Campus Technology Insider Podcast February 2024
Listen: Could Institutional Policies on Generative AI Hold Back Its Transformative Potential?
Rhea Kelly 00:08
Hello and welcome to the Campus Technology Insider podcast. I'm Rhea Kelly, editor in chief of Campus Technology, and your host.
David Wiley is well known as the co-founder and chief academic officer of Lumen Learning and a long-time advocate of open educational resources and access to educational opportunity. But if you follow him on LinkedIn or on his Improving Learning blog, it's clear that he also does a lot of thinking and speaking and writing about generative AI. For this episode of the podcast, we spoke about why generative AI is the logical successor to OER, AI's impact on instructional design, exciting AI developments on the horizon, and why it's too early for universities to write policies for generative AI usage. Here's our chat.
Hi, David, welcome to the podcast.
David Wiley 01:03
Thank you so much for inviting me to be here.
Rhea Kelly 01:06
So you are well known for your advocacy on open educational resources, open content. And lately, you've been prolific in blogging and speaking about generative AI. I think the parallels that you've made between those two realms are pretty interesting. I thought we could start there and have you talk a little more about that.
David Wiley 01:26
Sure. Well, let me start by saying thanks again for the invite. You know, in the late 1990s, when I was really starting to work on this work, open content — or what eventually came to be known as OER — was really the best tool available for increasing access to educational opportunity. And so I became a really vocal advocate for using open content and OER to do that. But the end goal was always increasing access to educational opportunity — it wasn't to promote OER in and of itself, if that makes sense. There's a confusion of the means with the ends that happens if you forget that your end goal is trying to increase educational opportunity, and instead think that you're an OER advocate. Because what, what will inevitably happen, and what has happened now, is that eventually there will be some innovation that will come along that provides even greater access to educational opportunity. And you want to be able to kind of seamlessly move into that future where you're advocating for the advance that's going to provide the most access to educational opportunity. You don't want to be stuck in the past advocating for something that used to be the best way to do it, but isn't the best way to do it any longer. So, I mean, in that sense I think of generative AI as being kind of the, the logical successor to OER. So I think that they're connected in the sense that I see them very much from the perspective of using them to increase access to educational opportunity.
I think there are, there are two other connections maybe that are worth mentioning. One is about a decade ago, I created this five Rs framework that a lot of people use to talk about and define what the word "open" in open educational resources means. Those five Rs are retain, reuse, revise, remix, and redistribute. And we won't do, we won't do a whole little tutorial on the five Rs right here. But I think there is something interesting, an interesting connection here, in that you can apply that five Rs framework to model weights, which are kind of like the source code of generative AI models, as well. So if, if you have permission, kind of from a legal standpoint, to download the model weights, which will be retain, revise and remix those model weights via fine tuning or, or, or maybe indirectly through RAG or some other process like that, and to use that updated model in any way that you want to use it and also share your updated model weights with others — then we would say that that generative AI model is open in the same sense that open educational resources are open. So I think there's an interesting connection there for us to think about too. To what extent does it make sense for us to advocate for models being open in a five Rs kind of sense? And there's already a lot of that kind of activity happening on places like Hugging Face, which I kind of struggled to take seriously for a while just based on its name, because it's named for the little hugging face emoji. But it's a huge community where people share open source models, they download them from there, they fine-tune them and make updates to them, and they reshare them there. They compare them to each other. There's kind of a leaderboard there of which open source generative AI model is the kind of most effective one right now. So there is some, some of that activity already going on, and I think that's an interesting connection between pre-generative AI OER and what's happening right now. The second connection has to do with copyright, which is a separate issue that I expect we're going to want to talk about.