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Keeping up with the AI Tsunami
How do (or don't) I keep up with AI & Education overflow of content
I mentioned in another post that I don't actually keep up with all of the stuff going on in generative AI. And I don’t recommend anyone else do so either. In this post, we’re going to look at some of the tactics that I do us
It is impossible. But, you can develop information flows that allow you to dip into the conversations. This is something that I’ve learned to do over the years and find it useful to stay abreast of things that are of interest to me. It doesn’t mean I keep up with all the things, but a sufficient amount of it and where there are gaps, I am ready to fill them.
I’m looking largely at information flows that come to me. There are definitely hashtags on certain platforms to follow and people’s sites to visit (who haven’t created emailing or RSS feeds)—maybe that’s a future post.
This is the thing to remember—I didn’t sign up for all of these at once. This has been a slow practice over the last decade or more (e.g. google alerts and some of the newsletters). So don’t read this and think you need to sign up for all of it now. Pick and choose 1-2 from each section and see how it feels. Return and sign up for more as makes sense.
Newsletters & Email Sign Ups
I like to keep a clean inbox of just the things I need to respond to. Everything else, I try to get through within 48 hours (or a week at the latest). My philosophy with newsletters and such is that if I don’t get to it in a week, I’m probably not going to. I also rate newsletters differently. Some, I always have to open; others, I’ll try to get to but am ok if I don’t because I know there’s overlap with others that I’ll get the gist somehow.
Some of what follows do not exclusively cover generative AI but the author(s) covers a range of important and valuable topics that reading them is valuable to my work.
This list is not comprehensive but hopefully useful for folks you want to follow and learn from. I have favorites but am keeping the list alphabetical.
Bryan Alexander: If you’re in higher education—really in any capacity, you need to be reading Bryan. He has several different publications but in this instance, his substack on AI and Education is worth checking out.
Maha Bali: Thoughtful ideas about how to use generative AI, the concerns and challenges of it, and how we might think about it with students. But honestly, regardless of what she’s writing about Maha is always providing insight and wisdom.
Stefan Bauschard: Some rich posts about different generative AI is intersect with higher education in big and small ways.
Josh Brake: No solely focused on generative AI but when he does, it always adds some new things to think about.
Autumm Caines: Critically insightful for concerns about and the actual value of generative AI.
Lance Cummings: Solid posts that give educators a sense of what to do with it, particularly for teaching and learning.
Philippa Harmdan: Very much focused on the intersection of generative AI and instructional design.
Gary Marcus: I agree with Marcus as much as I disagree with him but do find him to be insightful and a good check from all the cheerleading going on out there.
Ethan Mollick: Cutting edge of what can be done with generative AI in learning and work.
The Sentient Syllabus: From the folks at the Sentient Syllabus project (check it out!), I find that this source does some interesting and accessible technical discussions that are helpful in better understanding these tools.
Daniel Stanford: I first encountered Daniel when he created the amazing Google Group (see below) and since then have really appreciated his thoughtful contributions to the conversation.
John Warner: Deep takes on distinguishing generative AI from what it is we want students to do.
Marc Watkins: Watkins has been a solid voice with insight about how to make sense of these tools, their opportunities, and their limitations.
Listservs, Groups & Slack Channels
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.
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.
Facebook Group: Instructional Designers in Education: An enormous resource for so many things related to teaching and learning in education but often lots of great AI materials get shared here too.
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.
Facebook Group: ChatGPT and Other AI in the Higher Ed Classroom and Workspace: Created by Sandy Fyfe, this group is a bit larger in scope than the one above and also has lots of sharing of resources and ideas.
Slack-Future of Higher Ed: I dip my toes into this one on occasion to see what some of the chatter and resource-sharing is.
Slack-Artifical Intelligence and Libraries: I just recently stumbled across this and as some may know, I’ve never been a librarian but I’m a deeply interested in libraries (in general, but also within the scope of higher education).
There are a lot of these out there. A LOT. The ones below I subscribe to and try to read a few of them each week. There’s a lot of overlap among them so feel free to choose one and just stick with it. They don’t focus on education but they do help to learn what is going on in the industry as a whole and sometimes introduce tools that might be of interest.
Other Noteworthy Content
These are places that don’t focus solely on generative AI but usually do and will inevitably have other things of interest if you are interested in education and technology.
Using Generative AI for Sifting Through Knowledge
More recently, particularly for really long pieces on the internet or journal articles that I come across, I have been using ChatGPT (4) to help me make more sense of them. Typically, what happens is that I download articles any they end up in my “TBR” (To Be Read) folder, often never to read again. Increasingly, I hope up ChatGPT and enter in the following prompt (adjusting and tweaking it depending upon what I’m looking to get out of it:
You're a scholar with a skill for breaking down research into effective and clear language. Take the attached article and provide the following:
A paragraph that explains the arc of the article's contents.
Bullet points about its most significant points and why those are important to the article's argument.
A list of the possible actions or implications that one might want to take from this article if they work in higher education
What I like about this approach is that it saves that so I can always go back and it also gives me the opportunity to ask follow-up questions as needed.
Google search alerts
Many folks may already know this but Google Alerts is a great resource. You can get an email or RSS Feed that has all or the best of things released on the Internet in the past day, week, or as it happens.
I use it selectively because it can be overwhelming depending upon the terms you use. I would avoid using terms like “artificial intelligence” because it’s like to be so much meaningless that it’s more noise than signal. Still, I might use it to follow a particular voice or a particular intersection with generative artificial intelligence such as higher education or academia. Pairing terms is important and can be done with quotation marks.
Be smart about the word choice. “generative artificial intelligence” and “universities” feels like it’s going to be a flood of uselessness. Yet if I use “academia” or “higher education” it will be a bit more tuned to catch things that might be missed in the other streams—or reveal related content.
Depending upon your institution, I would do “artificial intelligence” with your institution’s full name so you can keep up with anything that anyone is saying about your school in particular. This could be a great way to see who else at or connected to your institution that is doing this work.
One another note about these. I create a filter in my email so they are automatically added to a folder rather than my inbox so that I can go in and read them as I need to.
Google Scholar alerts
Same deal with the Google Scholar Alerts in that they can be amazingly useful to have things flowed to you. This case, it’s largely academic content. This has been indispensable in my dissertation but also with keeping up with generative AI. In this case, I’m typically using the terms “Generative artificial intelligence” and “academia” or “education.”
The benefit of scholar alerts is that it draws upon research publications. Now, that also becomes the problem because often that means you have to then see if you can access the publication (e.g. if your institution has or can acquire access to the article) or if you have to go more challenging routes (requesting it from the author, trying crowdsource places like r/Scholar on Reddit or even going to platforms like SciHub or LibGen). Still, it can give you enough sense of what the literature is out there with abstracts and such to understand what is important or valuable for your usage.
What about you?
This is by no means a comprehensive list. I will probably ultimatley make this its own page of resources for folks to use in order to keep up with the conversations. I missed a lot and kept it largely on text-oriented materials because those are easier to skim and find my way through to the things I’m looking for.
What recommendations do you have? If you could provide just 1 publication or practice that is helping you make sense of the generative AI in education, what would it be?
If I get enough contributions, I’ll do a follow-up with them.