About 2 years ago, I wrote about trying to keep up with the tsunami of AI news and content and the fact is, it’s only gotten harder. This post is a slight update on that post.
I say slight because I still think a lot of what’s there is still solid and worth doing. But, if I’m being honest, it’s even hard for me to keep up with all the content produced across those publications. We’ve moved from a desert of insight, guidance, and provocation to an abundance. In truth, that creates as many problems as we must navigate the paradox of choice—there are so many things to choose from, it’s hard to decide which we choose.
You’ll notice that there are not podcasts as part of the content. Unfortunately, I’m not much of…
About 2 years ago, I wrote about trying to keep up with the tsunami of AI news and content and the fact is, it’s only gotten harder. This post is a slight update on that post.
I say slight because I still think a lot of what’s there is still solid and worth doing. But, if I’m being honest, it’s even hard for me to keep up with all the content produced across those publications. We’ve moved from a desert of insight, guidance, and provocation to an abundance. In truth, that creates as many problems as we must navigate the paradox of choice—there are so many things to choose from, it’s hard to decide which we choose.
You’ll notice that there are not podcasts as part of the content. Unfortunately, I’m not much of a podcast listener (maybe 1-2 episodes a month or a deep dive on occasion). I’m often listening to audiobooks (surprise, I know!). If you want a sense of recommendations of audiobooks on the topic of AI or see what I’ve read most recently in this vein, then check out my Goodreads Bookshelf on AI (or the one on education, teaching, and learning).
Here are a handful of reads that I know I’m always trying to read as soon as they come out. That’s not to say I only read this; this is just the shortlist. There are too many to highlight otherwise, and it would diminish the idea of not overloading the reader.
The Absent-Minded Professor (Weekly). I really enjoy Josh Brake’s thoughts on AI in education as they balance everyday practice, institutional realities, and critical theory. His writing offers examples and critiques that I find helpful. 1.
AI and Academia (Bi-weekly to monthly). If you’re in higher education, really in any capacity, you need to be reading Bryan Alexander. He has several different publications, but in this instance, his Substack on AI and Education is worth checking out. He regularly offers a temperature check about the field of education and how they’re sense-making of AI. 1.
AI In Learning (Monthly). Full disclosure, I’m a co-editor for this newsletter from Northeastern and also, I *also *get excited to read it each month. In particular, the One Thing to Try series highlights a specific faculty member (or two) and briefly unpacks a way they are using GenAI in their courses with students. 1.
Education Disrupted (1-2 posts a week). Stefan Bauschard tackles the concrete challenges and opportunities AI presents for schools and educators, urging thoughtful instructional redesign rather than surface-level adoption. His work blends evidence-based critique with actionable insight about preparing students for an AI future. 1.
Reflecting Allowed (Bi-weekly to monthly). You just need to follow Maha Bali if you’re in higher education and teaching spaces. Her blog (Reflecting Allowed) is about her teaching with regularly mentioning teaching and learning, along with how we make spaces of learning and community more engaging and welcoming. 1.
Marc Watkins (Bi-weekly). I appreciate Marc Watkins’s work for its clear, critical exploration of how generative AI is reshaping education. He feels grounded in his examination of real implications for teaching, assessment, and institutional responses. 1.
The End(s) of Argument (Weekly). Mike Caufield’s experiments and reflectons with AI and its intersection with information literacy, doesn’t break my brain but helps me think differently about how we consider AI’s role going forward. 1.
The Important Work (Bi-weekly). Run by Jane Rosenzweig, this is an ongoing collection of essays and thoughts from different authors each week who are taking some time to share their own sense-making through the lens of AI in the teaching space. 1.
Second Breakfast (Weekly). Audrey Watters delives a weekly dose of hard reality about what AI (and ed-tech in general) cannot do, no matter how many times they promise us otherwise. 1.
Wondertools (Weekly). Jerry Caplan doesn’t cover solely AI content, but it’s a good amount. I find his unpacking of AI or other tools is always a good primer for me and gets me thinking about teaching and learning applications.
With video channels, I’m often looking for people who are unpacking some of the newest features and aspects of GenAI, and double points if doing so in an educational context. But I find videos are the best place for me to absorb and see the changes that are coming.
Enovair 1.
Eric Curtis 1.
Mystery AI Hype Theater 3000 1.
Sovorel 1.
The Good Robot (not strictly AI but consistently good) 1.
Here are some voices in the social media spaces as well as spaces such as listservs that have done me well.
AI Google Group: A spinoff from the POD Network, this is a fantastic resource for faculty developers, instructional designers, and even faculty to share, learn, and ask for insights, help, etc.
AI in Education LinkedIn Group: Facilitated by Peter Shea (who also runs the amazing Instructional Designers in Education Facebook Group),
Anna Mills: Anna is one of the most active, caring, and insightful folks in the AI in education space. She’s quite active across all platforms and moves with curiousity and care in these conversations.
EDUCAUSE AI Community Group: If your institution has a membership with EDUCAUSE, this is a good resource. It’s not as active as some of the others but some solid conversations.
Ethan Mollick: Of course, I should include his One Thing To Try substack above but he more frequently offers a lot more insights with his LinkedIn platform.
Facebook Group: Higher Ed Discussions of AI Writing: Created by Laura Dumin, this group has tons of resources and rich discussions about how we’re navigating all of this.
Jason Guyla: Like others, he does have an individual writing platform, but is also more active and engaged in sharing thoughts and insights in social media spaces and that’s where I catch many of his best insights.
Laura Dumin: Laura runs the Facebook group above but is also another active and engaging voice on social media that I continually learn more from as she shares the good, the bad, and the ugly around navigating AI in education.
Michelle Kassorla: Michelle’s sharing things that are working with studebts, challenging conventional narratives about AI use, and overall sharing of her own creations with AI make her a great account to keep up with.
Share AI + Education = Simplified
Finally, given that readers here have nearly doubled since last May, I wanted to spotlight a few past posts that I think are still relevant that folks might have missed.
4 Steps for Supporting Faculty with GenAI: Some guidance from my own work with faculty over the last few years on how to support and engage them around GenAI. 1.
Academic Fracking: When Publishers Sell Scholars’ Work to AI: Wondering what publishers are doing with all of the academic content they own? Want to consider why academic publishing is a bit of a dumpster fire? Then, enjoy this piece. 1.
AI Plagiarism Considerations Part 1: Along with Part 2 and Part 3, this series helps capture some of my concerns by the focus on plagiarism and plagiarism checkers. 1.
AI Syllabi Policies: A Look at the Collection: I take some time to dig into the crowd-source AI Policy collection I’ve been curating for nearly 3 years now. 1.
Flash Fiction: Your Future Destination: A fiction piece I wrote years ago that feels quite prescient given the health concerns around GenAI. 1.
Getting to an AI Policy Part 1: A discussion of why just having a policy is not enough for institutions to move forward with figuring out GenAI. 1.
On Building an AI Policy for Teaching & Learning: Sharing a student-driven AI usage policy development for which I was involved (with more background here) 1.
On Not Using GenAI: An exploration of where it does and doesn’t make sense about GenAI Usage. 1.
What If GenAI Is a Nothing-Burger: A keynote for the NEFDC that I gave in 2024 that I think is a thoughtful provocation about navigating GenAI for institutions. 1.
Workshop Resources for Student Supports: A set of resources and materials that I created as part of a day-long workshop I did for the student-support side of a university.
So that’s what I got! What about you? What are the must-reads/watches/conversations that ground you when it feels like so many great voices are out there to learn more from?
Upcoming Sightings & Shenanigans
Continuous Improvement Summit, February 2026
EDUCAUSE Online Program: Teaching with AI. Virtual. Facilitating sessions: ongoing
Recently Recorded Panels, Talks, & Publications
The Peer Review Podcast with Sarah Bunin Benor and Mira Sucharov: Authentic Assessment: Co-Creating AI Policies with Students (December 2025)
David Bachman interviewed me on his Substack, Entropy Bonus (November 2025)
The AI Diatribe Podcast with Jason Low (November): Episode 17: Can Universities Keep Pace With AI?
The Opposite of Cheating Podcast with Dr. Tricia Bertram Gallant (October 2025): Season 2, Episode 31.
The Learning Stack Podcast with Thomas Thompson (August 2025). “(i)nnovations, AI, Pirates, and Access”.
Intentional Teaching Podcast with Derek Bruff (August 2025). Episode 73: Study Hall with Lance Eaton, Michelle D. Miller, and David Nelson.
Dissertation: Elbow Patches To Eye Patches: A Phenomenographic Study Of Scholarly Practices, Research Literature Access, And Academic Piracy
AI Policy Resources
AI Syllabi Policy Repository: 190+ policies (always looking for more- submit your AI syllabus policy here)
AI Institutional Policy Repository: 17 policies (always looking for more- submit your AI syllabus policy here)
Finally, if you are doing interesting things with AI in the teaching and learning space, particularly for higher education, consider being interviewed for this Substack or even contributing. Complete this form, and I’ll get back to you soon!
AI+Edu=Simplified by Lance Eaton is licensed under Attribution-ShareAlike 4.0 International