute for Teachers. During the past year, we’ve held an across-campus institute, half-day workshops, and too many AI discussions, webinars, and panels to count. We’ve also taken the training on the road to multiple K-12 campuses, offering faculty a chance to explore what critical AI literacy means to their teaching and students’ learning.

We all need to focus on engaging AI in sustainable ways. I think that should be a goal next year. To this end, I’m exploring how to help faculty navigate the tidal wave of AI announcements while maintaining our capacity and not burning out or disengaging.

Most Read: The Beyond ChatGPT Series

Thanks to the generous support from subscribers, I launched a series this summer exploring the implications of generative AI beyond text generation. This series helped establish awareness of AI reading assistants and its complicated potential to support certain students, while highlighting AI’s frightening ability to turn any document into a series of bullet-pointed summaries.

The Beyond ChatGPT Series

• Reading: No One is Talking About AI’s Impact on Reading

• Note Taking: AI’s Promise to Pay Attention for You

• Feedback: What Does Automating Feedback Mean for Learning?

• Tutoring: Why Are We In a Rush to Replace Teachers with AI?

• Research: What’s At Stake When We Automate Research Skills

• AI Detection: The Price of Automating Ethics

• Instructional Design: AI Instructional Design Must Be More Than a Time Saver

Writing Elsewhere

I started an advice column in the fall for the Chronicle focused on practical strategies for confronting AI in education. It’s been wonderful to connect to a broader audience outside of Substack and social media.

• When AI Does the Reading for Students

• Make AI Part of the Assignment

• Why We Should Normalize Open Disclosure of AI Use

I’m also co-editing several special issues of Thresholds in Education about generative AI and education. We’ve received dozens of essays and reports from educators across the globe who are navigating this new reality of AI tools within our classroom.

What Excites Me and Frustrates Me About AI in Education

More and more people are becoming aware of AI’s potential impact on student learning. How students use AI tools is complicated. Many students are still trying to figure out how to best use or not to use AI and turning to faculty for advice. Many faculty may not realize it, but having discussions with students about generative AI can deeply shape how students view their agency and voice with this technology. Those discussions are what hold the most promise for me because they come at a critical moment in our student’s development. We can persuade and mold how our students view generative AI in ways that are meaningful. That doesn’t happen as a one-off conversation or through boilerplate policy. These conversations must be a continuum.

What frustrates me the most about generative AI developers and the legions of those who build countless wrapper apps atop APIs, is they do so on the onus of releasing AI as a public experiment. They admit they don’t know the repercussions and say they must have feedback as they develop these advanced systems.

This reckless strategy hasn’t played out well in education. Mass cheating, deepfake harassment, and offloading learning have consequences we can barely comprehend. But since these consequences don’t lead to doomsday scenarios where robots run amok, very few critics within the AI development space want to focus on so-called ‘near-term harms’ presented by current generative AI systems.

However, one past critic of AI and computers in general was Joseph Weizenbaum. He pioneered some of the first chatbots or ‘chatterbots’ in the 1960s with projects like ELIZA. He was not a fan of how quickly users anthropomorphized their interactions with a machine, often giving it human traits. In 1985, he sat down for an interview with MIT about the place of computers in education. What Weizenbaum said then of computer-aided education echoes today: “We ought not to use entire generations of schoolchildren as experimental subjects.”

Thank You

Thank you for your time, your energy, and your focus. We get so few moments where we get to think deeply about our world and I am immensely grateful to all who’ve subscribed and read my words. I’m committed to keeping this newsletter free, but it’s hard to overstate how important paid subscribers have been to support this work. I would not have been able to tackle the Beyond ChatGPT series without such support. If you’ve valued what I’ve written and wish to support the future of this work, then I hope you will consider subscribing.

If you are interested in finding out more about the AI training I offer to K-12 and higher education, speaking engagements, or just want to say hello, please drop me a line at my personal website.