Introducing a mini-essay series on teaching and learning about AI, ethics, and education
(AI+Education at Northwestern, essay #1)
Sepehr: Good people - how are we doing? Despite all the craziness in the world, I’m in good spirits. My favorite season Fall is a little late but has finally arrived in Chicago. Kids are back in school, autumn colors are emerging and the air is chilling. Our academic year is in full swing at Northwestern (don’t ask me how our football team is doing..) It’s gearing up to be a very busy year, and I’m planning - I’ll even say publicly committing - to write, write, write. I have a few projects cookin’ that I’m especially excited about. In my last post, I mentioned a new creative project I launched last Spring with undergrads: the PCWB podcast blending comedy and academia co-hosted by yours truly and Chicago comedian Mike Knight, and executive produced by award-winning filmmaker Raphael Nash. More on that soon. But for now, I want to turn to what I’m up to in the classroom this year. As professors, the reality is that sometimes we teach because we are assigned a course that needs teaching. Sometimes, though, we get lucky and have the opportunity to teach a course that just beautifully aligns with a topic we are actively working on. This quarter I’m co-teaching an undergraduate course on AI in education with my doctoral student, , who is also working on his dissertation which examines how youth and young adults are engaging with the ethical, social, and political layers and implications of AI. We believe that our course (now in its 2nd iteration) stands out in the crowd of AI+education courses in its deep treatment of history and its clear focus on equity and ethics. So…we thought we would invite you all to join us on this teaching and learning journey over the next couple of months of our class. Starting with this post, we are doing a mini-essay collection of sorts to chronicle our adventures teaching and learning about AI in education along with our students. We hope you will tune in. And we look forward to your engagement, comments, and reactions. And if you just want our syllabus, we are sharing it here for easy reference.
Introducing a mini-essay series on teaching and learning about AI, ethics, and education (by Charles Logan and Sepehr Vakil)
We’re back! We’re once again teaching our undergraduate course AI, Equity, and Public Education in the School of Education and Social Policy at Northwestern University. We first taught this class in Fall 2023, right in the aftermath of generative AI’s arrival on the shores of education. The class hit full enrollment, and now we’ve returned by popular demand for the second edition. And as those of you who are following AI understand, a lot has happened in the AI and education space in just the past several months.
Our course tries to do two things at once: go back in time to provide historical context to the current moment in AI and education, and also stay attentive to the current, rapidly evolving landscape. How can one simultaneously go backwards and forwards? Who knows, but we will find out! And how should we have this conversation in ways that doesn’t lose sight of both the possibilities and very real perils of AI technologies (on the environment, on the future of warfare, and certainly for the future of teaching and learning)? Starting with this post, we are planning to share short weekly reflections on what our students are (hopefully) learning and what we’re learning in the process.
A bit more on what we’re especially excited about in this iteration of the course. This year, we organized the course into three core strands: history, ethics, and policy. The changes reflect our own evolving interests and concerns: from the troubling environmental harms of AI, to the ongoing AI experimentation occurring in the war on Gaza and Ukraine, and to the questions related to the complex policy environment around AI. We designed our course intentionally to allow exploration of this contested and arguably vast domain, but with a primary focus on the question of AI for teaching, learning, and schools. We also note that our syllabus is formulated to guide not just our students for this one particular course, but as a resource to you all and to ourselves as we continue to deepen our collective knowledge and understanding of this complex domain. To that end, as you can see from our syllabus, many of the course readings end up as optional additional resources for students.
We haven’t completely revised the course, however. We kept the technoethical audit of ChatGPT. We previously wrote about the audit’s first iteration for the Civics of Technology, including links to the documents we used in class. We’ve updated the readings for this year’s audit and added several technoskeptical questions pulled from the article “What Relationships Do We Want with Technology? Toward Technoskepticism in Schools?” by Jacob Pleasants, Dan Krutka, and Phil Nichols. You can explore this year’s version of the audit.
One big change we’re excited to try is a new final project. Last year, students created a pedagogical zine focused on an educational technology that incorporates AI. Several student groups granted us their permission to share their amazing work, and you can read about SoapBox, a tool that uses voice recognition; Sherpa, an AI-powered platform for oral exams; and Canva, the popular design platform. You can also access the final project’s documents for use in your own teaching.
So what are we challenging students to do for their final project this year? We’re both big fans of Emily Bender and Alex Hanna’s Mystery AI Hype Theater 3000, an essential public pedagogy project where Bender, Hanna, and special guests “break down the AI hype, separate fact from fiction, and science from bloviation.” Inspired by Mystery AI Hype Theater 3000, we’re asking students to collect their own thematically-related instances of AI hype in K-12 education, and drawing on our course material and class discussions, record themselves calling out the hype, pointing to possibility, and leaving their audience with a more nuanced understanding of how they believe AI can and cannot (and maybe should or should not) support teaching and learning in K-12 education.
Stay tuned for weekly dispatches with updates about how the course is going. We welcome your questions and feedback–and we’d love to see your activities and projects, as together we help each other and our students make sense of this AI moment in education.
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"Inspired by Mystery AI Hype Theater 3000, we’re asking students to collect their own thematically-related instances of AI hype in K-12 education..." Will you curate and share these publicly? I would love to see them!