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Welcome to Demystifying Instructional Design, a podcast where I interview various instructional designers to figure out what instructional designers do.
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I'm Rebecca Hogue, your podcast host.
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If you enjoyed this podcast, please consider subscribing or leaving a comment on the Show Notes blog post and consider helping to support the podcast with a donation to my Patreon account.
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Welcome Autumm and Lance to Demystifying Instructional Design.
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This is a bit of a different episode of a podcast.
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We're going to talk today a little bit about ChatGPT the AI phenomena that is lighting up higher ed anyways, if not other spaces as well.
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And so the first thing I'm going to ask is if you could do a quick introduction and give us a little bit of context.
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And I'll start with my context is I teach instructional designers.
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So I'm teaching at the master's level and my students are instructional designers.
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And so for me, I'm looking at it largely as is this tool useful for my students?
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That is the context that I have for it.
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And I'll pass it over to Autumm and then Lance.
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Hi.
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I'm Autumm Caines.
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I am an instructional designer in a faculty development office at the University of Michigan, Dearborn.
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I always think it's important to add what office you're in when you're talking about instructional design, because as Rebecca's audience will know, the context in which you work is an instructional designer can have a huge impact in the type of work that you do.
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So coming from the perspective of a faculty development office, it's more than just instructional technology and it's more than just instructional design.
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It's also faculty development.
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We can get into that a little bit more as we go forward.
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But just to set up the context, I'm also instructional faculty at College Unbound where I know Lance from, and I actually know Lance from this podcast as well.
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That's one of the reasons that I reached out to Lance was because I heard him on this podcast and then we ended up becoming colleagues at College Unbound, But I teach two classes at College Unbound.
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One is Digital Citizenship and the other one is Web and Digital Portfolio.
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So that's just a little bit about my context in terms of where I'm coming atthings from, in terms of ChatGPT.
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I have been looking into large language models since probably 2021 with the upset with the firing of Timnit Gebru at Google from when she was working, she was the head of Ethics and was working on the Lambda large language model and started paying attention to some of the advances that were happening in that technology around that.
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So I do have a tendency to come at it from a little bit more of a critical and ethical perspective.
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But I don't want to go for too long.
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I want to turn things over to Lance and let him introduce himself.
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Sure.
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Hi, I'm Lance Eaton.
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I am Director of Digital Pedagogy at College Unbound.
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I would say what department I'm from, but we don't really have departments because we're still a new enough college and have that new college smell where there's lots of different hats and ways that we try to work around action teams as opposed to traditional departments.
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But if I did, it would probably be Academic Affairs, which is I think where I mostly sit.
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And my role is that mixture of working with faculty, doing faculty development and kind of helping to support them in the development of teaching and learning courses and using different tools.
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And sometimes that tool is a pen and pad and sometimes it's an LMS and sometimes it's artificial intelligence.
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For me, I've had a lot of interesting thinking around or just looking at AI for a couple of years now.
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I just started to develop a more critical view of technology over the 2010s.
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It started to pop up on my radar and then really for much of the from the start of the pandemic until bout a year and a half ago, I was I guess that was halfway through the pandemic or whatever phase we're in now.
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I was working at the Berkman Klein Center for Internet and Society and was both helping to run programs and programing around Internet and society, and a lot of that focused on AI.
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And so I got to see a lot of different people in the industry coming with those critical lenses.
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And so that stuck in my head a lot, especially as ChatGPT became like the pet rock of the 2022-
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2023.
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And people really started to pay attention to a AI generative tools in a way that they certainly hadn't previously.
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Thank you both very much for your introductions and a little bit of context there.
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I'd love to ask you a little bit about what guidance you're giving students regarding the use of Chat GPT And if you could tell me what that stands for, that would be really helpful because I think the audience would find that useful.
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It's a generative pre-trained Transformer ChatGPT And I do think that Lance is the perfect person to answer this.
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I'm going to answer really briefly and just say that I was a little taken aback when this was first opened up, and I really wasn't sure what to do as a teacher. As an instructional designer.
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I had some ideas, but as a teacher I felt a little lost.
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And working at College Unbound, Lance is the person that
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I go to.
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When I have questions, right, And I knew people were going to be coming to me.
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So I went to him and the school just responded in an amazing way that Lance is going to tell you more about now.
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Thank you.
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Yeah.
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So this is again, being a fairly new school there's things we don't have always to fall back on.
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And also a lot of our practice and thinking is student centered.
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And so I was playing with it, thinking about it as well along in terms of instructional design and students and whatnot.
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And I get an email from Autumm saying, I think I have a student that has used it.
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And so that generated a discussion between me and her, and it was at the end of the semester and like there's so much else going on, it gave us an opportunity to really think about in this moment what is what is most useful to do.
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And this is where I think both of our collaborative nature and the way that CU structures itself is to go after the student wasn't the right approach.
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There was a part of our reaction that was just like a hot dang! Like, go student for being that quick and figuring it out.
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We had that moment and we celebrated that for a moment.
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I want to give this person like some kudos for creativity.
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We had the moment of just having that frustration and a mixture of just not...
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Sometimes it's a little ego driven, but like not being happy that the student did it.
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And then we just also were like, What's behind this?
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And I think that's where we really got our momentum and what has gotten our momentum for our school as a whole is really understanding the students and their uses of this.
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I go back to I want to say it's folks like James Lange and when people are doing this type of thing, which is framed in all sorts of deficit language of they're cheating, they're stealing, they're what have you, they're often indicating things aren't working for them.
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They're often indicating this is more of a sign for help, a sign for a lack of trust, lots of different things.
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And so very quickly, me and Autumm realized like, why don't we try to find out?
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And so our first goal was to craft an email.
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And I sent it out to students saying, Hey, this tool exists.
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And I think some students may have used it and we are interested in learning more about it in this non-punitive way.
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We just want to understand what led you to it.
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What might we be able to learn about why you found your way to this tool?
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Nobody responded to that.
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We hoped... nobody did.
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That was okay.
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My partner recommended, well what if you did an anonymous survey?
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And so we put that out to our students at the very end of the semester.
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We probably got, I think, four or five students, and this was at the end of the semester and during break that before everything really exploded, before you were seeing references to it in podcasts and in mainstream stuff, we had three or four students who were saying like, yeah, like we started to use this and we're using it in these ways.
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And so we thought that was interesting.
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And that kind of jolted me to think about the semester for us started January 9th.
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This is before most schools start their fall semester.
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And so we needed something in place.
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And so we developed a policy that we felt was like... recognizing we don't really understand the fullest implications of these tools.
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We don't want to just do a blanket ban and be like, Nope, you can't use it under any condition.
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And we wanted to create safe conditions that if students use it, then it can they can identify that they use it.
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So that can also invite questions and understanding and things like that.
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I think the potential for it can be is as vast as some of the challenges and the concerns around it.
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Right.
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So there's a lot of knee jerk reactions.
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There's a lot of valid reactions about the ways this interferes with how we demonstrate learning by students.
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But I think there's lots of possibilities for us to leverage it.
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If we can find versions of it that aren't steeped in all sorts of exploitative practices.
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But I'll pass to Autumm for her take.
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Yeah.
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So when I saw some responses that I thought potentially could be synthetic text, my first thought wasn't like cheating.
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My first thought.
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like Lance said, it was curiosity.
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It was like, wow, if they figured this out at the same time, I did worry.
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It's so new.
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It's such a new technology.
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This is December of 2022.
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It dropped on November 30th of 2022. The technology has been around for a while now.
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We can go all the way back to the sixties if we're just talking about chat bots.
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Eliza.
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was in the sixties.
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Weizenbaum's ELIZA.
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But in terms of the transformer technology, the idea of using neural networks around large language models to be able to create text so smooth and so clean.
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And so it sounds so convincing, right?
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That's been around for probably about two years now, but you always had to pay for it.
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It's always been behind some kind of paywall or part of some type of product.
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I mean just to open it up to the entire world right at the beginning of finals for higher education.
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That's not insignificant.
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Whenever I talk about this, I always think it's really important to put the context around it.
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Yes, it's a huge jump in terms of technology, right?
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In terms of the tech that is going on, the interface, the way that you use it, the smoothness, all of that.
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But a big part of the hype, a big part of everything that's going on around this has to do with the fact that it's free and the timing in which it was released.
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Those are just two really big parts of it.
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And especially in that moment, I was hearing all of these news articles and things coming out about people being really punitive with their students.
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I read an article about a student who failed an entire class when it was discovered that they had used this tool.
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And it's my understanding also, there's really not a way to prove without any doubt whatsoever that a student used this tool.
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You can run the text through some of the detectors, but those are flawed.
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They're flawed in my testing of this.
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And I don't think anybody even tries to pretend that they can return a 100% positive or 100% negative.
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There's tons of false negatives and false positives.
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So I really... I guess I say all of this to say I'm not surprised that the students, when we sent them that email and just said, hey, we're just curious, did you use this?
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Have you heard of this tool that nobody responded?
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Because like I said, there were tons of articles and news releases out there with people saying that they were punishing students for using this tech.
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So if I were a student and I used it out of curiosity and I also think it's a little bit crazy to say that students wouldn't use it if I were a student, I'd be curious.
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I'd want to try it out at least, and I don't know if I would actually submit that work, but I'd be tempted to, especially if it was the end of the semester.
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And I was really busy and I had a lot of pressure.
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I don't know of any academic integrity statement from any university that mentions AI generated anything.
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I don't know of any classroom policy that mentions any of this kind of stuff.
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So I think it really does challenge us to think about what we mean by cheating and to critically evaluate and take, retake stock in what we mean, what's valuable in an education.
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I felt really lucky that I was working for College Unbound during this time so that I could think about these kind of things with an amazing partner like Lance and with a school that is student centered and student focused.
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That's where I'm at with it.
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With students right now, I guess I'll throw in at the end.
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My class policy right now is actually a little bit more broad than the college's policy I actually say it's fine if you want to use it.
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Just tell me that you used it and describe how you used it.
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I just think it's way too early right now to be punishing students for it.
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You mentioned something about a one credit course, and I would love to hear more about that.
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Yeah, absolutely.
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To just build off of Autumm's point about her policy, like we created a policy that we put out as this is our temporary policy, folks, individual folks are welcome to adjust as makes sense for their classrooms.
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And I think that was, again, like we want to be both student centered.
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We want to empower faculty to make the right decisions on behalf of their students.
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That was another piece of this as I went into the winter break in conversations me and Autumm had, I just had this brain blast.
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That's Jimmy Neutron reference for folks that are interested.
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I just had this brain blast of like quintessential way I could help figure out this challenge at College Unbound would be to do it in a way that was student centered.
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And so like literally got out, I had this idea, I got on my phone, I texted the provost and I was just like, What about this for an idea?
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What if we do a one credit class that is filled with students who are going to play with, learn about and really think about ChatGPT and other AI generative tools.
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And through that class we can create a recommended set of policies for institutional usage.
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Instantly got back, thumbs up, let's do this. Which also meant that oh I have to figure out this course.
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So that was my winter break.
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And then I realized there was another iteration or rather again, my partner in conversation came up with this really great insight of what if you could also connect it to writing courses.
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And so we're doing this one credit course in Session, One of 17 week semesters and we do eight week courses in session one, and eight week courses in session two, and then sometimes sixteen week courses.
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So in Session one, I'm doing a one credit course where we're going to develop a rough draft of policies around usage for faculty and students. In session two, I'm going to try to connect with students that are taking our writing course and have them sign up for this class, and it'll really be an opportunity to kick the tires on the policy.
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So they'll be taking a writing class.
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they'll be using this policy to inform how they're going to use the AI generative tools.
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And that will be a bit of like really trying to figure out like, what are the holes in it, what are the ways that it really works.
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And in conversation with the faculty teaching those courses as well, so that by the end of the semester we'll have had students had a central role in developing it and testing it and putting forward the recommendations for it.
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That's where we are with it, we're about three and a half weeks into the one credit course and it's just been this there's about eight students in it and it's been this rich conversation around like them getting to use it and them getting to like really start to see the answers it comes back with.
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And then also them delving into other content, other things that are helping inform their opinions.
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The week by week things change because in the second week we got the Time magazine report about how in order to do content moderation of all of the horrible stuff on the Internet that they scrawled in order to like, make this open, AI, was paying Kenyan workers $2 an hour for content moderation, which is just another way of saying they paid Kenyan workers $2 an hour to be traumatized by like the worst of the Internet.
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So every week there's these new things that help to flesh out our thinking about it and conversations that we have.
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They hear things like this and they're like, this needs to be on like the UN's agenda.
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This is not correct.
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Like the ways to get like really invested and start to challenge their considerations.
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One of the earliest points that was just great was I had students read some of Autumm's work and raising some of those questions around what does it mean to sign up and get an account with Open AI where it asks for your name, it asks for your email and your cell number?
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And we got into a discussion around like digital redlining.
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And our students are predominantly students of color.
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And so this generated part of when I created the course or part of when I started to create the assignments and the goal was for them to use or engage with these tools, I recognized they would have to create accounts or they would have to have access.
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And so I've offered my credentials for them to log in and to use.
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And as a result of that conversation I had, I probably at this point, I've had half the students ask to use the credentials to use it so that they don't have to give up their own personal information to an entity that has 10 billion dollars invested by Microsoft and is like gathering up all sorts of data on the users.
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So yeah, that that is all where we are now is we're moving into the point in the course where like, besides playing with it, we're really thinking about what would we recommend for usage.
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That's the next discussion we're starting to have.
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Getting back to your question, Rebecca, in terms of how we're using it with students, I have been pretty vocal and I've written a couple of blog posts that you can link in your show notes, really being critical of the idea of using it with students.
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I'm really hoping that those faculty who do teach in a discipline where it makes sense to use it, take a pause, take a beat, and think critically about how they're going to ask students to use it.
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And I suggested some techniques that I could employ to make it so that they weren't forcing their students to use it.
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They weren't forcing their students to sign up for accounts at the bare minimum.
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But I guess I just want to say that I do recognize that.
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I think that's discipline specific and especially, of course, I just love the idea of a course that is specifically designed to gather student voice and get student input about university policy, about college policy.
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I can totally see it. That's a situation where, yes, the students should be informed to the point where they actually have experience with the tool so that they can give informed input.
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But I love the fact, Lance, that you created like a shared account.
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So that way nobody's putting your personal information at the account level, but also it muddles up and it creates noise in terms of the questions that they're asking, right?
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Because it's not just the creation of that account, but also the inputs that you're putting into it.
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And so by having everybody share one account.
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I think that does a Greater good in terms of protecting students.
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That's your influence at hand.
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Makes my day.
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I thank you for that.
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My next question is a little bit about what do we do for instructors?
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Right.
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What advice are we giving instructors?
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How can they?
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How should they?
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How should they not?
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What do we tell instructors about this new tool?
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I personally don't think there's anything wrong with waiting before you use it.
00:20:39.990 --> 00:20:40.710
So I guess there is.
00:20:40.920 --> 00:20:42.180
What do we tell instructors?
00:20:42.180 --> 00:20:45.690
It depends on what the instructors coming to us with needs for, right?
00:20:45.690 --> 00:20:54.319
So if they're coming to me and they're saying I'm worried about cheating, that's a different conversation than I'm intrigued and I want to use it.
00:20:54.329 --> 00:20:54.809
Right?
00:20:55.319 --> 00:21:00.809
So if it's I'm intrigued and I want to use it, my first response might be, Do you really need to use it?
00:21:00.809 --> 00:21:02.400
Do you really need to use it right now?
00:21:02.549 --> 00:21:03.630
What are you doing with it?
00:21:03.630 --> 00:21:04.589
What are you teaching?
00:21:04.589 --> 00:21:06.990
Is it directly related to what you're teaching?
00:21:07.349 --> 00:21:12.900
But is there a way that you could use it and demo it for the students rather than making the students have accounts?
00:21:12.900 --> 00:21:23.160
If you do want the students to have an account, could you have a shared account or could you talk to the students about their understanding of privacy and digital literacy?
00:21:23.160 --> 00:21:30.390
Like I would say, if you're teaching like a digital literacy, digital citizenship course, where are your students at?
00:21:30.390 --> 00:21:37.230
Is this like a level two, three, four kind of course, if this is intro, they might not have a good understanding.
00:21:37.230 --> 00:21:41.029
Most people don't have a good understanding of digital privacy.
00:21:41.039 --> 00:21:54.690
I just think that before you dive into using these tools, you should have a good foundation of data sharing and data collection and you should have examined some cases of where things have gone wrong, data breaches and things like that.
00:21:54.690 --> 00:21:58.920
You should have an idea of what kind of things could go wrong.
00:21:58.920 --> 00:22:13.380
If they're coming to me and they're asking me about cheating because they're worried about cheating, I usually try to do some damage control around helping them to move away from punitive approaches because I don't think they really do any good.
00:22:13.710 --> 00:22:20.670
At the end of the day, I think they just degrade our students' trust in us and our students' trust in higher education.
00:22:20.670 --> 00:22:37.079
And I guess I try to talk to the instructor and remind them how much is really built on that trust, how much of education comes from that place, and help them to realize that they're sacrificing so much more.
00:22:37.079 --> 00:22:54.779
If they take a punitive approach, they're sacrificing so much more than they would be if they took a more open approach, trying to understand where the students are coming from and trying to figure out how this really aligns with their outcomes and the things that they're trying to do in their course.
00:22:54.779 --> 00:23:04.740
So I usually bring it back to some type of helping them to articulate some type of policy for their syllabus, because it all comes back to expectations, right?
00:23:04.740 --> 00:23:27.630
It all comes back to them really thinking about in their heart and what's going on with them, their expectations for the course, the affordances, the tools like ChatGPT and DALL-E and all of these other generative tools can afford students and helping them to articulate to students why it's important and what they learn in the process.
00:23:27.990 --> 00:23:34.289
In terms of ChatGPT, it's not a matter of we want to create essays.
00:23:34.440 --> 00:23:35.789
That's not the point.
00:23:35.789 --> 00:23:38.019
If that's the point, we're doing it wrong.
00:23:38.049 --> 00:23:38.650
Right?
00:23:38.670 --> 00:23:42.930
The point is thinking through and being nuanced in your thinking.
00:23:42.930 --> 00:23:56.099
So nuanced in your thinking that you're putting it down on paper or on a screen and you're scrutinizing and evaluating every word, every paragraph, every sentence to make sure that things fit together and flow together.
00:23:56.099 --> 00:23:57.630
It's that process of writing.
00:23:57.630 --> 00:24:11.880
It's not the product of the essay and helping faculty to have that conversation with their students and helping faculty to articulate that meaning to their students in a way that helps the student to understand, I think is so much more powerful than wagging your finger.
00:24:11.880 --> 00:24:13.890
And if you do this, we're going to punish you.
00:24:14.609 --> 00:24:15.660
I'm going to turn it over to Lance.
00:24:15.660 --> 00:24:16.920
Let him talk about it a little bit.
00:24:17.190 --> 00:24:18.029
100%.
00:24:18.390 --> 00:24:20.069
Everything Autumm just said.
00:24:20.160 --> 00:24:29.220
I think the only areas I would add is I think there's some great value in them using it to enhance some of their own work.
00:24:29.220 --> 00:24:33.990
And I think that's great with the caveats of the potential concerns around privacy that we've already mentioned.
00:24:33.990 --> 00:24:44.309
I think if they are going to do that, I think it is important for them to also be citing and identifying where their course, where their thinking is influenced.
00:24:44.309 --> 00:24:51.210
And I come from this having worked with faculty who have done the things that they don't like, that they don't like their students to do.
00:24:51.210 --> 00:24:57.039
And so just really demonstrating transparency again in how they're using it with their students.
00:24:57.059 --> 00:25:11.250
The other thing that comes to mind in using it is and this is something, again, from conversations with Autumm, is really emphasizing, no matter what they think of it right now, I'm going to, going to take the quote from you Autumm.
00:25:12.269 --> 00:25:16.200
This is the, quote unquote, dumbest that AI is going to be.
00:25:16.230 --> 00:25:20.089
So I see a lot of dismissal and I see a lot of it's fine, like it's fine.
00:25:20.099 --> 00:25:21.299
I'll catch them anyways.
00:25:21.700 --> 00:25:25.769
And there's a whole other discourse around that approach or around those concerns.
00:25:25.769 --> 00:25:36.089
But I think undermining it or not recognizing like now with this research preview, it is getting better because we're all training it to be better.
00:25:36.450 --> 00:25:40.289
And I think within that is really highlighting what I'm starting to see.
00:25:40.289 --> 00:26:08.059
And I want to say, is Anna Mills and a couple other folks have, Maha Bali I think, has done this as well where they they're sharing their dialogs and you're seeing through the questions in the further development in iterations of their questions like the actual dialog, you get some really interesting cool things and I think that's a thing that is powerful and interesting and valuable for for faculty and for their students to be thinking about.
00:26:08.069 --> 00:26:19.380
I'm influenced by Warren Berger, who's written a couple of different books about questions, and I think this is one of those opportunities for us to really think about the power of questioning and what you need to ask good questions.
00:26:19.380 --> 00:26:34.109
And so there's, there's something within this that I think is a possibility for no matter the discipline to really think about how like, how do we ask good questions, how do we ask meaningful questions and how do we refine questions as a means of seeking knowledge.
00:26:34.109 --> 00:26:39.809
But in order to do that, we also have to demonstrate some understanding in order to ask those deeper questions.
00:26:39.809 --> 00:26:46.349
And I think there's a really rich opportunity there to explore within all of this as well, from both faculty and student side.
00:26:46.710 --> 00:26:59.130
Yeah, that was part of what I was thinking with instructional design and with my students is it is even in order to use this effectively as a tool, you need to know what questions to ask.
00:26:59.279 --> 00:27:03.420
And it's the same thing when you're doing analysis in instructional design.
00:27:03.420 --> 00:27:07.079
When you start, you need to know what the important questions are, right?
00:27:07.079 --> 00:27:08.490
Is this a training problem?
00:27:08.910 --> 00:27:11.369
Who are the students? What are the characteristics?
00:27:11.369 --> 00:27:19.109
Like all of these different analyses things are the questions you need to ask, and if you don't know what those questions are, the tools are not useful.
00:27:19.119 --> 00:27:26.339
And so I think there is an inherent skill in learning how to ask the tool the right questions.
00:27:26.880 --> 00:27:27.930
I think there is.
00:27:27.930 --> 00:27:33.059
And it's also different even though it's very, very smooth.
00:27:33.269 --> 00:27:33.779
Right.
00:27:33.779 --> 00:27:35.309
And it sounds very human.
00:27:35.309 --> 00:27:43.960
There is a big difference between asking a question of a human and asking a question of a large language model like ChatGPT.
00:27:44.339 --> 00:27:57.869
If anybody is more interested in this, I was blown away with the prompt engineering stuff that's out there, which is all about how to ask it questions and understanding the different ways that you can ask it questions, which can be.
00:27:58.079 --> 00:28:05.700
This was really interesting to think about how you interface with it and how it's different than maybe interfacing in a human conversation.
00:28:06.359 --> 00:28:18.779
This is probably of no value, but this whole conversation, just like it just had me flashback to Hitchhiker's Guide to the Galaxy when they're waiting for the answer to life, the universe and everything.
00:28:18.869 --> 00:28:24.210
Like, I feel like there's like there's something there for this conversation as well.
00:28:25.890 --> 00:28:26.940
It's the same dynamic.
00:28:27.329 --> 00:28:32.849
Looking for all the right answers are not necessarily the right questions or realizing what the machine is really built for.
00:28:33.509 --> 00:28:40.259
Lance you mentioned something interesting that I think is caused an interesting conversation on Twitter as well, and that's around citing.
00:28:40.799 --> 00:28:54.809
And I actually brought it up a little bit in a from a blog post that Maha Bali had put together, challenging not to anthropomorphize a computer system, but that's worth citing.
00:28:54.960 --> 00:28:56.490
Are we not just doing that?
00:28:56.730 --> 00:28:57.990
How does that make sense?
00:28:58.289 --> 00:29:06.240
I guess I would say I don't know that the citing itself is what anthropomorphizes the tool.
00:29:06.509 --> 00:29:09.630
I think there's lots of other ways we're doing that.
00:29:09.809 --> 00:29:23.160
And so citing might feel like one part of that conglomeration, I would say citing it in the traditional sense of citing, it feels like the fix for now as we're still trying to figure things out.
00:29:23.160 --> 00:29:29.160
I think all of it hearkens to trying to make explicit where information comes from.
00:29:29.549 --> 00:29:32.009
I think citing is a good start.
00:29:32.369 --> 00:29:42.630
I think if we were to lessen or try to detract that or deanthropomorphize it, it makes me think about, what is it...
00:29:42.630 --> 00:29:47.759
Phipps, the article again, it is something Autumm has shared with me in our conversations.
00:29:47.759 --> 00:30:09.089
Phipps and Lanclos citation approach, which is like you identify that you were using this, and that you understand the repercussions of using a tool that works, that is in part built off of like the illegal copying or use of copyrighted works and also the various exploitated labor.
00:30:09.420 --> 00:30:11.579
I feel like that's a way of threading.
00:30:11.630 --> 00:30:13.190
It's like you're citing it.
00:30:13.220 --> 00:30:15.690
You're citing where this information came from.
00:30:15.690 --> 00:30:23.420
And because you cannot tie it to individuals, you also recognize that tool is an exploitative tool of sorts.
00:30:23.599 --> 00:30:29.029
I think that's I think in my head that's one way I've been thinking about or would think about in this context.
00:30:29.299 --> 00:30:39.920
They offer that citation approach, I think slightly, and just to be provocative and it's something like, nope, I think that's what I will be using and will be encouraging others to use.
00:30:40.190 --> 00:30:44.990
We can't just hide behind a citation because I think maybe that's what it is.
00:30:45.740 --> 00:30:50.930
It doesn't anthropomorphize necessarily, but it hides.
00:30:51.559 --> 00:30:59.750
It hides what really goes into that answer, both technically and human cost.
00:31:00.230 --> 00:31:00.490
Yeah.
00:31:00.500 --> 00:31:08.089
So I do have a blog post pulled up and I can read the citation example that Phipps and Lanclos propose.
00:31:08.099 --> 00:31:13.640
So this is what they're proposing as a potential citation.
00:31:13.640 --> 00:31:21.650
And they say we offer the following text not because we think it, but the relevant people will actually use it, but because we think that they should.
00:31:21.829 --> 00:31:29.390
And so it's this presentation paper work was prepared using ChatGPT, an AI chat bot.
00:31:29.660 --> 00:31:41.539
We acknowledge that ChatGPT does not respect the individual rights of authors and artists and ignores concerns over copyright and intellectual property in the training of the system.
00:31:41.569 --> 00:31:49.190
Additionally, we acknowledge that the system was trained in part through the exploitation of precarious workers in the global South.
00:31:49.279 --> 00:31:53.509
In this work I specifically use ChatGPT to...
00:31:53.509 --> 00:31:58.099
then they have some ellipses where you would fill in the way that you actually used the work.
00:31:58.849 --> 00:31:59.750
It's powerful.
00:31:59.779 --> 00:32:00.940
It's really powerful.
00:32:01.250 --> 00:32:04.640
It really makes you stop and think, Should I actually use it?
00:32:04.640 --> 00:32:08.059
If I'm going to acknowledge all of these horrible things about it?
00:32:08.359 --> 00:32:10.069
I'm not sure that people would.
00:32:10.069 --> 00:32:12.349
Lance is saying, Lance is embracing it.
00:32:12.349 --> 00:32:14.849
And I think that's amazing, right?
00:32:14.869 --> 00:32:15.619
But I think.
00:32:15.980 --> 00:32:19.609
It also means I'm probably an irrelevant person rather than a relevant person.
00:32:21.099 --> 00:32:24.789
Oh! I don't know if you are, though.
00:32:24.799 --> 00:32:25.809
I don't know if you are, though.
00:32:25.819 --> 00:32:29.119
I think what they mean by that, people who would use it.
00:32:29.420 --> 00:32:35.359
And so if you're willing to use something like that, I think that definitely says something.
00:32:35.420 --> 00:32:40.460
I proposed in talking with them about the article, so there is probably I need to put this disclaimer out there.
00:32:40.460 --> 00:32:50.839
And if you go to the article, if you go to the blog post, you'll see at the top they acknowledge that I had some input on this, just I didn't write a word blog post, none of it.
00:32:51.289 --> 00:32:52.700
But we had some conversations.
00:32:52.700 --> 00:32:58.589
We had some conversations about citation and about different approaches to citation.
00:32:58.589 --> 00:33:23.160
And one of the things I put forward is you could use this as activism if you really felt very strongly the ethics of these systems and you wanted to make a point, you could add a citation like this to your presentation or your paper or whatever, and then just have a use of ChatGPT that is so minimal, right?
00:33:23.160 --> 00:33:27.000
Like I used it like a thesaurus and I changed out this one word.
00:33:28.019 --> 00:33:34.529
So I used it just so that you could use the citation to point out the abuses that can happen through it.
00:33:34.529 --> 00:33:35.700
It's really powerful.
00:33:35.700 --> 00:33:39.029
It could be used in lots of different kind of ways.
00:33:39.329 --> 00:33:43.740
It's also so powerful because it's using the very thing that ChatGPT obscures.
00:33:43.740 --> 00:33:47.460
So ChatGPT obscures citation, it fabricates citation.
00:33:47.460 --> 00:33:50.279
We don't know what is inside of these language models.
00:33:50.670 --> 00:33:53.519
More than likely, there is copyrighted work in there.
00:33:54.059 --> 00:33:55.500
We don't know that for sure.
00:33:55.500 --> 00:33:59.039
It's just we really don't know what's inside of the language that it's trained on.
00:33:59.039 --> 00:34:14.219
And so this in a way, weaponizes the idea of citation to really speak back to and bring some light and bring some acknowledgment to some of the darker things around this, around this particular tool.
00:34:15.119 --> 00:34:16.860
I think that's fascinating.
00:34:16.918 --> 00:34:22.409
I like the power in that citation, that opening citation.
00:34:22.829 --> 00:34:47.760
One of the ways that I've been using it, which is totally not using it as a data lookup, I have text that's in past tense that I need to move to present tense and it's making it a whole lot faster for me to write it because I can take the stuff that I wrote in past tense, plug it in and say, give me this in present tense, and then I can work with the present tense version that it gave me.
00:34:48.239 --> 00:34:53.010
And because I wrote the past tense, I own the present tense.
00:34:53.010 --> 00:34:54.719
It's just saving me time.
00:34:54.989 --> 00:34:57.539
So again, I'm using it strictly as a tool.
00:34:57.539 --> 00:35:02.159
Now I'm questioning how it is now taking that data.
00:35:02.159 --> 00:35:09.929
And I found it did do that to me because I had asked it a question about a town that we visited called Harrington Harbor.
00:35:10.469 --> 00:35:15.210
And originally it said that this place didn't exist and there was no knowledge of it.
00:35:15.809 --> 00:35:21.630
And then later, when I asked it about Harrington Harbor, it came back and quoted what I had written about it.
00:35:22.199 --> 00:35:22.639
Right.
00:35:22.860 --> 00:35:24.340
So it's like that.
00:35:24.360 --> 00:35:40.829
Oh, now your database thinks Harrington Harbor is the information that I just fed you about Harrington Harbor, which actually shows you where it's getting the information from and it isn't even fact checking it.
00:35:41.070 --> 00:35:52.949
You can't argue like Wikipedia has systems in place where things can be at least somewhat quality controlled in some way, or at least say whether it's been quality controlled or not.
00:35:52.949 --> 00:36:01.889
And fair because ChatGPT is a black box there's no looking inside to see where the information came from.
00:36:02.429 --> 00:36:03.539
I think that's fascinating.
00:36:03.690 --> 00:36:11.000
Just on going back to the point that it's changing all of the time, right?
00:36:11.010 --> 00:36:36.300
And like it seems like every single day there's a new thing coming out, speaking to what you're talking about Rebecca Amazon is now warning their employees to stop using it because they're seeing some of their, like trade secrets in terms of coding, showing up in answers from ChatGPT because they're using ChatGPT to help them code.
00:36:36.420 --> 00:36:47.489
And so the ChatGPT is not keeping those secrets and is then absorbing that and then sharing that with other users who are out there.
00:36:47.489 --> 00:36:56.309
It just put a link in the chat that you can maybe link in the show notes, but yeah, yeah, because it's a learning machine.
00:36:56.309 --> 00:37:02.849
We've been talking about learning technologies and it's coming back to ID stuff and instructional design and technologies.
00:37:02.849 --> 00:37:05.070
For years we've been talking about learning technologies.
00:37:05.070 --> 00:37:08.760
We haven't been talking so much about technologies that learn, which is a little bit different.
00:37:10.889 --> 00:37:12.630
This makes me so happy in some ways.
00:37:12.630 --> 00:37:18.369
I'm not going to like there's a lot there that there is some Schadenfreude going on right now.
00:37:18.389 --> 00:37:22.289
I'm not going to lie to the point about the responses.
00:37:22.769 --> 00:37:24.139
This is it.
00:37:24.239 --> 00:37:26.579
If it gets edited out, I completely understand.
00:37:26.670 --> 00:37:32.070
But I dropped this line this week when we were having a discussion about it.
00:37:32.320 --> 00:37:43.320
This just came to my head like, like fluid is that ChatCPT responds with all of the self-confidence of a mediocre white dude.
00:37:43.739 --> 00:37:49.019
It just does and I just ever since that came to mind, that's all.
00:37:49.019 --> 00:37:49.250
Okay.
00:37:49.260 --> 00:37:55.230
I can only hear ChatGPT responses and the voice of somebody named Brad.
00:37:57.199 --> 00:37:57.559
Yeah.
00:37:58.219 --> 00:38:00.349
Sorry to all of the Bradleys out there, right?
00:38:00.409 --> 00:38:00.840
That's right.
00:38:00.860 --> 00:38:01.280
That's right.
00:38:01.489 --> 00:38:02.179
Disclaimer...
00:38:02.179 --> 00:38:03.280
I think it's Chad, actually.
00:38:03.289 --> 00:38:03.630
I'm sorry.
00:38:03.659 --> 00:38:04.670
ChadGPT.
00:38:05.570 --> 00:38:10.489
Because we were talking about it in the context of its errors and things like that.
00:38:10.760 --> 00:38:13.610
And that came to me.
00:38:13.610 --> 00:38:15.380
And it just it sticks with me now.
00:38:15.409 --> 00:38:17.690
And that's all I can think about now is.
00:38:17.690 --> 00:38:20.269
I love it.
00:38:21.199 --> 00:38:25.610
I'll ask one more sort of question in this area and then I think we'll close off.
00:38:25.610 --> 00:38:31.449
And that is we've talked about guidance for students and guidance for instructors.
00:38:31.460 --> 00:38:33.019
What about instructional designers?
00:38:33.989 --> 00:38:37.349
What do you think instructional designers should be doing with this technology?
00:38:37.820 --> 00:38:45.000
Well, the first blog post that I wrote on this topic was actually me wondering if it could be an instructional designer.
00:38:45.809 --> 00:38:49.590
There's going to be labor implications of this technology, I think everybody.
00:38:50.639 --> 00:38:52.590
Everybody is clear on that, right?
00:38:52.679 --> 00:39:08.079
OpenAI is doing research right now to try to better understand the labor implications because their mission, they say, is to make sure that AI is basically a net positive in the world rather than a negative in the world.
00:39:08.099 --> 00:39:17.610
And so they recognize and realize this is going to have labor implications and trying to foresee and understand that is really important if we're going to be responsible or something like this.
00:39:18.059 --> 00:39:18.960
So I was just curious.
00:39:18.960 --> 00:39:21.800
I was just curious if it could, like, do my job.
00:39:21.809 --> 00:39:28.170
So I went in and pretended that I was a physics professor, which I know nothing about physics.
00:39:28.170 --> 00:39:39.349
I couldn't ask any discipline specific kind of questions, but I just asked really general questions about my department chair wants me to take my learning online and I'm skeptical about it.
00:39:39.360 --> 00:39:41.869
I don't know if this is really for me.
00:39:41.889 --> 00:39:46.380
And just tried to see what it was, what kind of answers that it would give me.
00:39:46.389 --> 00:39:51.300
So going back to the idea of prompt engineering, one of the fun things you can do is role play with it.
00:39:51.300 --> 00:39:53.269
You can ask it to role play with you.
00:39:53.280 --> 00:40:08.579
And so I started off by saying, You are an instructional designer and I'm an instructor and you, if anything, I think that's an interesting approach because I do think that there is a lot of very standard answers in instructional design.
00:40:08.579 --> 00:40:19.139
There's a lot of best practice that it's fine, I guess, but I've always pushed back against it because I think I'm not convinced that it is best practice.
00:40:19.139 --> 00:40:21.599
I don't know who really makes that decision.
00:40:21.630 --> 00:40:23.329
There's just a lot of it out there.
00:40:23.340 --> 00:40:35.369
And so I think it's kind of interesting just to see what kind of vanilla answers it gives you to instructional design problems and then say, okay, well can we be more creative than that?
00:40:35.880 --> 00:40:43.289
Can we go beyond this knowing that these are maybe some of the most generic answers that are out there?
00:40:44.010 --> 00:41:14.010
So for ID folks, I mean, I think it's one of those like really having to spend some time playing with it, whether it's ChatGPT or really any of these tools, both to understand their limitations and possibilities and evolution and to be prepared for the questions that they will get from faculty where I see it impacting potentially ID the most is probably in a lot of the
00:41:14.250 --> 00:41:15.030
OPMs.
00:41:15.030 --> 00:41:16.230
You're thinking about OPMs.
00:41:16.800 --> 00:41:22.199
OPMs I can see the large scale online institutions.
00:41:22.199 --> 00:41:41.400
Your SNUs, your ASUs, your Western Governor's looking to leverage this in a way that reduces the amount of instructional design folks that they rely upon or that they contract out and using this as more systematic means of updating their courses.
00:41:41.610 --> 00:41:50.670
I can see the pathways to that because in some ways it feels very much like textbooks, textbook publishers in their methods.
00:41:50.909 --> 00:41:56.639
We've got to sell more books, and so we've got to come up with a new edition every two years and we'll just switch the chapters around.
00:41:56.699 --> 00:42:01.619
There's some ways I can see some of the larger scale ones being like, We've got to refresh our courses.
00:42:01.619 --> 00:42:06.750
So hey, ChatGPT update it with this kind of flavor.
00:42:07.590 --> 00:42:08.119
Like I could...
00:42:08.130 --> 00:42:14.400
I can see a series of APIs and plug-ins being used to like do a lot of that.
00:42:14.699 --> 00:42:31.920
I think that's and so I would say anybody that is in that space just understanding it and seeing where that starts to pop out because I just have trouble not believing the ways in which those larger entities work on this like assembly line.
00:42:31.920 --> 00:42:39.510
And efficiency is always the better answer than anything else that they aren't going to start thinking about it and using it.
00:42:39.570 --> 00:42:54.119
I think another big role for instructional designers right now too, and I say this on January 30th of 2023 because it's changing all the time, like tomorrow, like it's going to be different.
00:42:54.119 --> 00:42:58.599
I think your administrators need guidance on top of your instructors.
00:42:58.599 --> 00:43:02.519
Your instructors are going to be coming to you and asking you for help with this.
00:43:02.670 --> 00:43:05.400
Just all the different roles of the instructional designer.
00:43:05.429 --> 00:43:10.199
There's the role of you as a content creator and as a designer who's creating stuff for people.
00:43:10.199 --> 00:43:24.719
There's the role of you as somebody who gives advice to faculty, but then most of us have either interactions with some type of administration or we have a director who has direct access to administrators.
00:43:24.719 --> 00:43:27.480
And I think all of us are very busy.
00:43:27.510 --> 00:43:29.760
We have a lot going on, right.
00:43:29.760 --> 00:43:35.639
And we don't have necessarily all the time in the world just to concentrate on generative AI.
00:43:36.150 --> 00:43:59.219
So I think they're going to be coming and asking for advice and asking for guidance in terms of what to do with all of the social change that's going to be happening around what the impact of these tools is going to mean, so just educating yourself and keeping on top of that stuff that's changing, even if you can't stay on top of it for every single day because it is changing every single day.
00:43:59.230 --> 00:44:16.699
If you can stay on top of it once a week, once every two weeks, whatever, to kind of keep your eye on what is happening and how it's changing, I think that it's going to be really important for those who will be coming to you and asking you for advice, which will be faculty, but more than likely it will be administrators, too.
00:44:16.719 --> 00:44:22.929
And I think there's an interesting point about whether or not it could replace instructional design.
00:44:23.349 --> 00:44:39.550
I don't think it can, but I do think it does some things very interestingly, and that's I've been asking it all of the questions, like I've generated some chapters from my textbooks, but I'm using it saying, okay, here are the questions I want this chapter to answer.
00:44:40.119 --> 00:44:40.900
What do you say?
00:44:40.929 --> 00:44:41.949
And then it gives me an answer.
00:44:41.949 --> 00:44:43.510
And I'm like, actually pretty good.
00:44:43.659 --> 00:44:44.409
I'll take that.
00:44:45.579 --> 00:44:51.579
Hey, I will say, and should I say this, and let's say this, just say it.
00:44:51.760 --> 00:45:03.380
I will say I wrote that first blog post trying to figure out if it would, if it could replace me with a little bit of a little bit of tongue in cheek, little bit of haha thing.
00:45:03.670 --> 00:45:12.820
But then I realized the larger discourse of people who really are looking at the potential impacts are not thinking about that.
00:45:12.829 --> 00:45:15.849
They are thinking about whether it could replace teachers.
00:45:17.380 --> 00:45:23.920
So instructional designers, without teachers, that's a really scary prospect if you ask me.
00:45:24.070 --> 00:45:27.340
And that's the bigger thing to be concerned with.
00:45:28.210 --> 00:45:31.420
Yeah, 100%.
00:45:31.929 --> 00:45:33.639
Do you think that's where it's going?
00:45:33.670 --> 00:45:54.059
I think the thing I see is and this is the it's the thing that with whether it's AI or it's robots, that that seems to be sometimes missed or under considered is like I hear folks being like there's some jobs, that robots or AI won't ever replace that's not they'll replace them en masse.
00:45:54.070 --> 00:46:08.019
What it will mean is that you as an individual instructional designer or plumber or whatever your profession, you will be able to do a lot more, more quickly.
00:46:08.199 --> 00:46:16.000
And so if previously you were only able to work with ten faculty, you can now work with 20 or you can work with 100.
00:46:16.179 --> 00:46:18.320
That's the thing that I'm seeing.
00:46:18.340 --> 00:46:32.679
So it's not that you replace all instructional designers, but it means one like the expectation of one instructional designer will be much more expansive or be much more expected than what it was previously.
00:46:32.679 --> 00:46:41.980
And like, we see that within our technologies, every tech like we have over the last 50 years, almost all workers have become increasingly way more productive.
00:46:42.039 --> 00:46:45.400
But we keep asking more and more of them and of course, paying less and less of them.
00:46:45.760 --> 00:47:01.489
And so I think that's the thing, is what this shows, or what this creates the opportunity to, is like now instead of and I've seen and was playing around with this in December as well when I was doing some advising, I was like, What if I use the machine to help me get started?
00:47:01.510 --> 00:47:08.400
So rather than spending 5 hours of like hemming and hawing, I used it as a like, let's see what I can get here and start running more quickly.
00:47:08.409 --> 00:47:12.000
And I think that is where the challenge is.
00:47:12.019 --> 00:47:13.869
It's not going to be replacing all.
00:47:13.869 --> 00:47:17.349
It's just going to make the need for this fewer and fewer.
00:47:17.380 --> 00:47:29.019
And I think when we talk about replacing teachers, like to me in many ways, the big scale instructional places that have 130,000 students, they pretty much replace teachers there.
00:47:29.110 --> 00:47:29.440
Right.
00:47:29.530 --> 00:47:32.559
If you teach at those schools, you're not doing curriculum.
00:47:32.679 --> 00:47:35.559
You are grading and you are doing discussions.
00:47:35.559 --> 00:47:40.800
And I think they're doing that because they need to at least justify that you actually have an interaction with a human.
00:47:40.809 --> 00:47:48.670
Well, yeah, they will replace those, but meanwhile they can also much of their staff is not faculty, but is actual staff like instructional designers.
00:47:48.670 --> 00:47:51.849
And now it's like, Oh, we can maybe even do less.
00:47:51.849 --> 00:48:00.369
And so I think I don't want to be like, Oh, we're all doomed because of robots and AI But I think that is the threat that they pose.
00:48:00.369 --> 00:48:03.610
And I think in industries we can start to see that happening.
00:48:04.539 --> 00:48:05.110
That's right.
00:48:05.530 --> 00:48:17.320
And yeah, I don't know if it I also don't want to jump on the robots are coming for our jobs pedestal like we know that doesn't end well.
00:48:17.619 --> 00:48:19.420
And it's never 100% true.
00:48:19.420 --> 00:48:23.400
But what you just talked about, Lance, is job loss, right?
00:48:23.409 --> 00:48:24.570
It's job shifting.
00:48:24.579 --> 00:48:34.510
If we have 50 instructional designers right now and each one of them are working with ten instructors, if each one of them can work with 50 instructors.
00:48:34.809 --> 00:48:37.949
Yeah, that's a different situation.
00:48:38.489 --> 00:48:41.829
It will be interesting to see how it plays out.
00:48:41.840 --> 00:48:44.530
I guess the big takeaway is nobody really knows.
00:48:44.530 --> 00:48:49.030
But one thing that we do know is that there will be some kind of labor implications.
00:48:49.150 --> 00:48:52.360
There could also be job creation around this as well.
00:48:52.420 --> 00:48:52.880
Right.
00:48:52.900 --> 00:49:03.650
Knowing people who know prompt engineering or who know how to train a language model, those kind of things could end up being something that are marketable skills that we might need going forward.
00:49:03.670 --> 00:49:13.389
So I don't want to paint it as all gloom and doom, but there will probably be upset and there will probably be some reskilling that is needed and there will probably be big changes.
00:49:13.420 --> 00:49:24.179
I want to say thank you to both of you for coming in and joining this little thought experiment around ChatGPT and what it might be doing this semester.
00:49:24.190 --> 00:49:42.130
I am really curious to see how all of this is going to play out and where we're going to be at come September, right when we go into another semester after having had the summer as well and a little bit more time for things to play out.
00:49:42.130 --> 00:49:46.869
But thank you very much for your willingness to come on and chat with me about Chat.
00:49:47.590 --> 00:49:49.090
Thanks so much for having us, Rebecca.
00:49:49.510 --> 00:49:49.989
Thank you.
00:49:51.130 --> 00:49:57.340
You've been listening to Demystifying Instructional Design, a podcast where I interview instructional designers about what they do.
00:49:57.940 --> 00:50:05.110
I'm Rebecca Hogue, your podcast host. Show notes are posted as a blog post on Demystifying Instructional Design dot com.
00:50:05.559 --> 00:50:07.960
If you enjoyed this podcast, please subscribe or leave a
00:50:07.960 --> 00:50:09.849
comment in the show notes Blog post.
00:00:06.309 --> 00:00:13.929
Welcome to Demystifying Instructional Design, a podcast where I interview various instructional designers to figure out what instructional designers do.
00:00:14.349 --> 00:00:16.208
I'm Rebecca Hogue, your podcast host.
00:00:16.870 --> 00:00:27.789
If you enjoyed this podcast, please consider subscribing or leaving a comment on the Show Notes blog post and consider helping to support the podcast with a donation to my Patreon account.
00:00:28.059 --> 00:00:32.118
Welcome Autumm and Lance to Demystifying Instructional Design.
00:00:32.140 --> 00:00:34.990
This is a bit of a different episode of a podcast.
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We're going to talk today a little bit about ChatGPT the AI phenomena that is lighting up higher ed anyways, if not other spaces as well.
00:00:45.280 --> 00:00:50.979
And so the first thing I'm going to ask is if you could do a quick introduction and give us a little bit of context.
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And I'll start with my context is I teach instructional designers.
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So I'm teaching at the master's level and my students are instructional designers.
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And so for me, I'm looking at it largely as is this tool useful for my students?
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That is the context that I have for it.
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And I'll pass it over to Autumm and then Lance.
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Hi.
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I'm Autumm Caines.
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I am an instructional designer in a faculty development office at the University of Michigan, Dearborn.
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I always think it's important to add what office you're in when you're talking about instructional design, because as Rebecca's audience will know, the context in which you work is an instructional designer can have a huge impact in the type of work that you do.
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So coming from the perspective of a faculty development office, it's more than just instructional technology and it's more than just instructional design.
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It's also faculty development.
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We can get into that a little bit more as we go forward.
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But just to set up the context, I'm also instructional faculty at College Unbound where I know Lance from, and I actually know Lance from this podcast as well.
00:02:03.019 --> 00:02:14.110
That's one of the reasons that I reached out to Lance was because I heard him on this podcast and then we ended up becoming colleagues at College Unbound, But I teach two classes at College Unbound.
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One is Digital Citizenship and the other one is Web and Digital Portfolio.
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So that's just a little bit about my context in terms of where I'm coming atthings from, in terms of ChatGPT.
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I have been looking into large language models since probably 2021 with the upset with the firing of Timnit Gebru at Google from when she was working, she was the head of Ethics and was working on the Lambda large language model and started paying attention to some of the advances that were happening in that technology around that.
00:02:51.729 --> 00:02:56.909
So I do have a tendency to come at it from a little bit more of a critical and ethical perspective.
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But I don't want to go for too long.
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I want to turn things over to Lance and let him introduce himself.
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Sure.
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Hi, I'm Lance Eaton.
00:03:03.069 --> 00:03:06.370
I am Director of Digital Pedagogy at College Unbound.
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I would say what department I'm from, but we don't really have departments because we're still a new enough college and have that new college smell where there's lots of different hats and ways that we try to work around action teams as opposed to traditional departments.
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But if I did, it would probably be Academic Affairs, which is I think where I mostly sit.
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And my role is that mixture of working with faculty, doing faculty development and kind of helping to support them in the development of teaching and learning courses and using different tools.
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And sometimes that tool is a pen and pad and sometimes it's an LMS and sometimes it's artificial intelligence.
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For me, I've had a lot of interesting thinking around or just looking at AI for a couple of years now.
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I just started to develop a more critical view of technology over the 2010s.
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It started to pop up on my radar and then really for much of the from the start of the pandemic until bout a year and a half ago, I was I guess that was halfway through the pandemic or whatever phase we're in now.
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I was working at the Berkman Klein Center for Internet and Society and was both helping to run programs and programing around Internet and society, and a lot of that focused on AI.
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And so I got to see a lot of different people in the industry coming with those critical lenses.
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And so that stuck in my head a lot, especially as ChatGPT became like the pet rock of the 2022-
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2023.
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And people really started to pay attention to a AI generative tools in a way that they certainly hadn't previously.
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Thank you both very much for your introductions and a little bit of context there.
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I'd love to ask you a little bit about what guidance you're giving students regarding the use of Chat GPT And if you could tell me what that stands for, that would be really helpful because I think the audience would find that useful.
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It's a generative pre-trained Transformer ChatGPT And I do think that Lance is the perfect person to answer this.
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I'm going to answer really briefly and just say that I was a little taken aback when this was first opened up, and I really wasn't sure what to do as a teacher. As an instructional designer.
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I had some ideas, but as a teacher I felt a little lost.
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And working at College Unbound, Lance is the person that
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I go to.
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When I have questions, right, And I knew people were going to be coming to me.
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So I went to him and the school just responded in an amazing way that Lance is going to tell you more about now.
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Thank you.
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Yeah.
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So this is again, being a fairly new school there's things we don't have always to fall back on.
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And also a lot of our practice and thinking is student centered.
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And so I was playing with it, thinking about it as well along in terms of instructional design and students and whatnot.
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And I get an email from Autumm saying, I think I have a student that has used it.
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And so that generated a discussion between me and her, and it was at the end of the semester and like there's so much else going on, it gave us an opportunity to really think about in this moment what is what is most useful to do.
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And this is where I think both of our collaborative nature and the way that CU structures itself is to go after the student wasn't the right approach.
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There was a part of our reaction that was just like a hot dang! Like, go student for being that quick and figuring it out.
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We had that moment and we celebrated that for a moment.
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I want to give this person like some kudos for creativity.
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We had the moment of just having that frustration and a mixture of just not...
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Sometimes it's a little ego driven, but like not being happy that the student did it.
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And then we just also were like, What's behind this?
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And I think that's where we really got our momentum and what has gotten our momentum for our school as a whole is really understanding the students and their uses of this.
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I go back to I want to say it's folks like James Lange and when people are doing this type of thing, which is framed in all sorts of deficit language of they're cheating, they're stealing, they're what have you, they're often indicating things aren't working for them.
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They're often indicating this is more of a sign for help, a sign for a lack of trust, lots of different things.
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And so very quickly, me and Autumm realized like, why don't we try to find out?
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And so our first goal was to craft an email.
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And I sent it out to students saying, Hey, this tool exists.
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And I think some students may have used it and we are interested in learning more about it in this non-punitive way.
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We just want to understand what led you to it.
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What might we be able to learn about why you found your way to this tool?
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Nobody responded to that.
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We hoped... nobody did.
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That was okay.
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My partner recommended, well what if you did an anonymous survey?
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And so we put that out to our students at the very end of the semester.
00:08:10.360 --> 00:08:29.889
We probably got, I think, four or five students, and this was at the end of the semester and during break that before everything really exploded, before you were seeing references to it in podcasts and in mainstream stuff, we had three or four students who were saying like, yeah, like we started to use this and we're using it in these ways.
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And so we thought that was interesting.
00:08:32.168 --> 00:08:38.168
And that kind of jolted me to think about the semester for us started January 9th.
00:08:38.889 --> 00:08:42.190
This is before most schools start their fall semester.
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And so we needed something in place.
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And so we developed a policy that we felt was like... recognizing we don't really understand the fullest implications of these tools.
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We don't want to just do a blanket ban and be like, Nope, you can't use it under any condition.
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And we wanted to create safe conditions that if students use it, then it can they can identify that they use it.
00:09:06.580 --> 00:09:10.000
So that can also invite questions and understanding and things like that.
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I think the potential for it can be is as vast as some of the challenges and the concerns around it.
00:09:16.539 --> 00:09:16.750
Right.
00:09:16.750 --> 00:09:18.549
So there's a lot of knee jerk reactions.
00:09:18.669 --> 00:09:25.570
There's a lot of valid reactions about the ways this interferes with how we demonstrate learning by students.
00:09:25.809 --> 00:09:29.590
But I think there's lots of possibilities for us to leverage it.
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If we can find versions of it that aren't steeped in all sorts of exploitative practices.
00:09:35.080 --> 00:09:37.110
But I'll pass to Autumm for her take.
00:09:37.840 --> 00:09:38.169
Yeah.
00:09:38.169 --> 00:09:47.889
So when I saw some responses that I thought potentially could be synthetic text, my first thought wasn't like cheating.
00:09:48.309 --> 00:09:49.360
My first thought.
00:09:49.360 --> 00:09:51.009
like Lance said, it was curiosity.
00:09:51.009 --> 00:09:55.960
It was like, wow, if they figured this out at the same time, I did worry.
00:09:56.259 --> 00:09:57.190
It's so new.
00:09:57.190 --> 00:09:58.720
It's such a new technology.
00:09:58.990 --> 00:10:01.389
This is December of 2022.
00:10:01.539 --> 00:10:08.200
It dropped on November 30th of 2022. The technology has been around for a while now.
00:10:08.230 --> 00:10:12.100
We can go all the way back to the sixties if we're just talking about chat bots.
00:10:12.370 --> 00:10:12.850
Eliza.
00:10:12.919 --> 00:10:13.820
was in the sixties.
00:10:13.820 --> 00:10:15.070
Weizenbaum's ELIZA.
00:10:15.110 --> 00:10:27.350
But in terms of the transformer technology, the idea of using neural networks around large language models to be able to create text so smooth and so clean.
00:10:27.350 --> 00:10:29.690
And so it sounds so convincing, right?
00:10:30.379 --> 00:10:34.730
That's been around for probably about two years now, but you always had to pay for it.
00:10:35.149 --> 00:10:39.049
It's always been behind some kind of paywall or part of some type of product.
00:10:39.049 --> 00:10:45.309
I mean just to open it up to the entire world right at the beginning of finals for higher education.
00:10:45.320 --> 00:10:47.440
That's not insignificant.
00:10:47.450 --> 00:10:52.639
Whenever I talk about this, I always think it's really important to put the context around it.
00:10:52.639 --> 00:10:56.539
Yes, it's a huge jump in terms of technology, right?
00:10:56.539 --> 00:11:02.909
In terms of the tech that is going on, the interface, the way that you use it, the smoothness, all of that.
00:11:02.929 --> 00:11:12.049
But a big part of the hype, a big part of everything that's going on around this has to do with the fact that it's free and the timing in which it was released.
00:11:12.500 --> 00:11:14.870
Those are just two really big parts of it.
00:11:14.870 --> 00:11:25.809
And especially in that moment, I was hearing all of these news articles and things coming out about people being really punitive with their students.
00:11:25.820 --> 00:11:33.919
I read an article about a student who failed an entire class when it was discovered that they had used this tool.
00:11:33.980 --> 00:11:41.960
And it's my understanding also, there's really not a way to prove without any doubt whatsoever that a student used this tool.
00:11:41.960 --> 00:11:46.570
You can run the text through some of the detectors, but those are flawed.
00:11:46.580 --> 00:11:49.129
They're flawed in my testing of this.
00:11:49.129 --> 00:11:57.049
And I don't think anybody even tries to pretend that they can return a 100% positive or 100% negative.
00:11:57.350 --> 00:12:00.279
There's tons of false negatives and false positives.
00:12:00.289 --> 00:12:08.990
So I really... I guess I say all of this to say I'm not surprised that the students, when we sent them that email and just said, hey, we're just curious, did you use this?
00:12:08.990 --> 00:12:11.480
Have you heard of this tool that nobody responded?
00:12:11.480 --> 00:12:21.259
Because like I said, there were tons of articles and news releases out there with people saying that they were punishing students for using this tech.
00:12:21.259 --> 00:12:32.210
So if I were a student and I used it out of curiosity and I also think it's a little bit crazy to say that students wouldn't use it if I were a student, I'd be curious.
00:12:32.210 --> 00:12:39.950
I'd want to try it out at least, and I don't know if I would actually submit that work, but I'd be tempted to, especially if it was the end of the semester.
00:12:39.950 --> 00:12:42.830
And I was really busy and I had a lot of pressure.
00:12:43.009 --> 00:12:51.830
I don't know of any academic integrity statement from any university that mentions AI generated anything.
00:12:52.070 --> 00:12:57.289
I don't know of any classroom policy that mentions any of this kind of stuff.
00:12:57.289 --> 00:13:12.100
So I think it really does challenge us to think about what we mean by cheating and to critically evaluate and take, retake stock in what we mean, what's valuable in an education.
00:13:12.100 --> 00:13:24.080
I felt really lucky that I was working for College Unbound during this time so that I could think about these kind of things with an amazing partner like Lance and with a school that is student centered and student focused.
00:13:24.230 --> 00:13:25.759
That's where I'm at with it.
00:13:25.759 --> 00:13:27.559
With students right now, I guess I'll throw in at the end.
00:13:27.570 --> 00:13:35.750
My class policy right now is actually a little bit more broad than the college's policy I actually say it's fine if you want to use it.
00:13:35.750 --> 00:13:38.750
Just tell me that you used it and describe how you used it.
00:13:38.750 --> 00:13:44.090
I just think it's way too early right now to be punishing students for it.
00:13:44.360 --> 00:13:49.220
You mentioned something about a one credit course, and I would love to hear more about that.
00:13:49.460 --> 00:13:50.629
Yeah, absolutely.
00:13:50.779 --> 00:14:03.080
To just build off of Autumm's point about her policy, like we created a policy that we put out as this is our temporary policy, folks, individual folks are welcome to adjust as makes sense for their classrooms.
00:14:03.080 --> 00:14:05.929
And I think that was, again, like we want to be both student centered.
00:14:05.929 --> 00:14:10.850
We want to empower faculty to make the right decisions on behalf of their students.
00:14:10.850 --> 00:14:19.490
That was another piece of this as I went into the winter break in conversations me and Autumm had, I just had this brain blast.
00:14:19.490 --> 00:14:22.429
That's Jimmy Neutron reference for folks that are interested.
00:14:22.669 --> 00:14:33.740
I just had this brain blast of like quintessential way I could help figure out this challenge at College Unbound would be to do it in a way that was student centered.
00:14:33.919 --> 00:14:42.470
And so like literally got out, I had this idea, I got on my phone, I texted the provost and I was just like, What about this for an idea?
00:14:42.470 --> 00:14:54.620
What if we do a one credit class that is filled with students who are going to play with, learn about and really think about ChatGPT and other AI generative tools.
00:14:54.620 --> 00:15:00.980
And through that class we can create a recommended set of policies for institutional usage.
00:15:01.370 --> 00:15:06.950
Instantly got back, thumbs up, let's do this. Which also meant that oh I have to figure out this course.
00:15:07.250 --> 00:15:08.360
So that was my winter break.
00:15:08.720 --> 00:15:17.429
And then I realized there was another iteration or rather again, my partner in conversation came up with this really great insight of what if you could also connect it to writing courses.
00:15:17.429 --> 00:15:30.019
And so we're doing this one credit course in Session, One of 17 week semesters and we do eight week courses in session one, and eight week courses in session two, and then sometimes sixteen week courses.
00:15:30.029 --> 00:15:49.259
So in Session one, I'm doing a one credit course where we're going to develop a rough draft of policies around usage for faculty and students. In session two, I'm going to try to connect with students that are taking our writing course and have them sign up for this class, and it'll really be an opportunity to kick the tires on the policy.
00:15:49.289 --> 00:15:50.759
So they'll be taking a writing class.
00:15:50.759 --> 00:15:57.029
they'll be using this policy to inform how they're going to use the AI generative tools.
00:15:57.029 --> 00:16:02.549
And that will be a bit of like really trying to figure out like, what are the holes in it, what are the ways that it really works.
00:16:02.549 --> 00:16:13.799
And in conversation with the faculty teaching those courses as well, so that by the end of the semester we'll have had students had a central role in developing it and testing it and putting forward the recommendations for it.
00:16:14.159 --> 00:16:31.049
That's where we are with it, we're about three and a half weeks into the one credit course and it's just been this there's about eight students in it and it's been this rich conversation around like them getting to use it and them getting to like really start to see the answers it comes back with.
00:16:31.049 --> 00:16:35.759
And then also them delving into other content, other things that are helping inform their opinions.
00:16:36.000 --> 00:16:59.100
The week by week things change because in the second week we got the Time magazine report about how in order to do content moderation of all of the horrible stuff on the Internet that they scrawled in order to like, make this open, AI, was paying Kenyan workers $2 an hour for content moderation, which is just another way of saying they paid Kenyan workers $2 an hour to be traumatized by like the worst of the Internet.
00:16:59.580 --> 00:17:06.269
So every week there's these new things that help to flesh out our thinking about it and conversations that we have.
00:17:06.449 --> 00:17:09.990
They hear things like this and they're like, this needs to be on like the UN's agenda.
00:17:09.990 --> 00:17:10.799
This is not correct.
00:17:10.809 --> 00:17:16.230
Like the ways to get like really invested and start to challenge their considerations.
00:17:16.529 --> 00:17:32.940
One of the earliest points that was just great was I had students read some of Autumm's work and raising some of those questions around what does it mean to sign up and get an account with Open AI where it asks for your name, it asks for your email and your cell number?
00:17:33.420 --> 00:17:36.420
And we got into a discussion around like digital redlining.
00:17:36.420 --> 00:17:39.690
And our students are predominantly students of color.
00:17:39.690 --> 00:17:55.109
And so this generated part of when I created the course or part of when I started to create the assignments and the goal was for them to use or engage with these tools, I recognized they would have to create accounts or they would have to have access.
00:17:55.109 --> 00:17:59.069
And so I've offered my credentials for them to log in and to use.
00:17:59.069 --> 00:18:18.480
And as a result of that conversation I had, I probably at this point, I've had half the students ask to use the credentials to use it so that they don't have to give up their own personal information to an entity that has 10 billion dollars invested by Microsoft and is like gathering up all sorts of data on the users.
00:18:19.019 --> 00:18:28.289
So yeah, that that is all where we are now is we're moving into the point in the course where like, besides playing with it, we're really thinking about what would we recommend for usage.
00:18:28.470 --> 00:18:30.599
That's the next discussion we're starting to have.
00:18:31.109 --> 00:18:46.650
Getting back to your question, Rebecca, in terms of how we're using it with students, I have been pretty vocal and I've written a couple of blog posts that you can link in your show notes, really being critical of the idea of using it with students.
00:18:47.130 --> 00:19:02.670
I'm really hoping that those faculty who do teach in a discipline where it makes sense to use it, take a pause, take a beat, and think critically about how they're going to ask students to use it.
00:19:02.670 --> 00:19:11.910
And I suggested some techniques that I could employ to make it so that they weren't forcing their students to use it.
00:19:11.910 --> 00:19:15.480
They weren't forcing their students to sign up for accounts at the bare minimum.
00:19:15.869 --> 00:19:19.200
But I guess I just want to say that I do recognize that.
00:19:19.200 --> 00:19:35.099
I think that's discipline specific and especially, of course, I just love the idea of a course that is specifically designed to gather student voice and get student input about university policy, about college policy.
00:19:35.789 --> 00:19:46.829
I can totally see it. That's a situation where, yes, the students should be informed to the point where they actually have experience with the tool so that they can give informed input.
00:19:46.829 --> 00:19:52.410
But I love the fact, Lance, that you created like a shared account.
00:19:52.680 --> 00:20:03.359
So that way nobody's putting your personal information at the account level, but also it muddles up and it creates noise in terms of the questions that they're asking, right?
00:20:03.359 --> 00:20:07.349
Because it's not just the creation of that account, but also the inputs that you're putting into it.
00:20:07.859 --> 00:20:10.529
And so by having everybody share one account.
00:20:10.799 --> 00:20:15.299
I think that does a Greater good in terms of protecting students.
00:20:15.690 --> 00:20:16.920
That's your influence at hand.
00:20:17.700 --> 00:20:18.309
Makes my day.
00:20:18.329 --> 00:20:19.019
I thank you for that.
00:20:20.369 --> 00:20:24.450
My next question is a little bit about what do we do for instructors?
00:20:24.569 --> 00:20:24.930
Right.
00:20:24.960 --> 00:20:27.690
What advice are we giving instructors?
00:20:27.960 --> 00:20:28.680
How can they?
00:20:28.680 --> 00:20:29.579
How should they?
00:20:29.579 --> 00:20:30.960
How should they not?
00:20:31.380 --> 00:20:34.079
What do we tell instructors about this new tool?
00:20:34.230 --> 00:20:39.990
I personally don't think there's anything wrong with waiting before you use it.
00:20:39.990 --> 00:20:40.710
So I guess there is.
00:20:40.920 --> 00:20:42.180
What do we tell instructors?
00:20:42.180 --> 00:20:45.690
It depends on what the instructors coming to us with needs for, right?
00:20:45.690 --> 00:20:54.319
So if they're coming to me and they're saying I'm worried about cheating, that's a different conversation than I'm intrigued and I want to use it.
00:20:54.329 --> 00:20:54.809
Right?
00:20:55.319 --> 00:21:00.809
So if it's I'm intrigued and I want to use it, my first response might be, Do you really need to use it?
00:21:00.809 --> 00:21:02.400
Do you really need to use it right now?
00:21:02.549 --> 00:21:03.630
What are you doing with it?
00:21:03.630 --> 00:21:04.589
What are you teaching?
00:21:04.589 --> 00:21:06.990
Is it directly related to what you're teaching?
00:21:07.349 --> 00:21:12.900
But is there a way that you could use it and demo it for the students rather than making the students have accounts?
00:21:12.900 --> 00:21:23.160
If you do want the students to have an account, could you have a shared account or could you talk to the students about their understanding of privacy and digital literacy?
00:21:23.160 --> 00:21:30.390
Like I would say, if you're teaching like a digital literacy, digital citizenship course, where are your students at?
00:21:30.390 --> 00:21:37.230
Is this like a level two, three, four kind of course, if this is intro, they might not have a good understanding.
00:21:37.230 --> 00:21:41.029
Most people don't have a good understanding of digital privacy.
00:21:41.039 --> 00:21:54.690
I just think that before you dive into using these tools, you should have a good foundation of data sharing and data collection and you should have examined some cases of where things have gone wrong, data breaches and things like that.
00:21:54.690 --> 00:21:58.920
You should have an idea of what kind of things could go wrong.
00:21:58.920 --> 00:22:13.380
If they're coming to me and they're asking me about cheating because they're worried about cheating, I usually try to do some damage control around helping them to move away from punitive approaches because I don't think they really do any good.
00:22:13.710 --> 00:22:20.670
At the end of the day, I think they just degrade our students' trust in us and our students' trust in higher education.
00:22:20.670 --> 00:22:37.079
And I guess I try to talk to the instructor and remind them how much is really built on that trust, how much of education comes from that place, and help them to realize that they're sacrificing so much more.
00:22:37.079 --> 00:22:54.779
If they take a punitive approach, they're sacrificing so much more than they would be if they took a more open approach, trying to understand where the students are coming from and trying to figure out how this really aligns with their outcomes and the things that they're trying to do in their course.
00:22:54.779 --> 00:23:04.740
So I usually bring it back to some type of helping them to articulate some type of policy for their syllabus, because it all comes back to expectations, right?
00:23:04.740 --> 00:23:27.630
It all comes back to them really thinking about in their heart and what's going on with them, their expectations for the course, the affordances, the tools like ChatGPT and DALL-E and all of these other generative tools can afford students and helping them to articulate to students why it's important and what they learn in the process.
00:23:27.990 --> 00:23:34.289
In terms of ChatGPT, it's not a matter of we want to create essays.
00:23:34.440 --> 00:23:35.789
That's not the point.
00:23:35.789 --> 00:23:38.019
If that's the point, we're doing it wrong.
00:23:38.049 --> 00:23:38.650
Right?
00:23:38.670 --> 00:23:42.930
The point is thinking through and being nuanced in your thinking.
00:23:42.930 --> 00:23:56.099
So nuanced in your thinking that you're putting it down on paper or on a screen and you're scrutinizing and evaluating every word, every paragraph, every sentence to make sure that things fit together and flow together.
00:23:56.099 --> 00:23:57.630
It's that process of writing.
00:23:57.630 --> 00:24:11.880
It's not the product of the essay and helping faculty to have that conversation with their students and helping faculty to articulate that meaning to their students in a way that helps the student to understand, I think is so much more powerful than wagging your finger.
00:24:11.880 --> 00:24:13.890
And if you do this, we're going to punish you.
00:24:14.609 --> 00:24:15.660
I'm going to turn it over to Lance.
00:24:15.660 --> 00:24:16.920
Let him talk about it a little bit.
00:24:17.190 --> 00:24:18.029
100%.
00:24:18.390 --> 00:24:20.069
Everything Autumm just said.
00:24:20.160 --> 00:24:29.220
I think the only areas I would add is I think there's some great value in them using it to enhance some of their own work.
00:24:29.220 --> 00:24:33.990
And I think that's great with the caveats of the potential concerns around privacy that we've already mentioned.
00:24:33.990 --> 00:24:44.309
I think if they are going to do that, I think it is important for them to also be citing and identifying where their course, where their thinking is influenced.
00:24:44.309 --> 00:24:51.210
And I come from this having worked with faculty who have done the things that they don't like, that they don't like their students to do.
00:24:51.210 --> 00:24:57.039
And so just really demonstrating transparency again in how they're using it with their students.
00:24:57.059 --> 00:25:11.250
The other thing that comes to mind in using it is and this is something, again, from conversations with Autumm, is really emphasizing, no matter what they think of it right now, I'm going to, going to take the quote from you Autumm.
00:25:12.269 --> 00:25:16.200
This is the, quote unquote, dumbest that AI is going to be.
00:25:16.230 --> 00:25:20.089
So I see a lot of dismissal and I see a lot of it's fine, like it's fine.
00:25:20.099 --> 00:25:21.299
I'll catch them anyways.
00:25:21.700 --> 00:25:25.769
And there's a whole other discourse around that approach or around those concerns.
00:25:25.769 --> 00:25:36.089
But I think undermining it or not recognizing like now with this research preview, it is getting better because we're all training it to be better.
00:25:36.450 --> 00:25:40.289
And I think within that is really highlighting what I'm starting to see.
00:25:40.289 --> 00:26:08.059
And I want to say, is Anna Mills and a couple other folks have, Maha Bali I think, has done this as well where they they're sharing their dialogs and you're seeing through the questions in the further development in iterations of their questions like the actual dialog, you get some really interesting cool things and I think that's a thing that is powerful and interesting and valuable for for faculty and for their students to be thinking about.
00:26:08.069 --> 00:26:19.380
I'm influenced by Warren Berger, who's written a couple of different books about questions, and I think this is one of those opportunities for us to really think about the power of questioning and what you need to ask good questions.
00:26:19.380 --> 00:26:34.109
And so there's, there's something within this that I think is a possibility for no matter the discipline to really think about how like, how do we ask good questions, how do we ask meaningful questions and how do we refine questions as a means of seeking knowledge.
00:26:34.109 --> 00:26:39.809
But in order to do that, we also have to demonstrate some understanding in order to ask those deeper questions.
00:26:39.809 --> 00:26:46.349
And I think there's a really rich opportunity there to explore within all of this as well, from both faculty and student side.
00:26:46.710 --> 00:26:59.130
Yeah, that was part of what I was thinking with instructional design and with my students is it is even in order to use this effectively as a tool, you need to know what questions to ask.
00:26:59.279 --> 00:27:03.420
And it's the same thing when you're doing analysis in instructional design.
00:27:03.420 --> 00:27:07.079
When you start, you need to know what the important questions are, right?
00:27:07.079 --> 00:27:08.490
Is this a training problem?
00:27:08.910 --> 00:27:11.369
Who are the students? What are the characteristics?
00:27:11.369 --> 00:27:19.109
Like all of these different analyses things are the questions you need to ask, and if you don't know what those questions are, the tools are not useful.
00:27:19.119 --> 00:27:26.339
And so I think there is an inherent skill in learning how to ask the tool the right questions.
00:27:26.880 --> 00:27:27.930
I think there is.
00:27:27.930 --> 00:27:33.059
And it's also different even though it's very, very smooth.
00:27:33.269 --> 00:27:33.779
Right.
00:27:33.779 --> 00:27:35.309
And it sounds very human.
00:27:35.309 --> 00:27:43.960
There is a big difference between asking a question of a human and asking a question of a large language model like ChatGPT.
00:27:44.339 --> 00:27:57.869
If anybody is more interested in this, I was blown away with the prompt engineering stuff that's out there, which is all about how to ask it questions and understanding the different ways that you can ask it questions, which can be.
00:27:58.079 --> 00:28:05.700
This was really interesting to think about how you interface with it and how it's different than maybe interfacing in a human conversation.
00:28:06.359 --> 00:28:18.779
This is probably of no value, but this whole conversation, just like it just had me flashback to Hitchhiker's Guide to the Galaxy when they're waiting for the answer to life, the universe and everything.
00:28:18.869 --> 00:28:24.210
Like, I feel like there's like there's something there for this conversation as well.
00:28:25.890 --> 00:28:26.940
It's the same dynamic.
00:28:27.329 --> 00:28:32.849
Looking for all the right answers are not necessarily the right questions or realizing what the machine is really built for.
00:28:33.509 --> 00:28:40.259
Lance you mentioned something interesting that I think is caused an interesting conversation on Twitter as well, and that's around citing.
00:28:40.799 --> 00:28:54.809
And I actually brought it up a little bit in a from a blog post that Maha Bali had put together, challenging not to anthropomorphize a computer system, but that's worth citing.
00:28:54.960 --> 00:28:56.490
Are we not just doing that?
00:28:56.730 --> 00:28:57.990
How does that make sense?
00:28:58.289 --> 00:29:06.240
I guess I would say I don't know that the citing itself is what anthropomorphizes the tool.
00:29:06.509 --> 00:29:09.630
I think there's lots of other ways we're doing that.
00:29:09.809 --> 00:29:23.160
And so citing might feel like one part of that conglomeration, I would say citing it in the traditional sense of citing, it feels like the fix for now as we're still trying to figure things out.
00:29:23.160 --> 00:29:29.160
I think all of it hearkens to trying to make explicit where information comes from.
00:29:29.549 --> 00:29:32.009
I think citing is a good start.
00:29:32.369 --> 00:29:42.630
I think if we were to lessen or try to detract that or deanthropomorphize it, it makes me think about, what is it...
00:29:42.630 --> 00:29:47.759
Phipps, the article again, it is something Autumm has shared with me in our conversations.
00:29:47.759 --> 00:30:09.089
Phipps and Lanclos citation approach, which is like you identify that you were using this, and that you understand the repercussions of using a tool that works, that is in part built off of like the illegal copying or use of copyrighted works and also the various exploitated labor.
00:30:09.420 --> 00:30:11.579
I feel like that's a way of threading.
00:30:11.630 --> 00:30:13.190
It's like you're citing it.
00:30:13.220 --> 00:30:15.690
You're citing where this information came from.
00:30:15.690 --> 00:30:23.420
And because you cannot tie it to individuals, you also recognize that tool is an exploitative tool of sorts.
00:30:23.599 --> 00:30:29.029
I think that's I think in my head that's one way I've been thinking about or would think about in this context.
00:30:29.299 --> 00:30:39.920
They offer that citation approach, I think slightly, and just to be provocative and it's something like, nope, I think that's what I will be using and will be encouraging others to use.
00:30:40.190 --> 00:30:44.990
We can't just hide behind a citation because I think maybe that's what it is.
00:30:45.740 --> 00:30:50.930
It doesn't anthropomorphize necessarily, but it hides.
00:30:51.559 --> 00:30:59.750
It hides what really goes into that answer, both technically and human cost.
00:31:00.230 --> 00:31:00.490
Yeah.
00:31:00.500 --> 00:31:08.089
So I do have a blog post pulled up and I can read the citation example that Phipps and Lanclos propose.
00:31:08.099 --> 00:31:13.640
So this is what they're proposing as a potential citation.
00:31:13.640 --> 00:31:21.650
And they say we offer the following text not because we think it, but the relevant people will actually use it, but because we think that they should.
00:31:21.829 --> 00:31:29.390
And so it's this presentation paper work was prepared using ChatGPT, an AI chat bot.
00:31:29.660 --> 00:31:41.539
We acknowledge that ChatGPT does not respect the individual rights of authors and artists and ignores concerns over copyright and intellectual property in the training of the system.
00:31:41.569 --> 00:31:49.190
Additionally, we acknowledge that the system was trained in part through the exploitation of precarious workers in the global South.
00:31:49.279 --> 00:31:53.509
In this work I specifically use ChatGPT to...
00:31:53.509 --> 00:31:58.099
then they have some ellipses where you would fill in the way that you actually used the work.
00:31:58.849 --> 00:31:59.750
It's powerful.
00:31:59.779 --> 00:32:00.940
It's really powerful.
00:32:01.250 --> 00:32:04.640
It really makes you stop and think, Should I actually use it?
00:32:04.640 --> 00:32:08.059
If I'm going to acknowledge all of these horrible things about it?
00:32:08.359 --> 00:32:10.069
I'm not sure that people would.
00:32:10.069 --> 00:32:12.349
Lance is saying, Lance is embracing it.
00:32:12.349 --> 00:32:14.849
And I think that's amazing, right?
00:32:14.869 --> 00:32:15.619
But I think.
00:32:15.980 --> 00:32:19.609
It also means I'm probably an irrelevant person rather than a relevant person.
00:32:21.099 --> 00:32:24.789
Oh! I don't know if you are, though.
00:32:24.799 --> 00:32:25.809
I don't know if you are, though.
00:32:25.819 --> 00:32:29.119
I think what they mean by that, people who would use it.
00:32:29.420 --> 00:32:35.359
And so if you're willing to use something like that, I think that definitely says something.
00:32:35.420 --> 00:32:40.460
I proposed in talking with them about the article, so there is probably I need to put this disclaimer out there.
00:32:40.460 --> 00:32:50.839
And if you go to the article, if you go to the blog post, you'll see at the top they acknowledge that I had some input on this, just I didn't write a word blog post, none of it.
00:32:51.289 --> 00:32:52.700
But we had some conversations.
00:32:52.700 --> 00:32:58.589
We had some conversations about citation and about different approaches to citation.
00:32:58.589 --> 00:33:23.160
And one of the things I put forward is you could use this as activism if you really felt very strongly the ethics of these systems and you wanted to make a point, you could add a citation like this to your presentation or your paper or whatever, and then just have a use of ChatGPT that is so minimal, right?
00:33:23.160 --> 00:33:27.000
Like I used it like a thesaurus and I changed out this one word.
00:33:28.019 --> 00:33:34.529
So I used it just so that you could use the citation to point out the abuses that can happen through it.
00:33:34.529 --> 00:33:35.700
It's really powerful.
00:33:35.700 --> 00:33:39.029
It could be used in lots of different kind of ways.
00:33:39.329 --> 00:33:43.740
It's also so powerful because it's using the very thing that ChatGPT obscures.
00:33:43.740 --> 00:33:47.460
So ChatGPT obscures citation, it fabricates citation.
00:33:47.460 --> 00:33:50.279
We don't know what is inside of these language models.
00:33:50.670 --> 00:33:53.519
More than likely, there is copyrighted work in there.
00:33:54.059 --> 00:33:55.500
We don't know that for sure.
00:33:55.500 --> 00:33:59.039
It's just we really don't know what's inside of the language that it's trained on.
00:33:59.039 --> 00:34:14.219
And so this in a way, weaponizes the idea of citation to really speak back to and bring some light and bring some acknowledgment to some of the darker things around this, around this particular tool.
00:34:15.119 --> 00:34:16.860
I think that's fascinating.
00:34:16.918 --> 00:34:22.409
I like the power in that citation, that opening citation.
00:34:22.829 --> 00:34:47.760
One of the ways that I've been using it, which is totally not using it as a data lookup, I have text that's in past tense that I need to move to present tense and it's making it a whole lot faster for me to write it because I can take the stuff that I wrote in past tense, plug it in and say, give me this in present tense, and then I can work with the present tense version that it gave me.
00:34:48.239 --> 00:34:53.010
And because I wrote the past tense, I own the present tense.
00:34:53.010 --> 00:34:54.719
It's just saving me time.
00:34:54.989 --> 00:34:57.539
So again, I'm using it strictly as a tool.
00:34:57.539 --> 00:35:02.159
Now I'm questioning how it is now taking that data.
00:35:02.159 --> 00:35:09.929
And I found it did do that to me because I had asked it a question about a town that we visited called Harrington Harbor.
00:35:10.469 --> 00:35:15.210
And originally it said that this place didn't exist and there was no knowledge of it.
00:35:15.809 --> 00:35:21.630
And then later, when I asked it about Harrington Harbor, it came back and quoted what I had written about it.
00:35:22.199 --> 00:35:22.639
Right.
00:35:22.860 --> 00:35:24.340
So it's like that.
00:35:24.360 --> 00:35:40.829
Oh, now your database thinks Harrington Harbor is the information that I just fed you about Harrington Harbor, which actually shows you where it's getting the information from and it isn't even fact checking it.
00:35:41.070 --> 00:35:52.949
You can't argue like Wikipedia has systems in place where things can be at least somewhat quality controlled in some way, or at least say whether it's been quality controlled or not.
00:35:52.949 --> 00:36:01.889
And fair because ChatGPT is a black box there's no looking inside to see where the information came from.
00:36:02.429 --> 00:36:03.539
I think that's fascinating.
00:36:03.690 --> 00:36:11.000
Just on going back to the point that it's changing all of the time, right?
00:36:11.010 --> 00:36:36.300
And like it seems like every single day there's a new thing coming out, speaking to what you're talking about Rebecca Amazon is now warning their employees to stop using it because they're seeing some of their, like trade secrets in terms of coding, showing up in answers from ChatGPT because they're using ChatGPT to help them code.
00:36:36.420 --> 00:36:47.489
And so the ChatGPT is not keeping those secrets and is then absorbing that and then sharing that with other users who are out there.
00:36:47.489 --> 00:36:56.309
It just put a link in the chat that you can maybe link in the show notes, but yeah, yeah, because it's a learning machine.
00:36:56.309 --> 00:37:02.849
We've been talking about learning technologies and it's coming back to ID stuff and instructional design and technologies.
00:37:02.849 --> 00:37:05.070
For years we've been talking about learning technologies.
00:37:05.070 --> 00:37:08.760
We haven't been talking so much about technologies that learn, which is a little bit different.
00:37:10.889 --> 00:37:12.630
This makes me so happy in some ways.
00:37:12.630 --> 00:37:18.369
I'm not going to like there's a lot there that there is some Schadenfreude going on right now.
00:37:18.389 --> 00:37:22.289
I'm not going to lie to the point about the responses.
00:37:22.769 --> 00:37:24.139
This is it.
00:37:24.239 --> 00:37:26.579
If it gets edited out, I completely understand.
00:37:26.670 --> 00:37:32.070
But I dropped this line this week when we were having a discussion about it.
00:37:32.320 --> 00:37:43.320
This just came to my head like, like fluid is that ChatCPT responds with all of the self-confidence of a mediocre white dude.
00:37:43.739 --> 00:37:49.019
It just does and I just ever since that came to mind, that's all.
00:37:49.019 --> 00:37:49.250
Okay.
00:37:49.260 --> 00:37:55.230
I can only hear ChatGPT responses and the voice of somebody named Brad.
00:37:57.199 --> 00:37:57.559
Yeah.
00:37:58.219 --> 00:38:00.349
Sorry to all of the Bradleys out there, right?
00:38:00.409 --> 00:38:00.840
That's right.
00:38:00.860 --> 00:38:01.280
That's right.
00:38:01.489 --> 00:38:02.179
Disclaimer...
00:38:02.179 --> 00:38:03.280
I think it's Chad, actually.
00:38:03.289 --> 00:38:03.630
I'm sorry.
00:38:03.659 --> 00:38:04.670
ChadGPT.
00:38:05.570 --> 00:38:10.489
Because we were talking about it in the context of its errors and things like that.
00:38:10.760 --> 00:38:13.610
And that came to me.
00:38:13.610 --> 00:38:15.380
And it just it sticks with me now.
00:38:15.409 --> 00:38:17.690
And that's all I can think about now is.
00:38:17.690 --> 00:38:20.269
I love it.
00:38:21.199 --> 00:38:25.610
I'll ask one more sort of question in this area and then I think we'll close off.
00:38:25.610 --> 00:38:31.449
And that is we've talked about guidance for students and guidance for instructors.
00:38:31.460 --> 00:38:33.019
What about instructional designers?
00:38:33.989 --> 00:38:37.349
What do you think instructional designers should be doing with this technology?
00:38:37.820 --> 00:38:45.000
Well, the first blog post that I wrote on this topic was actually me wondering if it could be an instructional designer.
00:38:45.809 --> 00:38:49.590
There's going to be labor implications of this technology, I think everybody.
00:38:50.639 --> 00:38:52.590
Everybody is clear on that, right?
00:38:52.679 --> 00:39:08.079
OpenAI is doing research right now to try to better understand the labor implications because their mission, they say, is to make sure that AI is basically a net positive in the world rather than a negative in the world.
00:39:08.099 --> 00:39:17.610
And so they recognize and realize this is going to have labor implications and trying to foresee and understand that is really important if we're going to be responsible or something like this.
00:39:18.059 --> 00:39:18.960
So I was just curious.
00:39:18.960 --> 00:39:21.800
I was just curious if it could, like, do my job.
00:39:21.809 --> 00:39:28.170
So I went in and pretended that I was a physics professor, which I know nothing about physics.
00:39:28.170 --> 00:39:39.349
I couldn't ask any discipline specific kind of questions, but I just asked really general questions about my department chair wants me to take my learning online and I'm skeptical about it.
00:39:39.360 --> 00:39:41.869
I don't know if this is really for me.
00:39:41.889 --> 00:39:46.380
And just tried to see what it was, what kind of answers that it would give me.
00:39:46.389 --> 00:39:51.300
So going back to the idea of prompt engineering, one of the fun things you can do is role play with it.
00:39:51.300 --> 00:39:53.269
You can ask it to role play with you.
00:39:53.280 --> 00:40:08.579
And so I started off by saying, You are an instructional designer and I'm an instructor and you, if anything, I think that's an interesting approach because I do think that there is a lot of very standard answers in instructional design.
00:40:08.579 --> 00:40:19.139
There's a lot of best practice that it's fine, I guess, but I've always pushed back against it because I think I'm not convinced that it is best practice.
00:40:19.139 --> 00:40:21.599
I don't know who really makes that decision.
00:40:21.630 --> 00:40:23.329
There's just a lot of it out there.
00:40:23.340 --> 00:40:35.369
And so I think it's kind of interesting just to see what kind of vanilla answers it gives you to instructional design problems and then say, okay, well can we be more creative than that?
00:40:35.880 --> 00:40:43.289
Can we go beyond this knowing that these are maybe some of the most generic answers that are out there?
00:40:44.010 --> 00:41:14.010
So for ID folks, I mean, I think it's one of those like really having to spend some time playing with it, whether it's ChatGPT or really any of these tools, both to understand their limitations and possibilities and evolution and to be prepared for the questions that they will get from faculty where I see it impacting potentially ID the most is probably in a lot of the
00:41:14.250 --> 00:41:15.030
OPMs.
00:41:15.030 --> 00:41:16.230
You're thinking about OPMs.
00:41:16.800 --> 00:41:22.199
OPMs I can see the large scale online institutions.
00:41:22.199 --> 00:41:41.400
Your SNUs, your ASUs, your Western Governor's looking to leverage this in a way that reduces the amount of instructional design folks that they rely upon or that they contract out and using this as more systematic means of updating their courses.
00:41:41.610 --> 00:41:50.670
I can see the pathways to that because in some ways it feels very much like textbooks, textbook publishers in their methods.
00:41:50.909 --> 00:41:56.639
We've got to sell more books, and so we've got to come up with a new edition every two years and we'll just switch the chapters around.
00:41:56.699 --> 00:42:01.619
There's some ways I can see some of the larger scale ones being like, We've got to refresh our courses.
00:42:01.619 --> 00:42:06.750
So hey, ChatGPT update it with this kind of flavor.
00:42:07.590 --> 00:42:08.119
Like I could...
00:42:08.130 --> 00:42:14.400
I can see a series of APIs and plug-ins being used to like do a lot of that.
00:42:14.699 --> 00:42:31.920
I think that's and so I would say anybody that is in that space just understanding it and seeing where that starts to pop out because I just have trouble not believing the ways in which those larger entities work on this like assembly line.
00:42:31.920 --> 00:42:39.510
And efficiency is always the better answer than anything else that they aren't going to start thinking about it and using it.
00:42:39.570 --> 00:42:54.119
I think another big role for instructional designers right now too, and I say this on January 30th of 2023 because it's changing all the time, like tomorrow, like it's going to be different.
00:42:54.119 --> 00:42:58.599
I think your administrators need guidance on top of your instructors.
00:42:58.599 --> 00:43:02.519
Your instructors are going to be coming to you and asking you for help with this.
00:43:02.670 --> 00:43:05.400
Just all the different roles of the instructional designer.
00:43:05.429 --> 00:43:10.199
There's the role of you as a content creator and as a designer who's creating stuff for people.
00:43:10.199 --> 00:43:24.719
There's the role of you as somebody who gives advice to faculty, but then most of us have either interactions with some type of administration or we have a director who has direct access to administrators.
00:43:24.719 --> 00:43:27.480
And I think all of us are very busy.
00:43:27.510 --> 00:43:29.760
We have a lot going on, right.
00:43:29.760 --> 00:43:35.639
And we don't have necessarily all the time in the world just to concentrate on generative AI.
00:43:36.150 --> 00:43:59.219
So I think they're going to be coming and asking for advice and asking for guidance in terms of what to do with all of the social change that's going to be happening around what the impact of these tools is going to mean, so just educating yourself and keeping on top of that stuff that's changing, even if you can't stay on top of it for every single day because it is changing every single day.
00:43:59.230 --> 00:44:16.699
If you can stay on top of it once a week, once every two weeks, whatever, to kind of keep your eye on what is happening and how it's changing, I think that it's going to be really important for those who will be coming to you and asking you for advice, which will be faculty, but more than likely it will be administrators, too.
00:44:16.719 --> 00:44:22.929
And I think there's an interesting point about whether or not it could replace instructional design.
00:44:23.349 --> 00:44:39.550
I don't think it can, but I do think it does some things very interestingly, and that's I've been asking it all of the questions, like I've generated some chapters from my textbooks, but I'm using it saying, okay, here are the questions I want this chapter to answer.
00:44:40.119 --> 00:44:40.900
What do you say?
00:44:40.929 --> 00:44:41.949
And then it gives me an answer.
00:44:41.949 --> 00:44:43.510
And I'm like, actually pretty good.
00:44:43.659 --> 00:44:44.409
I'll take that.
00:44:45.579 --> 00:44:51.579
Hey, I will say, and should I say this, and let's say this, just say it.
00:44:51.760 --> 00:45:03.380
I will say I wrote that first blog post trying to figure out if it would, if it could replace me with a little bit of a little bit of tongue in cheek, little bit of haha thing.
00:45:03.670 --> 00:45:12.820
But then I realized the larger discourse of people who really are looking at the potential impacts are not thinking about that.
00:45:12.829 --> 00:45:15.849
They are thinking about whether it could replace teachers.
00:45:17.380 --> 00:45:23.920
So instructional designers, without teachers, that's a really scary prospect if you ask me.
00:45:24.070 --> 00:45:27.340
And that's the bigger thing to be concerned with.
00:45:28.210 --> 00:45:31.420
Yeah, 100%.
00:45:31.929 --> 00:45:33.639
Do you think that's where it's going?
00:45:33.670 --> 00:45:54.059
I think the thing I see is and this is the it's the thing that with whether it's AI or it's robots, that that seems to be sometimes missed or under considered is like I hear folks being like there's some jobs, that robots or AI won't ever replace that's not they'll replace them en masse.
00:45:54.070 --> 00:46:08.019
What it will mean is that you as an individual instructional designer or plumber or whatever your profession, you will be able to do a lot more, more quickly.
00:46:08.199 --> 00:46:16.000
And so if previously you were only able to work with ten faculty, you can now work with 20 or you can work with 100.
00:46:16.179 --> 00:46:18.320
That's the thing that I'm seeing.
00:46:18.340 --> 00:46:32.679
So it's not that you replace all instructional designers, but it means one like the expectation of one instructional designer will be much more expansive or be much more expected than what it was previously.
00:46:32.679 --> 00:46:41.980
And like, we see that within our technologies, every tech like we have over the last 50 years, almost all workers have become increasingly way more productive.
00:46:42.039 --> 00:46:45.400
But we keep asking more and more of them and of course, paying less and less of them.
00:46:45.760 --> 00:47:01.489
And so I think that's the thing, is what this shows, or what this creates the opportunity to, is like now instead of and I've seen and was playing around with this in December as well when I was doing some advising, I was like, What if I use the machine to help me get started?
00:47:01.510 --> 00:47:08.400
So rather than spending 5 hours of like hemming and hawing, I used it as a like, let's see what I can get here and start running more quickly.
00:47:08.409 --> 00:47:12.000
And I think that is where the challenge is.
00:47:12.019 --> 00:47:13.869
It's not going to be replacing all.
00:47:13.869 --> 00:47:17.349
It's just going to make the need for this fewer and fewer.
00:47:17.380 --> 00:47:29.019
And I think when we talk about replacing teachers, like to me in many ways, the big scale instructional places that have 130,000 students, they pretty much replace teachers there.
00:47:29.110 --> 00:47:29.440
Right.
00:47:29.530 --> 00:47:32.559
If you teach at those schools, you're not doing curriculum.
00:47:32.679 --> 00:47:35.559
You are grading and you are doing discussions.
00:47:35.559 --> 00:47:40.800
And I think they're doing that because they need to at least justify that you actually have an interaction with a human.
00:47:40.809 --> 00:47:48.670
Well, yeah, they will replace those, but meanwhile they can also much of their staff is not faculty, but is actual staff like instructional designers.
00:47:48.670 --> 00:47:51.849
And now it's like, Oh, we can maybe even do less.
00:47:51.849 --> 00:48:00.369
And so I think I don't want to be like, Oh, we're all doomed because of robots and AI But I think that is the threat that they pose.
00:48:00.369 --> 00:48:03.610
And I think in industries we can start to see that happening.
00:48:04.539 --> 00:48:05.110
That's right.
00:48:05.530 --> 00:48:17.320
And yeah, I don't know if it I also don't want to jump on the robots are coming for our jobs pedestal like we know that doesn't end well.
00:48:17.619 --> 00:48:19.420
And it's never 100% true.
00:48:19.420 --> 00:48:23.400
But what you just talked about, Lance, is job loss, right?
00:48:23.409 --> 00:48:24.570
It's job shifting.
00:48:24.579 --> 00:48:34.510
If we have 50 instructional designers right now and each one of them are working with ten instructors, if each one of them can work with 50 instructors.
00:48:34.809 --> 00:48:37.949
Yeah, that's a different situation.
00:48:38.489 --> 00:48:41.829
It will be interesting to see how it plays out.
00:48:41.840 --> 00:48:44.530
I guess the big takeaway is nobody really knows.
00:48:44.530 --> 00:48:49.030
But one thing that we do know is that there will be some kind of labor implications.
00:48:49.150 --> 00:48:52.360
There could also be job creation around this as well.
00:48:52.420 --> 00:48:52.880
Right.
00:48:52.900 --> 00:49:03.650
Knowing people who know prompt engineering or who know how to train a language model, those kind of things could end up being something that are marketable skills that we might need going forward.
00:49:03.670 --> 00:49:13.389
So I don't want to paint it as all gloom and doom, but there will probably be upset and there will probably be some reskilling that is needed and there will probably be big changes.
00:49:13.420 --> 00:49:24.179
I want to say thank you to both of you for coming in and joining this little thought experiment around ChatGPT and what it might be doing this semester.
00:49:24.190 --> 00:49:42.130
I am really curious to see how all of this is going to play out and where we're going to be at come September, right when we go into another semester after having had the summer as well and a little bit more time for things to play out.
00:49:42.130 --> 00:49:46.869
But thank you very much for your willingness to come on and chat with me about Chat.
00:49:47.590 --> 00:49:49.090
Thanks so much for having us, Rebecca.
00:49:49.510 --> 00:49:49.989
Thank you.
00:49:51.130 --> 00:49:57.340
You've been listening to Demystifying Instructional Design, a podcast where I interview instructional designers about what they do.
00:49:57.940 --> 00:50:05.110
I'm Rebecca Hogue, your podcast host. Show notes are posted as a blog post on Demystifying Instructional Design dot com.
00:50:05.559 --> 00:50:07.960
If you enjoyed this podcast, please subscribe or leave a
00:50:07.960 --> 00:50:09.849
comment in the show notes Blog post.
