Demystifying Instructional Design
Demystifying Instructional Design
Episode 32 with Jeremy Tuttle: Balancing Innovation and Practicality when using AI in Instructional Design
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Unlock the secrets to harnessing the power of generative AI in instructional design with our special guest, Jeremy Tuttle, Director of Learning Design at Niche Academy. Jeremy shares his firsthand experiences using tools like ChatGPT and Adobe Illustrator, revealing practical insights on their applications and limitations. Learn why creating effective learning materials still demands significant human intervention for editing and fact-checking, and discover the challenges of aligning AI-generated images with specific design needs.
As we explore the broader landscape, we draw intriguing parallels between the current AI integration process and the early days of UX/UI design. Hear about the balance required between pushing the boundaries of innovation and maintaining practicality, underscored by a nostalgic anecdote about the evolution from MySpace's customizable pages to today's streamlined interfaces. We also delve into future trends such as learner personalization, chatbots, and the critical role user feedback plays in refining AI applications.
Finally, we tackle the ethical dimensions of using AI in creative fields. From the necessity of artists' consent and fair compensation to the complexities of AI training pools, we leave no stone unturned. Drawing a provocative analogy to the Napster era, we question the implications of AI-generated art on the value of creativity. This episode is a compelling exploration of the intersection between technology and artistry, advocating for stronger protections to ensure art continues to thrive in the age of AI. Join us for an essential conversation that challenges and enlightens.
Please consider making a donation to my Patreon account to help support this podcast financially: patreon.com/rjhogue
Welcome to Demystifying Instructional Design. This is the new season and this season we're going to focus on the use of generative AI, in particular, in instructional design. Welcome, jeremy. Can you start by introducing yourself?
Jeremy Tuttle:Yes, First of all, thanks for having me back. I was in the last season and I had a great time and I'm so thankful for thanks for having me back. I was in the last season and I had a great time and I'm so thankful for you to invite me back. I'm Jeremy Tuttle, I'm the Director of Learning Design for Niche Academy and I lead a fantastic team in the creation of many, many tutorials.
Rebecca Hogue:When we last talked, chat GPT was just starting and you said you were going to wait until chat GPT-4 came out before you tried it out. My question is how did that go? Did you try it out? Do you use it?
Jeremy Tuttle:Yeah, yeah, we tried it out and it did a great job with the text generation side of things that we were looking at, but it didn't quite meet our needs in the way that we thought it would.
Jeremy Tuttle:We have a very particular style in which we write and we have very specific goals that we want to hit as we're putting together our learning material, and when we asked ChatGPT to spit out something to help us in our process, we found that we were spending more time editing what had been spat out to bring it into our style and then also spending more time fact-checking the information than if we had just done it ourselves. So we don't use it to generate learning material, but we have used it to generate scenarios. You know, if we're going to ask a learner to think about a certain situation that they might be put in in regards to the topic at hand, an easy example would be you're working with an angry customer and you need to do X, y, z as part of the process. Instead of trying to envision what an angry customer could be, you could just ask ChatGPT write up a script of a customer who's angry about this thing and then it'll spit out three or four paragraphs describing how this angry customer is angry and that has saved us time.
Rebecca Hogue:That's interesting because I heard that as well, the idea of scenarios, but I wasn't quite sure how you would use it. I have Notions I pay for the intelligent version of Notion with the AI in it, and I asked it what questions to ask, and the first question it gave me was how has AI influenced your approach to instructional design?
Jeremy Tuttle:Good question. As of right now, it hasn't, because I see AI as something that's alongside me, not something that's leading me, so my process hasn't really changed. I just now occasionally go to it for help with ideas or as a sounding board, more than something that's going to dramatically change my process.
Rebecca Hogue:And we talked a little bit about the text generation. Do you use it for any image generation?
Jeremy Tuttle:So that's another thing where we have a very specific style that we have and the files that we create for our imagery are then used for animation. So they have to have layers in specific spots so that our animators can find the thing that they need to animate and then use it effectively. If you generate an item in Adobe Illustrator, it might look good, but when you dig into the layers it's a mess.
Rebecca Hogue:Okay, I was going to ask you about Adobe Illustrator because, yes, chatgpt4 can create images. I use it to create feature images for some of my blogs, but in instructional design, we're more likely to be using illustrations and using Adobe Illustrator, and they have this new beta adding in backgrounds as well as icons, and so you're saying that the backgrounds that they add are just sort of a mess.
Jeremy Tuttle:Oh. So the way I like to describe it is that if you want to take what it provides you wholesale, it's great. If you just want to take what you see and run with it, it does its job. But if you need to edit it in any capacity the way that the file is built, the way that the layers are organized, the way that the groups are grouped together it becomes a real hassle to try to get the image to look the way you want it to look.
Jeremy Tuttle:For the example, this wasn't as part of my work, but just a side project that I was doing. I was in a play and we needed a logo for a sporting goods store. So I was thinking this play is set in Minnesota. People like to fish. Why not have this sporting goods store be like a fisherman's and a hunting sporting goods store? So I asked Illustrator to generate a logo that would include a fish in some capacity, and it spat out this beautiful I believe it was a bass jumping out of the water.
Jeremy Tuttle:It had lovely splash marks, it looked good, but it was far too busy to be believable as a logo. It had way too much detail. So I wanted to go in and just remove a little bit of the detail. So I click into layer one and there are, out of 200 layers or so, group one, 200 layers, and so I have to go find this shape, delete that shape, this shape, delete that shape. But they're these little tiny specks everywhere. So, try, trying to bring it down to be a more simple one, and even if I prompted it to give me simplify it, simplify it, simplify it, didn't matter. I still had that issue. So if I want to create something that I'm going to work with and on, I feel it's still easier to start from scratch than it is to take something and try to mold it and push it into something that I feel I need.
Rebecca Hogue:And have you tried any of the video creator stuff?
Jeremy Tuttle:So I know in Adobe Premiere they have a couple really good tools like the Remix tool. If you're working on video and you're in Adobe Premiere and you're going to put music down on your video, use the Rem remix tool. What it does is you can stretch a song longer or you can shrink a song shorter, but it will always end on the end of the song and it will find ways to stitch the song at good specific spots so that as you're listening to it, you can't tell that there was a transition applied within the music as you shrunk it or stretched it.
Rebecca Hogue:That sounds super handy.
Jeremy Tuttle:It is incredibly handy. One of the things when I was doing video editing a lot in my prior job, I was really good at stitching music together in that in that way, I play a lot of musical instruments. I love music, so I could find the beat. I could cut on the beat, pull it together. If it didn't sound quite right, I could add a little bit of a crossfade so that it blended the cut a little bit and it took me probably five minutes five to 10 minutes per video doing that. But with the remix tool you just go. I wanted this long. Then it processes for maybe 15 seconds and it's done and all the ones that I've checked it sounds immaculate. So highly recommend the remix tool. There are other tools. I have a list up on my other screen so I don't forget. They have other tools like auto reframe, which, if you're filming your, your training, that could be helpful, but it's not that difficult to reframe yourself, so adjusting the scale of the image and then changing the position to sit where you want it to be.
Rebecca Hogue:Yeah, I don't find that a particularly difficult task.
Jeremy Tuttle:Removing the background was an interesting one yeah, and that's been available in After Effects for quite some time Using keying effects. Traditionally, you would auto key using the color green or the color blue. I'm probably diving way too deep into video production here for this audience, but taking that same technology, you don't always have to do green, you don't always have to do blue. So is now that we have uh, what's it called? I can't remember what it's called, but it it can detect lines in pixels, so the shape of my head produces a line compared to the background. As long as the system can identify where that line is, it can easily pull everything else out. So it's a good thing that they're adding it to Premiere.
Rebecca Hogue:Yeah, and actually if you're recording on things like Zoom, you just ask your audience or you're recording people to use a green screen background, which I thought was a very interesting thing. You just use, change the background to green and you have a green screen.
Jeremy Tuttle:Yep, there you go, there you go, done.
Rebecca Hogue:So can you provide some examples of projects where AI was particularly useful?
Jeremy Tuttle:Yes, one of our instructional designers was working on a project for working safer hours. It's part of our OSHA series making sure that people understand what safe work hours is and this is one of the times where she could not quite envision a specific scenario where a manager who's in charge of setting a schedule could look at the situation and then react to it. So she asked chat gpt uh, provide me a scenario where an employee is working unsafe work hours. Just give me that. And she was given a story. She was able to change some of the details, but it, she said, it saved her three hours worth of time and effort trying, because she just felt like she was hitting a wall. She didn't have the creative spark at that moment in time to put that kind of a story together, so that that's one instance where it came in handy.
Rebecca Hogue:It sounds like that is the most common use from instructional designers right now is in that, creating dialogue or creating scenarios that you know. Act as that other person and tell me what you think.
Jeremy Tuttle:Right right.
Rebecca Hogue:Have you had challenges in integrating AI into your processes?
Jeremy Tuttle:That's a good question and I think it comes down to what. Do I consider the threshold as a challenge. I don't think we've tried to implement it as earnestly as others have. We have a very specific process that we follow and we've considered it at different points along the process. And if it hasn't worked in that point of contact of the process, we haven't tried to force it in some other capacity. And some people might say that's not innovative. Other people might say you're doing the right thing. From from my perspective, I need to keep my production line moving and I'm not willing to halt the presses long enough to really dig in and see if it would make a difference. And it's not impacting our ROI to not put it in with fidelity, so I'm not incentivized.
Rebecca Hogue:Do you have any thoughts on how it will change? What do you need generative AI to do to be useful for you?
Jeremy Tuttle:That is a really good question and I recently spoke at the Al Polly Humboldt Innovation Summit and with this group. They were not concerned. They were interested in innovative ed tech and how people are approaching AI and as part of that presentation I went into user experience, user interface, ux, ui stuff and I think that generative AI is following an extremely similar trajectory as UX UI faced a decade ago. So I'll give the example that I gave there, which is and all of a sudden my brain just turns into presenter mode and I was about to ask the room raise your hand, If you ever had raise your hand If you ever had a MySpace page.
Rebecca Hogue:Oh, can't say that one. No, I did not have a MySpace page.
Jeremy Tuttle:But are you aware of what MySpace looked like? Yes, yeah. So everybody on MySpace had the capacity to change how their page looked. You could put a plain background. You could put an image as your background. You could desolate an image of you and five friends to be your background. So that background could be incredibly simple or incredibly busy. You have the capacity to change the font color, to change other bounding box color. So if you were so inclined, you could put a bright orange text on a slightly less bright orange background and you weren't stopped. So if people came to your page you'd have to squint really hard or get out your at mantis shrimp yeah, notoriously bad for that yeah.
Jeremy Tuttle:So in thinking about that, uxui and in its nascent stage had a whole world of open possibilities. You could design a web page however you wanted, no matter how bad compared to modern day standards it is. Think of the space jam web page, where it's got sparkly sparkles going on in the background. And now we know that if somebody is going to interact with a website and needs to be clear what is interactable and what isn't interactable, we need to remove noise from those things that we want them to engage with, whether it's text, video, a button and if we remove that noise, people are. They feel better in the digital environment. Another example would be the three line icon. You know the three horizontal lines Seven years ago? Well, today that's called the menu icon. You go to a website. You see the three lines or hamburger icon. Right, yeah, you see that. You click it. It opens a menu and it turns into a little X and then, if you want to leave that menu, you click the X. The menu swivels back up into itself. But seven years ago, when I was building tutorials here for Niche Academy, I had to call it the three line icon because if I didn't, people didn't know what to click. Today I can just call it the menu icon, and I get zero negative feedback from the learners of those tutorials saying I don't know what a menu icon is, I don't know where to click.
Jeremy Tuttle:So this progression in UX, ui and understanding how people want to and need to interact in a digital space has vastly improved. I think the same can be said for generative AI, in that right now we're sitting in the MySpace era. Everything and anything is possible. You can ask it to do all the things and in five years from now, we're going to look back at today and go man, there were a lot of bad practices going on back then. So do I know what those bad practices are in this moment? No, I don't. I don't have the ability to jump ahead five years and then look back, but I do think that what is the entire possibility of what's happening right now is not going to be the case in five years from now. It's going to be more limited scope as we learn what end learners and users for just general use cases, as they decide what feels good and what meets needs.
Rebecca Hogue:And just figuring out what that is and getting yeah, because again you think about the hamburger menu and you know, yeah, it took a little while for everyone to know what it means, but now everyone does Right, it's the same kind of yeah, what can we do? Have you done any learner personalization? Do you do any of that? Have you done any learner personalization?
Jeremy Tuttle:Do you do any of that? I do not. So the training that my team creates and provides is meant to work in any organization and therefore be very broad, and then we hand that training off to our customers and then customers can customize it to their unique needs. So for that sort of personalization it would have to be done on the customer side, not ours.
Rebecca Hogue:Okay, and do you do? Have you done any chatbots?
Jeremy Tuttle:We do have a semi chatbot on our website. It pulls from the knowledge base that we have for our product, but it's very limited and we do that very intentionally.
Rebecca Hogue:And so that's just more on your marketing side than not really on your training and creation side.
Jeremy Tuttle:Correct, correct. Yeah, we don't do a chat bot on the training creation side.
Rebecca Hogue:Yeah, I think that's think that is potentially an interesting future practice. Whether it turns into being a future bad practice or future good practice, the jury's still out on that one.
Jeremy Tuttle:Yeah. So I'm glad you mentioned because one of the aspects of generative AI that I'm very interested in is the concept of authority and expertise. So, if you don't mind me taking a minute or two to help define those terms so that we're running on the the same vocabulary somebody who is an expert is a person who has extensive knowledge, practice experience, research on a very specific topic, and authority is constructed around expertise and it's dependent on the situation and context in which that information is being used. So I'm going to give you a very disparate, very extreme example of expert information versus authoritative information. So we have a dietician, somebody who specializes in diets, in nutrition, in getting people to eat food in a specific way to meet their end goals. Then we have you.
Jeremy Tuttle:You are an expert in what you eat. If I asked you what you had for breakfast, could you tell me what you had for breakfast? Coffee, yes, coffee, perfect, beautiful. Who would I go to to ask what you had for breakfast? Should I go to you or should I go to the dietician? If I wanted my question answered, I would come to you.
Jeremy Tuttle:You are an authority on what you eat, but a dietitian has spent way more time thinking about nutritional value and diet plans and whatnot, right. So even though the dietitian is an expert, they are not an authority on your diet. Using that kind of thought process, let's put that in context with generative AI. Generative AI is pulling from expert sources. Is it pulling from all the expert sources? Could be debated. What we'll assume for the sake of this, this discussion, that it's pulling from at least one expert source. Is that expert source that it's pulling from authoritative for your needs? I'll pull a more recent example. I believe it was air canada that lost ruling because their chatbot on their website guaranteed something yeah yeah, person very sad, her husband died on a flight.
Jeremy Tuttle:She went to the chatbot saying, hey, this happened, I need to be refunded. And the chatbot said, well, as long as you've done this within 90 days, we can refund you. So she followed that procedure and then she got a message back from Air Canada human, not Air Canada chatbot saying, actually, our policy is that doesn't happen at all, sorry. And she took him to court and she won. Air Canada lost and she won, she won, she won, yeah.
Rebecca Hogue:Because chatbots yeah, that was actually quite a remarkable thing. So the chatbot is considered an authority.
Jeremy Tuttle:Exactly so.
Jeremy Tuttle:It's expert information was not the policies of the company.
Jeremy Tuttle:The expert information was just whatever it had back in its repository.
Jeremy Tuttle:If we take that in context for our learners, if we release responsibility of the company content that we put in front of our learners, they are going to assume it is authoritative information and they're going to run with it. But if I, as a trainer, as a leader, as a manager, as a supervisor, do not verify that that is authoritative information, that it is what the learner should be doing, then that learner is going to be running down a path that they shouldn't be and they're going to be going down it faster if they're using the AI as their source because the AI spits it out faster and if they're not thinking critically about what that information is, where it's coming from, what the sources of that generated GISA information comes from, they're going to keep going and they're going to keep going. And the next time I as a manager, supervisor, trainer, check in, I'm going to go Whoa, how did you get all the way there when all I put was was here, and then you got to backtrack, you got to retrain, you got to.
Rebecca Hogue:Well, and yeah, it's worse. Right, yeah, there's nothing worse than training wrong. It's like documentation, right, wrong documentation is worse than no documentation.
Jeremy Tuttle:Absolutely.
Rebecca Hogue:And yeah, I can see that from a training perspective as well. And so where does the AI? Where is AI going to learn authority? Absolutely. And yeah, I can see that from a training perspective as well. And so where does the AI? Where is AI?
Jeremy Tuttle:going to learn authority. It doesn't, because authority is contextual. You need to know the situation in which it's being presented and what the intended outcome is. For that to happen, but AI, unless extremely specifically prompted, cannot do that.
Rebecca Hogue:And then, in order to do that prompting at least today you spend more time figuring out the prompt than if you would have just done it yourself.
Jeremy Tuttle:Absolutely, absolutely.
Rebecca Hogue:So what are some of the tools that you use regularly that involve AI? We've talked a little bit about Adobe, creative Cloud tools and ChatGPT. Is there any other?
Jeremy Tuttle:There aren't any other tools that I use right now. One tool that both intrigues me and concerns me is Sora. It's the film generative AI. You can ask it to say a woman walks down a Japanese or a street in Tokyo with neon lights, and it'll produce a very convincing woman walking down the street in Tokyo with neon lights going on around her.
Rebecca Hogue:In three arms because you know the image stuff, you can't get human and you can't get text.
Jeremy Tuttle:Sora is pretty good, and that's why I find it both intriguing and concerning. I concerning on the ethical side making sure that you're not generating politician doing this insane act but on the instruction side, there is the potential to say I need to demonstrate this dangerous situation without putting an actual human at risk. Can I prompt this film generator to put a fake person in this dangerous situation so that you can help somebody identify what's going wrong? So is it at that point? Yet I don't think so. Is it cost effective? Yet? Definitely not, but at some point in the future I think it will be.
Rebecca Hogue:That sounds like a very useful use case for generative AI. Is that danger case where you don't want to put, or you can't put, somebody in danger, but you need to demonstrate what that danger looks like? Yeah, yeah, that's actually really, and we talk about that as a reason to use simulation rather than being able to do the actual in the training context. Right, you have to simulate because it's not safe or it's not cost-effective, right? Those are big reasons for simulation, and so that sounds like it could be a very. That's where video could, that generative video could compete in that realm. That's an interesting idea. How do you effectively evaluate, or how do you evaluate, the effectiveness of AI in your projects? Now, you've talked a little bit about how some of them are just not time effective.
Jeremy Tuttle:Yes, the other is the intended outcome with the generative text side of things. Chatgpt is good at grammar, but tone, even if you ask it to switch tone, is it really the tone that you want or is it the tone that they're giving you? Same thing for Grammarly, right. In Grammarly as you're writing, you can get suggested changes to how you're writing to improve it in some capacity. Grammarly as you're writing, you can get suggested changes to how you're writing to improve it in some capacity, whether it's for brevity, for fluidity.
Rebecca Hogue:And that's actually a great example. Grammarly is one of the earlier AI examples that people don't necessarily know that. Yeah, that's AI that work in the background giving you those things. But yeah, tone, that's a good point.
Jeremy Tuttle:So understanding what I want out of this situation and if I'm getting it. That takes the mental effort. It takes the mental effort. It takes the mental effort, the cognitive load of that creative experience which, in my opinion, is unnecessary. If I'm throwing a pot on a pottery wheel and we're 10 years in the future and we have AI in our glasses and we can see a certain shape projected out onto the throwing wheel so that I can produce the pot to that shape, is that creative or is that just derivative replication? I find joy in the creativity. I find fulfillment in the creativity and having the words be my own. So, personally, I don't use it for any of my writing. I had to think for a second have I used it to have it right for me in any capacity? And no, though I do support others in using it for their own personal reasons. Not everybody is like me who derives joy playing with the same sentence for 30 minutes trying to get it just right, and I appreciate that.
Rebecca Hogue:And how does cost affect your decision to use different things?
Jeremy Tuttle:Everything has a cost. It's the ROI and the opportunity cost. So right now in the instructional design space there are a flood of companies coming in that are touting ai, supported, ai generated training in. In. Whether it's you put in the, the prompt, we give you the material, or we've put in the prompt and give you the material. There are a number of companies coming out now that do that. So to differentiate within the space, is it worth trying to make a splash doing that same tactic, or is it a bigger opportunity to say we don't do that. So that's something that niche academy, my, my company is weighing is. Is it worth getting out more, you know, getting out more training content through the use of AI and maybe it being not to the same standard of quality that it has been up till now? Or do we continue our current pace and make sure that it's produced thoughtfully by humans and we advertise that so that customers can see that this is a more not necessarily thoughtful, but a more intentful approach?
Rebecca Hogue:That's a really good point. It's like again back into the future of AI and as a company, it's like now you're advertising that we don't use AI and that's your competitive advantage over the AI ones. I've played with a couple of those AI generative ones and so far I'm finding everything that comes out of it is bland. Yeah, yeah, it's just sort of like you're spitting out facts but you're not applying learning theory.
Jeremy Tuttle:Oh, and so I'm very glad you mentioned that, because another aspect of my job is I've been in conversations with managers, people who lead other people within a company and they're responsible for the professional development of the people on their team. They see generative AI as an opportunity to release some responsibility in regards to that training. If I don't have to sit through an hour of training in the conference room with a slideshow that I prepared, wouldn't that be great? I can just hand this off to my team and they can go running. So, ignoring the discussion we had earlier where you know if you do that, they're just going to run down a path quickly and you're not going to catch them.
Jeremy Tuttle:Uh, the other aspect of that these managers who want to just set them free don't understand learning outcomes unless they're instructional designer or trainer by trade. So, without thinking about the learning outcomes or objectives or competencies whatever term you use at your organization, your, your learners, aren't necessarily going to get the right information. Again, going back to the authority. So we need to ensure that, for proper training transfer, that managers still care about the, the work that their staff produces, the effort that they go through. You can't have AI be your fail-safe for quality. And going back to who was it at IBM that said you can't, air computers shouldn't be making business decisions, because you can't hold them accountable.
Rebecca Hogue:I hadn't heard that, but that actually is a great quote.
Jeremy Tuttle:I'm pulling it up. A computer can never be held accountable for decisions. Therefore, all computer decisions are management decisions. That's the actual quote, but it still holds true with training, in that if you release your responsibility to something that can't have accountability, then you therefore don't have accountability and you aren't doing your job. I'm calling you out, managers out there who think that you can release that responsibility and assume that your staff, your employees, your team members are going to be effective and supported.
Rebecca Hogue:It's a good point. We are coming towards the end of our time, at least for the podcast portion. Is there anything else you'd like to chat about? You said you had a list. You had a list. I'm curious what other questions I should be asking. I certainly deviated from the questions that I had in front of me because I'm like, okay, that's not really what we want to get at. So again, which is an exact example of using the AI to generate the questions but then using the human to adjust them to the particular context of the interview it's like, well, that's not really the right question to ask.
Jeremy Tuttle:Absolutely, Absolutely no. I think all the points that I wanted to get across got across yeah so what's your next big hope for ai?
Rebecca Hogue:my, my next big hope yeah, like short term, like in the next six months. What are you hoping to get?
Jeremy Tuttle:I can't remember what the status is in the EU on legislation regarding the training material for large language models and other generative software, but I hope to have stronger legislation around it stronger legislation around it. I'm friends with many artists and a lot of the artists that I talk with are strongly concerned about software just coming and gobbling up their style, their work, so that people can pay pennies to get artwork in their style. And are we in an age where art is no longer valuable? I hope not, but if that isn't taken care of, it will be the case where anybody who wants any sort of artwork, they just go generate it themselves.
Rebecca Hogue:Sort of changes? What art is?
Jeremy Tuttle:Yeah, it would no longer be a human endeavor, and a large part of art is making human connection through a medium of some sort. So if it's no longer about human connection, then those participating or engaging with non-human media it. It doesn't feel the same, at least to me and so how does legislation help that?
Jeremy Tuttle:it prevents certain art from being generated, that it shouldn't only be from the artists themselves. So there's a long list of artists that was posted, trying to remember when and by whom. But Dolly was trained on a list of hundreds of artists and in that list of artists there are people who adamantly affirm that they did not give consent for their art to be put into the system to be part of the training material. And so people can go into dolly and say make me this thing in this person's style. And had that not been the case, had that dolly not been trained on that style, it wouldn't have been able to spit out that kind of art. The only way to have received that kind of art would be to go to the artist themselves, so it has effectively removed money from their pockets. There's an argument to be made that art is free, but also no, but it is.
Rebecca Hogue:I understand that part of it, but the as long as it's generating a true remix and not reproducing the exact same thing.
Jeremy Tuttle:At what percentage? Right, if you talk to the music industry, you say I'm going to remix your song and I only remix it 5%. The music industry is going to be no, I'm slamming you with a DMCA, take it down, because it was that.
Rebecca Hogue:5% does not qualify as new and innovative or whatever the copyright, legality or legal terms are yeah, it's, and I find it interesting that the same didn't happen for the text-based generative AI, but it does for the visual-based AI, which I find that fascinating. You can say write me a poem in this style and it will, and. And there hasn't been that same pushback that we get in the minute you go visual, suddenly there is just much more pushback from the artists on. You know, wait a second. I didn't give my permission for that and that's actually one of the big things I teach when people are creating web pages and eBooks and whatever it's like. Yeah, is that Creative Commons? Do you have a license to use that?
Jeremy Tuttle:Absolutely.
Rebecca Hogue:Is that valid? Is there enough Creative Commons, Rebex, CCO as opposed to CC BY out there? That would allow the dallys of the world to get their databases so that they can be generative.
Jeremy Tuttle:Absolutely. Visual generators shouldn't or can't use art produced by artists, just that those artists should be able to consent into being part of that training pool and they should be compensated as part of that. Had this list of hundreds of artists been compensated, I don't think there would be nearly the uproar as it currently is in this space, and I think that's what the legislation in the EU is trying to and I'm not an expert in that space. I've only read it once, so I'm just going off of what I vaguely remember, so I could be completely wrong, but they're trying to set up those ethical standards in regards to how the system is trained so that the people who are affected by its training have either recourse or ability to also profit from yeah, that that actually brings up an interesting ethical question on the use of some of the visual stuff.
Rebecca Hogue:If I'm using it to create something, am I participating in this unethical behavior because I'm using it to create something?
Jeremy Tuttle:Yeah, and an interesting parallel is back in the early 2000s, using napster, but it was downloading music for free and an ethical problem. In the modern day we we can think about and go, yeah, that kind of feels like stealing, but at the time Napster was a giant company and millions upon millions of people were downloading music for free. Did they? Were they moral and ethical monsters that in that moment I don't think they felt that way.
Rebecca Hogue:No, yeah, it's kind of. Yeah, that's an interesting parallel example. Okay, any any last thoughts before we close up.
Jeremy Tuttle:No, thank you for having me. It's always fun to come on here and chat with you, hear your insights, and I'll gladly come back anytime.
Rebecca Hogue:Well, thank you very much. I really appreciate your willingness to come on and chat with us about what is this AI beast, especially now that it's been around for a little while it's not quite so new anymore, and so that's quite interesting.
