Human-Governed AI for Learning Design With James Gilchrist

Welcome & Guest Return

Jackie Pelegrin 0:00

Hello, and welcome to the Designing with Love podcast. I am your host, Jackie Pelegrin, where my goal is to bring you information, tips, and tricks as an instructional designer. Hello, instructional designers and educators. Welcome to episode 140 of the Designing with Love Podcast. Today I'm excited to welcome James Gilchrist back to the show. James is the founder and director of Lighthouse L&D Consulting. At iSpring Days 2026, he facilitated a session that sparked an important conversation about AI and learning and development. More specifically, he challenged us to think about what human insight and judgment will still need to protect. As human insight and judgment, we still need to protect as these tools continue to evolve. James, welcome back. I'm glad to have you here again with me.

Speaker 1 0:54

It's nice to be back, Jackie. Thanks for having me.

Jackie Pelegrin 0:57

Yes. Sometimes we make those little mistakes and let's just roll with it, right? It happens. That's right. Right. I love it. So I love how you you had that opportunity to speak at iSpring Days about how AI may change work. But LD, as we know, has that responsibility to preserve the thinking behind the work. And I love that. Such a powerful idea. So to start us off, what led you to this topic and why does it feel so timely right now for us?

Speaker 1 1:27

So my presentation was called Discernment, Direction, and Quality, Human Governed AI for LD. And what led me to the topic was a growing sense that in LD, AI is arriving wrapped in a very compelling promise, speed, faster drafting, faster outlining, faster production, faster turnaround, faster scaling. And to be fair, some of that promise is real. AI can absolutely help us move faster. But what concerned me was that deeper questions could start getting pushed into the background. Why are we doing this?

AI Speed Versus Real Learning

Speaker 1 2:10

What is this actually for? What kind of result will truly help people learn? That is where discernment starts to matter. And to be clear, these are not new questions and they are not newly being pushed in the background. Having spent as many years as I have in this industry, I've ridden that wave where LD seem to be able to make the case for the what and the why uh for learning. But then some technology comes promising that things can be made faster, that it becomes easier, that you don't need to know as much, essentially, in order to be able to create the content. Um and AI is the latest. But I made the point that in our field, faster isn't the same thing as better, and more output is not the same thing as more learning. That distinction became increasingly important to me because LD work is not just about making content, it's about helping people understand, apply, transfer abilities and skills, grow and perform. That kind of work has always required judgment, and I would suggest that in an AI-shaped environment, it requires even more. Um what made the topic even more concrete for me is I've been pretty serious about working with AI for about 18 months. So not as long as some, longer than some. Um, but from the very beginning, I didn't approach it from the standpoint of, well, let me go out and take these classes, let me watch all these things that's gonna tell me how all of this stuff works. I just started using it. And based on what I was getting back, like any natural learning process, I started to change what I was doing. Um, and in this case, I had used AI to help create uh create an image to go along with a LinkedIn post that was going to be all about um authenticity, the power of individual choice. And it was so compelling the process that I went through to make the image, and the image itself was so cinematic that I got the idea I could turn this into a short video. And that was something I hadn't done before. So I said, oh, okay, let's let's now stretch my legs, and now I'm going to take this still image and I'm gonna make a video that I can speak over. So it's got to be long enough to carry the message. Um and what seemed at first like a straightforward creative exercise became a lived demonstration of the very thing the piece was about. AI was helping generate motion, variation, and possibility, but it didn't know what mattered in the scene. It didn't know what mattered to me. Uh, it didn't know what needed to remain emotionally true or what compromises were acceptable. My governance was what was needed for AI to accelerate production in any meaningful way. My discernment, direction, and assessment of meaningful quality. So that is really what led me here. Professionally, I see the field being pulled towards speed. I read LD industry reports, and I see that organizations are investing approximately twice as much into AI, which is essentially software, tools, versus the amount that they're investing in their people, whether it's leadership development or uh upskilling, um training people in their individual careers. And that really struck me. Um and then personally, I had an experience that made the limits of speed and the necessity of human judgment much more visible. And it feels timely because many people in LD are being asked to integrate AAI now, whether or not they've had the time to decide what must and should remain human-led.

Jackie Pelegrin 6:32

Absolutely. You know, and everything that you're talking about in LD is also happening in higher education curriculum as well.

A Creative Test Of Governance

Jackie Pelegrin 6:40

James, everything you just mentioned is like I kept going, yes, yes, that's happening. It's it's really it's eye-opening because now the faculty are getting familiar with these tools and our curriculum developers and instructional designers like myself. But you're right, there's there's no governance behind it. It's and what I'm seeing is that we have courses that are just overloaded with too much information, too much content. And I'm like cognitive overload alert, right? And I'm just like the alarm bells are going off like crazy. And then I it's crazy because I looked at a syllabus the other day, and half the course, the first four topics look great, wonderful, not you know, not anything alarming. Then I get to five through eight, which is the other subject matter expert, the other faculty had had worked on, and it was just scrolling and scrolling just for one assignment. And I'm like, this is five pages, and I'm not even to the and I'm like, that's the assignment. Wow. I can't imagine how it's gonna look in the LMS if we if that gets approved by the college. But he had five paragraphs worth of a purpose statement before getting to the instructions. And I'm like, if that happened in L and D, you would lose people right away. Students, same thing, you know. So it's like, wow. And I'm like, was this done by AI? I I could read it and I could kind of tell some of it was AI generated. And so that's what we're finding. I don't know if you're finding that too, but it's you're starting to see the telltale signs of subject matter experts that are grabbing it from AI and then just putting it into whatever you know document you have it in. And it's like, oh my goodness. I'm like, we gotta stop and and just kind of yeah, look at that and see what are we actually doing? Are we, yeah, you're right, are we speeding it up or are we actually causing more problems down the road with it?

Speaker 1 8:38

So you said something that jumped out at me. Um, you reminded me that throughout my career, one of the biggest uh questions has always been, how can we prioritize what it is that we are telling the learner and scaffold so that they understand what's important? Because um the subject matter experts or the stakeholders that I would work with would often come back. Now, mind you, in a uh I I don't know about education, but in corporate LD, an organization that's used to providing training around its own services, um, there was usually a backlog, like an archive of everything that had ever been done, everything that had ever been written. And when you would talk to someone uh in the business and they would say, Well, we need training on X, and you would say, Well, what do you have on X? And they would say, Oh, here's what we have on X, and you'd get, you know, three binders worth of stuff. And I would say, Well, we we haven't even talked about what the problem is yet. And I can tell you right now that 90% of what you're showing me is probably not relevant for what it is that we need to do. So it was whittling down. It was figuring out how can we take out content? Because we don't want the learner to burn out before they even get to the part where they are practicing the thing they need to know, the behavior change. Um the other thing was so when you would agree on a curriculum and then you would say, um, so what is the most important thing they need to know versus what is the nice to know? What is the sort of supporting material? Because we want to organize according to that. And the answer would be, well, it's all important, it's all equally important. You know, if you say I hear that a lot.

Jackie Pelegrin 10:33

Yeah.

Speaker 1 10:34

You know, you can do that, but it's not going to result in, I mean, if you get completion, that's all you're gonna get. You're not gonna see, you're not gonna move the needle, you're not gonna see per performance enhanced. Um, and that's our role in LD. It's always been our role in LD is to sort of field those questions and and help people who are attached or who are championing or who are paying the bill understand hey, we're on your side. We're actually trying to save you money. We're actually trying to improve the results you get from this training, right?

Speaker 2 11:10

Right.

Speaker 1 11:10

And then you look at AI. And one of the magic things about AI is you can say, give me a 10-chapter course explaining everything about, you know, ABC. And A AI just spits it out. So anyone who's not in learning and development, they look at that and they say, This is the magic bullet. This is the the the the gold standard. I never have to wait for content anymore. And and m and I skim through it and it seems pretty good. I don't need to sit in a meeting with someone sort of reviewing it point by point, because you know, it seems to be seems to look good, reads well, right? All of that is true. And and you say, as an LD professional, imagining the learner, like you were doing, you were like, oh my god, I'm imagining this student looking at this exercise, and what are they gonna think? Um, and then you add to that things like, well, in the modern age, with people not having very much time to consume content in the first place, they've got so much they've got on their plate. Like the learning is it's it's an obligation for us to keep it simple, make it clear, not take any more time than it has to, right?

Jackie Pelegrin 12:22

Right, right. So true.

Speaker 1 12:24

There have been studies that talk about how people scan material, digital pages, written pages, that sort of thing. And when they start looking at something, they're doing the left to right. And as they start to feel the loss of time, they start reading like an F. They go across the top line and they go a little bit across on the second line, and now they're just scanning down the left side of the page. They're not even reading what's there.

Jackie Pelegrin 12:55

I've been guilty of that.

Speaker 1 12:56

Right? So but that's our job. That's our job to put ourselves in the in the role of the learner, in the in the mindset

Content Overload & SME Habits

Speaker 1 13:05

of the learner. So again, it's all of that just comes back to if the thing that AI is really good at is indiscriminately giving you an incredible amount of content, as an LD professional, you look at that and you understand, well, that's the beginning. That's step one. Whereas because it's never been something that's been clear to people outside learning, they look at that and they say, that's done. Right.

Jackie Pelegrin 13:33

Right.

Speaker 1 13:34

So anyway, you you talking about what you were looking at and the telltale signs of like, oh, this this appears to be using sentence structure, word choices, a way of emphasizing, trying to smooth everything out, trying to make everything sort of the Pablum version of language is what AI often generates.

Jackie Pelegrin 13:56

Right.

Speaker 1 13:56

And part of what I was talking about today is the need to put uh guardrails up and to know what it is that you're looking for.

Jackie Pelegrin 14:05

Right. So true. And you you touched on this, and I wanted to dig a little bit deeper in this because of the pressure right now for LD teams and even people like me in curriculum to move quickly with AI, right? It's like you gotta you gotta already have it in the in your tool belt and and use it. So, from your perspective, what's the difference between using AI in a way that truly supports the learning design versus using it in a way that slowly chips away at critical thinking and good judgment? Because that's one of my one of my uh fears is that critical thinking and that judgment.

Speaker 1 14:43

Well, um, so I've spent a lot of time evaluating uh learning solutions created by others. Um, people who are just starting out in instructional design, they come to me, they show the show their show me their courses, and I'm looking at them. Um and understanding the difference between um designing for the learner and designing for look and feel, or designing for polish, or presentation, or production values and all of that is one of the clearest signs that someone is still new at the game. Okay. And that is true regardless of what tool they're using. And in this case, critical thinking and good judgment isn't something that the idea of AI makes a difference. Um the difference continues to be and is more important because now you are getting that wall of content coming back at you from AI. Um that discernment, direction, and quality be top of mind for the designer and it are governing the work. So put that another way it's always been important. Discment, direction, and quality have always been important when working with ourselves, guiding our own work. As you become more experienced, you understand that that's really the beginning, the middle, and the end of creating any successful learning solution is knowing how to apply those things, but we lose sight of them in the face of AI, right? So AI can absolutely support learning design by accelerating production. Um, it can generate outlines more quickly, it can, as we've said, draft content faster, it can summarize information, it can propose structures, uh, offer variations, and it can reduce the time it takes to get from a blank page to something workable. That is real. But none of those things by themselves tell us whether we are becoming more effective as LD professionals. What chips away at critical thinking is when we start treating speed as if it were effectiveness, or treating output as if it were evidence of learning value. In my presentation today, I said the real risk is not that without AI we will somehow fail to produce enough. The real risk is that in our eagerness to produce more, we start confusing motion with progress, output with value, and efficiency with effectiveness.

Jackie Pelegrin 17:38

So the lines start to get blurred and then we can't tell what's what's real, what's not anymore, right? Yeah.

Speaker 1 17:45

So I gave people who came to the session today a framework that I'd been working on over the past couple of months, and it's very simple, simple enough to remember, but strong enough to be useful. And I like to call it DDQ. Discernment, direction, and quality. Discernment asks what is actually needed, what matters most, and what deserves protection. Direction asks where should this go next? What role should AI play in its development? And what should remain human-led. And quality asks what makes this worth a learner's investment? And what standard of mine tells me this is ready. If those questions are active,

DDQ Framework Explained

Speaker 1 18:45

AI can support the work well. If those questions begin to disappear because things are moving too fast, then AI is no longer just helping production. It's starting to erode the very judgment that makes LD work effective in the first place. So for me, the difference is simple. AI supports learning design when it remains governed by human discernment, human direction, and human quality standards. And it chips away critical thinking when those things are no longer actively being exercised.

Jackie Pelegrin 19:18

Right.

Speaker 1 19:19

Don't if you don't, uh you use it or lose it, right?

Jackie Pelegrin 19:23

Mm-hmm. Absolutely. Right. So that that human in the loop is so important to keep all throughout the process. Um, yeah, not just at certain points, but yeah, we got to have that critical judgment all the time at every every pass, right? Absolutely. Yeah, that's so true. So, James, for instructional designers and learning leaders who want to embrace AI without losing quality or humanity in the process, uh, which I think is so key, right, today. What are some practical guardrails you would recommend to these types of individuals like like us that are out there?

Speaker 1 20:02

Well, the DDQ framework um is was my answer to a boundary or a guardrail, like you mentioned. Um it's important that it be used before production. In other words, you have to make sure you've answered those questions before you start producing. Um I mentioned today, and to great effect, meaning I got a lot of hearts and likes and stuff happening in the in the meeting today when I talked about how we so often get told, oh, we need a scenario, oh, we need a module, oh, we need a course, we need a this, we need a that. Then they're all learning assets and they're being named as if they are themselves, by their format, the solution. Um and again, with AI, you can tell it that's what you want and it will make it, you know? Um so we have to ask what's actually needed, what matters most, and what deserves protection before deciding how AI will be used. In other words, what is the problem we're trying to solve? What are the conditions under which this activity is happening? What are the constraints? Um what are the real at the ground level circumstances, not the idealized, this is how it's supposed to work scenario, you know? Um, and you look at how best to address those, and then that leads you to the format, you know. Um there's the old to a carpenter with a hammer, everything's a nail, something, something like that, right? It's easy. If you have an LMS, for example, and the LMS accepts a certain type of uh format, you get used to it's like you're feeding the LMS before rather than creating a job aid or whatever the real solution needs to be. Um But again, discernment is going to help prevent teams from moving too quickly into production mode before they understand the real learning need. And then the second guardrail, the second leg of the stool is uh direction, right? So you decide what it is that AI should work on, what it can support, and what should remain human-led. And if that's not named clearly, teams can begin using AI indiscriminately rather than intentionally. In my presentation, I was very clear that some work should remain unmistakably human-led, like reading context or interpreting learner need, protecting meaning, judging tone, recognizing ethical implications, and knowing what is trustworthy, right? And those are not minor responsibilities in LD. Um they're central ones. And then finally, we establish quality standards. Um, standards are great things for an organization to have and to work from. Um, I know when I was working um when I was an instructional designer, sometimes standards made me feel restricted. I didn't like feeling like I had to create everything in the same sandbox. I had a new idea about how I wanted to solve a problem, etc. Um, and so I felt like standards could sometimes sort of squelch creativity, but reality, everyone's working at a different level. Everybody has a different amount of stuff on their plate to get done. Um, not everyone is performing at the same level, and you take away those standards and you can see an uneven output result, uneven quality results, right? So standards when it comes to AI are more important even than they are in uh for a human team because humans can look at the standards and understand what they how they can be interpreted, right? The AI is always going to run off in a in its own direction unless it's told specifically where not to go. And it's not going to know where it shouldn't go or what it shouldn't make or what it shouldn't assume unless you tell it. So that's part of the orientation that we as humans provide. So asking whether the work creates understanding, supports meaningful practice, reflects learner context, provides feedback and consequences, um, and deserves trust, those are the kinds of questions that protect instructional soundness.

Jackie Pelegrin 25:28

I love that. I love how you you brought it through to like a like a stool, because I was actually thinking that the stool with the little three three little legs, right? Yeah, I like that. Yes, because it, you know, and something I was thinking of too when when we put something into AI and you know, and it gives us something, it's almost like that genie in a model, right? I'm gonna rub the genie and it's gonna give me what I want. It's gonna give me my wish. And but those wishes aren't always gonna give us what we what we truly need, right? So yeah, I think it's so important. So I I love that that pillars, those pillars that you brought forth, James. That's that's amazing. I'm gonna have to remember that now. Definitely. I'm gonna go back to this and and look at that and keep make sure I I write it down because I think it's so important to have that from the very beginning, as you said. That's great. So uh as you were facilitating this session with icepring days, was there a question, reaction, or a moment from the audience that really stayed with you afterward that you would like to share with the listeners here?

Speaker 1 26:33

Um yes, actually. There was a very interesting question that got asked at the end

Guardrails That Protect Quality

Speaker 1 26:39

of the session. Um someone asked how I recommended they handle the guilt that they felt at not already having mastered all the different ways that AI integration um was happening at their organization. Like they felt the pressure to simultaneously be getting more efficient at their job while simultaneously being fed all of these directives about how they had to incorporate AI, how they had to integrate AI, how AI needed to be used. And they were focused on their job. They were focused on supporting a customer, or they were focused on, you know, managing employees. And it just felt like this it was just haunting them, you know, this feeling of like this is piling up in the back of like I'm falling behind because I haven't trained myself in all the ways of AI, and yet it's in it, and I'm already in the middle of it. It's like a like the basement is flooded and it's coming up to my knees kind of feeling. Wow. And I was so struck by the question. There were so many things that that question revealed about their circumstances. And so what I said was that first of all, that uh if they were feeling guilty because they hadn't managed to uptake all of the AI skills that they needed to be able to handle the integration that was being foisted on them. Um they should stop and think about where the guilt was coming from. The guilt was coming from a place of respect. They have respect for their organization, they have respect for their role, they have respect for their job, they know it's important that they do it well, and they know that these these initiatives are just going to keep coming. So they feel like they're doing something wrong, and that's why they feel guilty. And I said, um, your company isn't really giving you a whole lot of respect, is what it sounds like to me. It sounds like you're being asked to do more with less. You're being asked to fulfill a promise that you didn't make, and you aren't being trained or given the tools, resources, or the time needed to be successful. Kind of like you're being set up to fail. And if the thing you fail at doing is figuring out how to integrate AI, which is essentially taking the role away from people like you in the company, that's a double-edged sword there. That's kind of a, you know, there's a has a nasty aftertaste. And so I said, um, you should start by giving yourself more respect. Because, first of all, the fact that you care enough about this circumstance that is essentially untenable to feel bad about not being able to do it says a lot about how much you are invested in helping the business succeed. You're trying to you're trying to do your job and trying to do it successfully. Um and it's your company's fault that you're failing. It's your company's fault that you're not better prepared and that these things are being integrated without true integration. You know, they're being they're being introduced without integrate integration, is the way I would put it. Um and then I said to move towards a solution, I said take some pressure off yourself and don't think of learning AI as falling into that category of these are the employee uh instructional courses that you're expected to take, right? Don't look at the backlog or the catalog of courses that you're supposed to be taking in order to slowly accumulate all this knowledge that you're supposed to have at your disposal. And instead use, think of AI as it lines up with something that you are naturally interested in. So pick a subject or a creative path or some type of engagement or activity that calls to you, that appeals to you, and start using AI with it. Because you will learn a lot by doing, and you will start mastering some skills, and it won't feel like it's under the same umbrella as all the other stuff that's weighing you down. You know, you can if you and in the process, if you start to feel good about what you're producing with AI because it's a thing you care about, like heck, write a song, start writing a short story, or create an app with one of those vibe coding tools, like just anything you can to sort of dip your toe in the water and start getting more comfortable with it in a way that feels fun. Now, when you start going back to learning the AI that you need to learn specifically for the tasks and duties you have to perform at the company, it's not going to feel quite so onerous. It's not going to feel like a burden. It's going to feel like, oh, I actually have an idea about some of this stuff, you know? And it's a lot better to feel like something is fun than to feel guilty about a thing you aren't doing. And I I couldn't see their face, so I wasn't sure if that landed, but um, the general consensus seemed to be it was a good question and a workable answer.

Jackie Pelegrin 32:38

That's such a powerful, you know, way to be able to address that and to meet that person where they were, but also to take them to that next step, right? And to, yeah, I love that. Um, because yeah, it can be easy to feel guilty sometimes, I think about um about that. And I've heard some people that kind of I I feel like at work have been feeling that way because yeah, you're just like, oh, it's thrust upon us and now we're now we're being expected to do it. But the good thing is that my company has given us support in that, so that's really good. So you know, it's really nice to have that. And we have internal, we have a closed system model, so we don't use chat GPT, but it's based upon chat GPT, so it's nice because all of our policies, procedures, all the curriculum stays internal in-house. So it's that's really good. It stays protected, and um, it's nice too because when someone makes

AI Guilt & Learning By Play

Jackie Pelegrin 33:34

a custom GPT, they can they have a framework to be able to do that and it guides them along. So our IT department did a and our media department did a really good job of thinking of all of that. And so we have so many custom GPTs now because people think of ideas, oh, we could use it for this, and then they create the custom GPT and share it with everybody. So it's become a it's kind of neat, James, because it's become a a community of sharing all of this and and making sure that we're still at the center of it no matter what. So it's it's really exciting. Yes.

Speaker 1 34:08

Well, that was that was something I wanted to make sure my presentation addressed, and that was what it feels like in at work right now in LD with the advent of AI and the uh amount of change that's coming.

Speaker 2 34:23

Right.

Speaker 1 34:24

Um, because I feel like that has an impact on how everything gets done. You know, my my belief in, you know, ever since I got started in LD, I've always been interested in systems, but I've also been very focused on the individual ingredients, the individual people that make up the system. And I've always said you can't ignore either. You can't try to change a system without taking into account the impact that's going to have on the individuals who make up the system and expect it to happen overnight or even change. It's like turning a big ship. And that's often what happens. Things come from the top down, they say, this is the change, this is the new roadmap, these are the new mission statements, these are our pillars of et cetera. And everyone needs to sort of get up to speed and start doing things in alignment with that. Um, and everyone is sort of left on their own. To, you know, they're given a couple of resources to help them understand what's being asked of them, and then it's kind of up to them. And you notice that in different departments, it gets handled differently or it gets embraced to different degrees, right? It's always about internal resistance. Like what are the obstacles happening at the employee level that is causing friction, right? And the problem, again, with a system-only approach is it doesn't account for any of those individual friction points. And so you get a very unevenly distributed success or lack of success rollout, you know, it it doesn't happen smoothly. And conversely, if you give everyone an idea about what they should be doing, but you don't provide the framework and you don't support it from the top down, those same internal frictions are gonna cause failures to occur. And you're also gonna wind up with a widely varying, you know, field of how it's being how the new direction is looking, depending on what department you're in, right? It's gonna look very different because everybody's kind of going off in their own direction. So you have to do both. You have to design a system with the individual characteristics in mind. And if you bring that same approach to your work with AI, whether you're creating a custom GPT and you have the luxury of knowing it from the code up, it's what it is going to do more often than not. Um, or you're working with something like ChatGPT, uh, where you have to do a little bit more investigative reporting. You know, you have to pay closer attention to the outputs you're getting and look for patterns. I think pattern recognition, ironically, AI is wonderful at pattern recognition, but it's amazing how rarely it will identify its own, it will volunteer up its own patterns. You have to, you have to go to it and say, I'm starting to notice a trend, AI. Verify the following for me, and then it will say, Oh, yes, you're absolutely right. That's exactly what's happening and what I'm doing. And then you can say, Oh, all right, rule number one, let's put a guardrail there. Don't do that unless X, Y, and Z is, you know, in the equation. But I just uh I think it's I think it's I would what I want to take a say uh as a follow-up to what you just said is I think that there's real joy to be found in making the integration of AI a group thing. In other words, rather than providing uh individual learning solutions like you know, online e-learning courses or whatever it is that is intended to help people like study by themselves and sort of get up to speed, you make it a group activity, right? People will understand what's going on much faster if they are working together to use the AI to solve a problem. And it shouldn't be limited to IT, it shouldn't be limited to those who are have the luxury of rolling up their sleeves and putting their hands into Ethernet cables, you know. It's like you wanna you wanna spread the love around and make it feel like something that is for everybody.

Jackie Pelegrin 38:37

Right. Absolutely. Yeah, that's so true. Because uh, you know, we we've got these AI guides for different people in the department. We're working on one for the instructional designers right now, and it's it's actually pretty neat because we're we're looking at what was created for the curriculum developers, and we're like, hmm, but we can't make it exactly the same because what we do is is different. But over the course of the last 18 months or so, I've been able to come up with different ideas. Some of it's been from the faculty, some of it's been from stakeholders, and it's like, oh, well, that's a good idea. I didn't think of using AI in that way, but yeah, and we experiment with it. We you're right, it's it's a collaborative effort. And so it it's it's so important not to stay siloed in those types of situations and really utilize everybody's talents. And right, that's what we did before AI. We utilized everybody's talents and brought everybody together. So I think it's just as important now to do that than ever, right? To have that collaborative effort.

Speaker 1 39:40

Don't you think part of the situation stems that we find ourselves in stems from early communication around AI as a whole? The idea is A AI was talked about in common vernacular in ways that

Adoption Works Better As A Group

Speaker 1 39:54

suggested things that when it comes time to live with it and have it become integrated in your work, um, are two different sides of a coin. And it's the expectation that got set, uh, and in some cases the fear, right? We've got this very powerful hype fear coin going on. It's it's it was interesting for me to try and create a talk that was intended to sort of walk on the edge of the coin, you know, because I'm because I'm a believer in the things that AI can do to improve or increase our uh ability to use our discernment and to use our direction and to and to establish quality, right? Sometimes you don't know what's wrong until you see it made wrong, right? So there is that. Sometimes you you're working on something, and AI gives you something, and you look at that and you go, huh. I didn't think to tell you not to do that, but now that I see it, I know don't do that, right? So that's so that can help, right? That's that's that's that's real. Um but then at the same time, I'm really concerned about this sort of creeping overwhelm and this feeling of that I feel like people in LD are asking themselves right now, which is literally in they ask it in their quiet of their early, you know, the late night mind. They're asking, am I valued here anymore? Am I, you know, am I valued? Is do I did did somehow my intrinsic worth just evaporate overnight? What the F is going on? You know, that's that's the question. That's right. It's in the back of people's minds, and they can't, they don't feel like they can talk about it, and they get over there's this like tidal wave of the AI is here and get on board, you know what I mean? So people don't feel very comfortable talking about that. And I really wanted to say, look, I'm not here to blow smoke up your butt about you know that everything AI is easy and wonderful and is better than anything that anyone's ever done. But I also don't want you to feel like it's the end of everything and it's gonna replace you. You know, it's it's you we all need to find our own way to the middle. And I just think part of what needs to change is the language around all of it.

Jackie Pelegrin 42:32

I agree. Yeah, because it yeah, because it it did instill fear in in a lot of people in my department too from the very beginning. Editors and all of that, they're like, wow, is our job gonna go away? All this stuff, and are we being replaced, right, by the by the machine? Yeah, so yeah, yeah. So those are real valid concerns, right? For sure. Yeah.

Speaker 1 42:54

I I got um so so I'm on I'm on LinkedIn, you know, that's primarily where I talk about things, um, advertise, etc. Um, one thing that came up recently on LinkedIn, I don't know if it's because of my tier, you know, I'm a pre premier subscriber to LinkedIn, um, or not, but I was offered the chance to sign up to be an AI trainer or to get access to organizations looking for human guidance to train AI. Um, and I thought that was fascinating that it should just sort of fall in my lap. And I knew it was early because as soon as I said, sure, okay, let me see what that looks like, and I said yes, I looked at what was available, and there was not a whole lot available. It wasn't like a lot of variety. But the fact that I was seeing it and the fact that it was happening at that sort of plain clothes level, you know, um, the equivalent of a newsstand, you just walk by and pick something up. It was that easy, it felt like I didn't go out and look for it, it just came to me. Um, said a lot to me about where we're going. And that and I think that that's a really interesting place for people who are good at educating others to find themselves. Because everything we've ever learned about learning methodologies, pedagogy, things that help people take up new skills and communicate, you know, those all of those things, it's like we need to share with With the machines in order for them to become not to become better at what we're asking them to do. Um so it's just interesting, I think. You think, you know, one day I'm one one day I'm training people, and the next day I'm training AI. And tomorrow the AI I've trained may be able to do some of the training that the people need, and vice versa. So I don't know. I feel like it's a bit of a melting pot right now, and I think it's important that we talk about it that way so people don't feel like they're disenfranchised and instead feel like, oh no, actually, I'm really well positioned because if I know how to train people, I'm gonna be pretty good at figuring out how to help AI learn, you know?

Jackie Pelegrin 45:22

Right, right. Absolutely. I love that. That's great. So, James, for our last question, as AI continues to reshape the field, uh, what do you hope instructional designers and educators and those in the L and D space even will continue to protect or prioritize most in their work as they move forward?

Speaker 1 45:46

Uh let's see. Um I hope that they continue to protect the things that DDQ was meant to keep in view. What matters, where the work should go, and what makes it worthy of the learner. I hope that they continue to protect discernment, the ability to recognize what is actually needed, what matters most, and what deserves protection. I hope that they continue to protect direction, the responsibility to decide what role AI should play and what must remain human-led. And I hope that they continue to protect quality, the standards that make learning instructionally sound, contextually grounded, and capable of supporting meaningful learning transfer. Near the close of my session today, I said depth is not

Hype, Fear, & Training The Machines

Speaker 1 46:39

obsolete, care is not inefficient, and judgment is not old-fashioned. And I believe that very strongly. Those are not secondary qualities, they are part of what allows us to use powerful tools responsibly and well.

Jackie Pelegrin 46:58

Absolutely. Oh, well said. I love that. There's nothing more to add to that because it's just so beautiful. I love it. And it's it's so true. Definitely. Well, James, thank you so much for coming back on the show. Glad we got to reconnect again and that we keep that connection too. I always appreciate how thoughtful and grounded your perspective is uh whether we talk or we're on LinkedIn together, um, especially on this type of topic that so many professionals are trying to navigate right now. And you've seen them at firsthand, right? So this conversation for me and for others, I know is such a helpful reminder that while our tools may keep changing, meaningful learning still depends on human insight, care, and intention, as you mentioned. So for anyone who wants to keep learning from you, what's the best place to follow you or connect? Um, probably LinkedIn, right?

Speaker 1 47:49

Yep. They should, they should definitely find me on LinkedIn, um, either my personal profile or my company profile, which is Lighthouse LD Consulting.

Jackie Pelegrin 48:01

Great. You're very active on there, just as I am. Yes.

Speaker 1 48:05

I am. I definitely, I, I uh I I enjoy I enjoy the conversation. And I feel like that's something something that I get more of there than other places. Although I will say, you know, there are other social platforms that um are starting to get some uh they're they're starting to fill up a little bit. It feels like overspill, like people are going from LinkedIn to a few of the other platforms, and sometimes it's nice to go to them just because it feels a little less crowded. You know, you get a little more the tone is a little bit different. It's a more little more direct and personal and a little less officious. But I think people are mistaken about LinkedIn when they think it's only businesses talking to other businesses. There are a lot of individuals on there doing really good work. Um I would enjoy connecting with anyone who listens to your program. Um, I'm always glad to come back on the program. Um, and I really admire the way you keep asking uh the insightful questions and bringing people on to give interesting answers.

Jackie Pelegrin 49:08

Absolutely. Yes, I love it. You know, it's it's great because like I mentioned before we got on the show, I've had individuals from Turkey and from Australia. And I even interviewed someone yesterday that has a 20-year military career in the army, and now he he's a life coach, he's a certified life coach. But what was just it was amazing to interview him too. And so every person that I bring on, it's just a it's a tapestry that just keeps bringing about, you know, all these little pieces, and then it it creates this beautiful picture. So I love it. It's great.

Speaker 1 49:45

If I can add one last thing, it's to anyone listening to your program. Um I hope that something that came across today in this conversation is that your desire to be seen and to have your voice represented in the larger conversation is a valid one. Um I'm I've been in LD for two decades or more, and my passion for making people who care enough to create good solutions um feel good about the work that they do and to understand the important role that they play and know that despite it feeling like an uphill battle sometime, um, it's worth doing. And that they have an intrinsic value that they bring to their organization. Um know that. Be seen, feel seen, feel heard, you know. That's what I'm about, and that's why I like doing a podcast, because we get the chance to talk about those things that a lot of people are thinking, but maybe they don't know anyone else's.

Jackie Pelegrin 50:55

Right, exactly. And then they go, Oh, I'm not the only one that's thinking that. Yes, it's it's a valid, a valid thing that I'm thinking. And yeah, so there's others out there that are sharing the same thing. So I like that. Yeah. Helps us feel connected and stay connected to each other. Absolutely. Absolutely. Yes. Well, thanks, James, for coming back. I appreciate it. And if there's anything else on your mind that comes up, let me know and and I'd be happy to have us reconnect again

What To Protect & Closing Thanks

Jackie Pelegrin 51:24

and have you back on. Um, I this is enjoyable. I love it every moment.

Speaker 1 51:30

Well, thank you very much, and I look forward to the next time.

Jackie Pelegrin 51:33

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