Ready Or Not, Here AI Come - A Recent Keynote

Estimated Reading Time: 16 minutes

So I recently had the pleasure of getting to do a Keynote Panel with my students around generative AI at Massachusetts Colleges Online--an organization that I am quite a fan of and have presented at over the years.  The Keynote was structured so that I would talk for 20 minutes and then, we would do a panel with the students.  They were amazing and I will additional opportunities to hear from them in the future.  Still, the talk that I gave, I thought was valuable and important for folks to hear as it provides a bit of the context, insights, and advice that I have learned over the last 7 months.  

Below is the text of my talk and you are also welcome to watch this recording I also made in case you want to hear me instead of read me.  The video is just under 20 minutes.  

Ready or Not, Here AI Come: Exploring the Role of Generative AI in Higher Education

Keynote Talk by Lance Eaton

Hi folks,

So my students and I were recently invited to give the Keynote talk at Massachusetts Colleges Online annual conference in mid-June.  The set up was that I would give a short talk and then we would turn to a panel with the students to hear more from them.  I decided to re-record the talk here for folks as again, I think there are some things here that are valuable to others.  

A photo of C3PO from Star Wars with black text at the top that says "R2-D2, you know better than to trust a strange computer."
Image source: Lyman Hansel Gerona on Unsplash
I can remember my first MCO–back in 2012, I came to this conference for the first time.  It was such a delight to be in community with so many folks from around Massachusetts.  Many of you have become colleagues, collaborators, and life-long friends.  So, to be asked to be here is a proud moment for me to be sure.  

But what I’m even more excited about is that the MCO organizers agreed to the idea of brings students to be on a panel.  Because the message I will hammer home time and again in this brief talk–is that talk to your students, build trust with your students, and collaborate with your students.  This won’t solve all the challenges and concerns that generative AI represents–but goddang, it will inevitably surprise you and open up more opportunities.  

Ok–so before I get too much into that, I wanted to provide a bit of background about me.  I’ve been teaching in since 2006–in fact, I started and continue to teach at North Shore Community College.  

I have taught probably around 120-130 college courses in a variety of disciplines.  Early on, I was doing the full-time adjunct thing and that led me into instructional design because when you are teaching 9 face-to-face courses and 2 online courses in a semester, you need to really make synergistic choices that utilize technology effectively.  

So I got my start at North Shore Community College as an instructional designer and for the last 12 years, I've worked at intersection of technology and higher education throughout several Massachusetts colleges and universities.  During this time, I've developed a deeper consideration and participated in rich and complex conversations about the roles of technologies in our world.   

And, of course, in the last decade the rise of movements like Black Lives Matter, Standing Rock, MeToo, and others organizations and communities have risen up to bring to my attention to the ways that technologies can be both empowering and complicit in historical and contemporary violence toward BIPOC folks, the LGBTQIAA community, people with disabilities, and other groups who have been pushed to the periphery. Those things too have made me think about my pedagogical practices, the technologies I use, and the ways that I work with faculty.  

All of that led me to College Unbound, as their Director of Digital Pedagogy, where, as a young college still building its infrastructure as it grows, I have to think deeply about what technologies we bring into practice given that we serve largely an adult population that is more than 70% women of color.  

Being thoughtful about the possibilities and downstream effects of technology is particularly important for our students who are more often digitally surveilled and digitally redlined - that is, subjected to technology rather than agents of technology. 

It’s with a lot of thinking about those things that I start this presentation with an Equity Acknowledgement to further ground our conversation. 

This presentation was prepared using ChatGPT. I acknowledge that ChatGPT and many generative artificial intelligent tools do not respect the individual rights of authors and artists, and ignore concerns over copyright and intellectual property in the training of the system.  
Additionally, I acknowledge that this AI system was trained in part through the exploitation of precarious workers in the Global South. Also, I recognize that the structures to support the expanse of AI rests on continued large-scale extraction of resources from environments in methods that have long effects on the local populations and in the end, many of those resources (i.e. hardware) are often causing further harm in global climate change and environmental degradation; particularly and directly for the Global South and communities that are historically and presently marginalized.  
In this work I specifically used ChatGPT as a collaborative exercise and to test out some ideas about its usage, better understand the tool and its uses in education.  (Inspired by Lawrie Phipps and Donna Lanclos's An Offering)

I’m closely approaching 45.  Douglas Adams still remains a strong influence in my life and it makes me wonder if this quote by him has pushed me to not believe that technology is against the natural order of things but to think more critically about the value exchange that technology offers.  I’m hoping that we can all sit in this place.  

Before we go much further, I just want to mention that I’ll be referring to several documents and resources–you can find those resources linked below and also in this document of resources.

When ChatGPT dropped in December 2022, it landed mostly with a thud.  Many folks were wrapping up what they perceived (real or otherwise) as their first “normal” semester since the pandemic started in Spring 2020.  It can be understood why folks weren’t paying attention to some new tech being touted by tech bros and anyone with an opinion on Twitter.  

But some of us in higher ed, did hear about it and did start to realize the implications of ChatGPT.  Folks like Maha Bali, Bryan Alexander, and others were beginning to have public conversations before the end of December.  Hereto, I started to play with it and share some of my thoughts publicly as I’m apt to do–whether on social media or on my blog.  

Autumm Caines–a colleague and friend of mine came to me with an interesting question about its possible appearance and use by someone in her class at College Unbound.  We got on a zoom call and talked about what did this mean and how did we want to think through it.  I’m indebted for her insight and deliberation as we moved from concern to curiosity; from angst to excitement–and honestly, some respect for the potential students for so quickly leveraging a tool in a new way.

But–and it’s a big but!  College Unbound centers students' voices and works to address the educational trauma that a reasonable share of our students experience at the hands of traditional education.  Any framework where we even began to accuse students, directly or indirectly, felt like a dangerous place for us to go.  A false positive would be antithetical to what we stand for.  So we approached it with curiosity.  Autumm posted a note to her students saying she thought students might have been playing with this tool and she would love to learn more if they did.  She didn’t hear back but led me to the next step.  

I put together an anonymous short survey and sent it out to all students.  It asked if they knew about it, if they were using it, and if so, in what ways did they use it.  We got back some results that showed students were using it improve understanding, to navigating being multi-language learners, and brainstorming.  These were useful insights and so that led me to realize that we needed to know more and think more deeply about it–and not do so in the absence of students but with students.  

So I then had an idea–and I’ll be the first to admit; I have a lot of useless or unnecessary ideas–but this one.  Well, it was definitely one of those that I instantly knew was the right thing to do.  

I realized that a course on AI & Education where the students and I learn about Generative AI while also playing with it and thinking about it in an educational context would make for a great learning experience.  And, we could craft the guidelines for institutional policy.  It struck me and made absolute sense.  My Provost was quickly on board and we realized in general that this could be an ongoing structure not just for Generative AI but other aspects of the college when we encountered new things–be it technology or other structural elements of the institution.

My partner, because she’s also brilliant added to the idea where we could run the course twice.  We have 8-week sessions for our instructional courses in the Spring.  So Spring 1, I ran the course to develop the policy with the students.  Spring 2, we test-piloted those guidelines with specific assignments that the students had in other classes.  The goal was to try them out and see if they made sense or consider loopholes or other issues.  

Here is the syllabus for session 2:  AI & Education Syllabus

Before the class could start, our faculty still needed guidance.  So I put together and shared out this Generative AI Strategy that both issued a temporary policy and provided the larger context for how we get to something more stable.

At the same time, because, well, I’ve been doing this kind of work for a while and I’m deeply invested on open educational practices, I began to crowdsource Generative AI policies in Syllabi and sharing that out so folks had examples to work with.  Currently, we have over 40 examples and you can also add your own if you fill out the form at the top of this crowdsourced document.

The 2 classes were amazing and I can’t stress this enough.  Having students join a class where their work will mean something–where they will further employ their agency–it’s so beautiful. It led to a lot of discoveries, conversations, and ways of understanding the tool that I just wouldn’t have had were I just talking with other faculty and folks in higher ed.  Students had lots of initial and complicated feelings and thoughts, and throughout the course, they just continued to become more developed and thoughtful.  They challenged one another and my own thinking as we played around with ChatGPT, read about it from different perspectives, and considered what does this tool mean for work, learning, and evaluation.  

This was evident early on and led me to see if students would be open to being on a panel at the NERCOMP conference in March. Students and NERCOMP were both interested, so they spoke to a room of some 30 leaders in higher education about their insights.  And needless to say, they crushed it.  And at that point, I knew, that while I certainly have a place in the discussion in places like these, their voices need to be heard and they need to be core to the conversation.  Since then, they have been invited onto podcasts, panels, featured in the Chronicle of Higher Ed, and well, are here to continue to share their wisdom.  

So session 1 of the AI & Education course came up with the guidelines; Session 2 test-drove them and edited them. 

We are just finishing up having faculty review them and doing so in a very similar fashion–a collaborative document where faculty are using the comment feature to share thoughts, questions, and challenges.  This is a great dialogue among faculty as they interact, share concerns, and make new realizations.  

Once done, the students will have a final look at it and then we’ll put it forward as a proposal for CU to consider as institutional policy.  Additionally, some students continue to meet with me as we look to different projects and opportunities such as speaking engagements, podcasts, and even writing projects.  They been invited to participate in Academic convocations and as part of leadership panels at national conferences.  

The thing that I can’t stress enough about all this is how powerful and important it has been for me to be in this space with them.  As you’ll soon see, they have many different lenses to be thinking about generative AI–ones that  are substantially different than my own identities and positionality. We as educators can often think that we know best and understand all of this in ways that are more important or relevant than students. We may think that is the case, but we’re going to miss a lot if we make that assumption when it comes to this set of tools and how they will show up in our lives.

So what has this semester showed me?
  1. Use it and get to know it deeply. There’s a lot of writing about it, but many folks have only played with it in superficial ways.  One of the resources I provided is a prompt-guide to help you think about how to ask it useful questions and the other is a chat-log that I copied to give you a sense of the different answers.  
  2. Students need to be a part of the conversation; not apart from the conversation.
  3. We need to recognize that there are ample ways that generative AI can be useful--failing to do that, we'll continue to lose legitimacy.
  4. Don’t assume that you can “tech” your way to a solution that makes this easier.  This is not a time to double-down on dehumanizing and accusational plagiarism software in an attempt to "catch them".  That road won't lead anywhere good--just ask the professor in Texas who flunked all his students--including graduating students--based on false positives.
  5. The hardest part will be figuring out which of our darlings to kill.  Gahh--that's a horrible expression but we're in the muddy space now.  The space, where a new technology represents a significant change to long-held practices and beliefs.  Some of those practices can and should go away. The vast majority of us do not have the skills or have ever successfully started a fire with our bare hands and wood.  Very few of us know how to set a typewriter ribbon.  There are going to be skills or knowledge areas that we think are really important but actually aren’t in an age of generative AI.  And we should challenge every skill and piece of knowledge and be ready to adjust, reconsider, or put aside some.  
  6. These emerging tools will mean we have to think differently about what the classroom is for and how we relate--I think it will make us have to be more human, build more trust, and through that create more space for exploration and experiment–if guided and targeted learning that is contextual to the student can happen all the time; then what is the value proposition for the classroom?
  7. Whatever problems we are trying to figure out in terms of students; the misuse of generative AI is a symptom of a much larger problem that asks students to be deliberate, relaxed, and take the long way--when our capitalist structure tells them to take on everything, be filled with angst about the fragile nature of lower and middle socio-economic class standing, and that there is never enough cheese in this rat race so they better haul ass and take the shortcut.

Now, you’ll probably notice that I’ve not really talked a lot about or given more substantial guidance to faculty in this short talk and that’s because today’s message really is about the students.  

If you want to hear more from me about my thoughts and recommendations for faculty with more specific considerations from my lens, then I recommend these resources: A talk I recently gave at North Shore Community College and a blog post where I pull together the different talks, slide decks and resources I’ve created for folks.

So at this point in the presentation, I switched to being the moderator and facilitating questions that the students participated in.  I did end on a final note in considering talking to the students I worked with and while this may specifically apply to my students, I think there are pieces of it that are likely to apply to many students if you take the time to engage and listen.

I know this goes without saying, but it’s always worth saying.  Please listen and hear what the students are saying; recognize that their voices are as important as anyone else in this room and that their work on exploring, studying, discussing, and writing about generative AI is already more substantial than probably 80-90% of the people at your institution.  

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