Campus Technology Insider Podcast February 2024
Rhea Kelly 05:18
Definitely, because that was exactly where I was gonna go next. I think you have kind of a unique perspective on that issue of copyright, and it's been in the news so much lately with lawsuits and etc. So what do you think is happening, and where is it going?
David Wiley 05:34
I hope what's currently happening is indicative of where it will go. To date, the US Copyright Office has been really consistent in asserting that products created by generative AI tools are not eligible for copyright protection. They can't be copyrighted. It's not that you might choose to release them under an open license the way that you would back in the days of OER. It's just that they're just public domain from the get go. The purpose of copyright, the way it's described in the Constitution, is to provide an incentive for creators to create. And AI doesn't need an incentive. And that's, that's the only reason, stated in the copyright clause of the Constitution, for that specifically enumerated right that Congress has to grant copyrights. So it seems like from my perspective, the copyright office has been making what I think of as being kind of the right calls so far. And I hope that it continues to go that way. If you think about all the products of generative AI not even being eligible for copyright, then it connects back to OER in the sense that anything that Chat GPT, or Claude, or Bard, or DALL-E, or any of these tools create, it's all OER. You can do those five R activities to all of their products.
And so for a couple of decades now, there's been a lot of kind of fretting and hemming and hawing in the OER community about the, what we call the sustainability of OER initiatives. Who's going to create the new OER that's needed? Who's going to go back and do the work of updating and maintaining and improving the OER that somebody created seven years ago? Where's the funding going to come from to support all those people? But all of those, that all changes with generative AI. Before generative AI, we asked who would do that work and how we would incentivize them, Who will create an open textbook about biology, and then five years later, who's going to update it, maintain it, improve it? Now, when you need to know something on any topic in biology, you can just go to the generative AI and ask about it and generally get a really reasonable answer. And if you're using a model that's been specifically crafted to be smarter about biology than, than a general model has been, you can get even better answers. A traditional textbook is kind of a snapshot in time of one person or a small group of people's understanding of a concept. And they've explained it in a specific way, and they've written it down and captured it, so that other people can come along, maybe even after the author is dead, and read that and kind of see where they were coming from, as they described what it meant. That, it really contains a single explanation, a single description, right? Whereas with generative AI, when you ask for an explanation, if it doesn't make sense to you, you can just ask for another. If the example that it gives doesn't resonate with you, you can just get another. If you think you understand but you're not sure, you can ask it to ask you review questions and then have it give you feedback on your answers. There's this, this fundamental difference between kind of pre-generative AI instructional materials and post, and that the one is this kind of static snapshot of understanding, where with generative AI, now the kind of defining characteristic of it is your ability to dialogue with it in an interactive way.
Rhea Kelly 09:14
It kind of sounds like, I mean, do you think there's a place for traditional textbooks still, or are, is generative AI going to kill that format?
David Wiley 09:23
Well, I guess it depends on what you mean by kill. If transforming into a butterfly kills the caterpillar, then, then yes, generative AI will probably kill the traditional textbook, right? But, but it's hard to imagine a medium-term future where every textbook isn't augmented by some kind of generative AI capability that gives students the opportunity to have all the explanations they could ever want, all the different examples on different topics they could want. Maybe I want my examples to be about hiking and basketball and jazz and amateur radio, and you want your examples to be about something else, because that's what's you know, that's what you're into. And to be able to do infinite open-ended review, where I can get specific feedback about my answer, once that capability exists in the world, it's hard to imagine — it's not hard to imagine a short-term future, but it's hard to imagine a medium-term future where that's just not table stakes for any kind of educational materials offering.