Hey, Megan, let's do a podcast.

Great idea. What should we talk about?

All right, let's dive in. Megan, we're going to talk about AI in 20 minutes.

Yeah, right.

20 minutes.

Yeah. Yeah.

First off, how big of a deal is it?

Oh, it's big. It's almost as big as Taylor Swift. Whoa. I mean, it's big. Unlike Taylor Swift, it actually is a tool that the Defense Department deploys. All kidding aside, though, everybody's talking about it. Right? Like, everybody is talking about it. Just got back from the conference.

Every session I went to was talking about artificial intelligence. There's a little bit of personal self selection there, too. But seriously, and it's interesting, I am already seeing things that are done by a real human as a marketing point in learning products. So I'm a facilitator for e Cornel. And one of their selling points is that there are real human facilitators. They say it a lot nicer than that. But I'm reading this like, oh, I'm one of those real humans. But it was just like, oh, we're already to the point where that human craft is now seen as a premium because.

Interesting. Yeah, very interesting. Where do you come into the AI space?

Yeah. So the first time I really heard anything about AI was about four years ago. I started working for a company called Lamasoft. They are a supply chain design company that was started here in Ann Arbor. They later got acquired, so you're not going to find much of anything about them if you look them up right now. But they had a department called Applied Research, and that department was all about people creating algorithms that would help the software understand how to, with all the data that you're giving it, design the most efficient route for your trucks to be dropping off and picking up from the distribution center to get it to the next location and all of that. So that's where I first thought of when people started talking about AI. But this new brand of AI is quite a bit different.

Yes and no. Right. So, I mean, it's building on the shoulders of giants kind of thing. Sure. Right. So AI has been around for decades. Watson beat us at Jeopardy in 2011. I think that's the year.

It's been reading our mammograms for a very, very long time. And. But similar to what you saw at Llamasoft, it required a lot of geeks in a specialized department who had advanced degrees, a lot of computer power to do one thing. Right, and generative AI does more than one thing generally. And what OpenAI's real big innovation, they had a lot of technological innovations, but it's really a user experience concept, right? So all of a sudden it is free. It requires no training, it requires no hardware for the end user. They just needed a browser and an Internet connection.

So it's accessible and it does a lot of really useful things. In fact, people are creating new useful things that it does all the time. And so it's completely changed the game and consumerized AI and put it right in our face. Right? All sorts of tools from what gets recommended to you while you shop to how does Llamasoft plan where a truck should go? How do you navigate through gps? Lots of things use AI tools. But it wasn't as obvious as it is with chat GPT. So chat GPT comes out, or OpenAI brings out chat GPT. The other providers then bring their products that they had been working on. All of a sudden, Google, Meta, everybody, Microsoft, all of a sudden they bring their products.

They're kind of rushed at the end to jump in early. So you have multiple providers and then, so it's kind of, we live in this creator economy. All sorts of folks are building on with GPTs, with the OpenAI API, and so they're adding on to that existing work. So you have this gigantic explosion of tools. And as you and I sit here and record this, it is, I don't know why, I just looked at my watch. We're talking in the timescale of months, but we're only talking about the timescale of months, right. November 2022 to whatever it is that we're listening. We're recording this in February of 24.

So 14 months. 15 months, yeah. My child was just barely walking at 15 months. So things are moving fast.

Yeah. In the L & D space, I see a lot of opportunities for things and I think some of those might be a little bit more obvious to people. Like, hey, I can write my script for my e learning course faster, or I can generate ideas for things using chat GPT. But some ways might be not as obvious. Can you tell me about what are some obvious ways, what are some not obvious ways that we're going to use it in L & D? Are using it in L & D, yeah.

And I think there's a lot of intersections, right? So I see it kind of multiple layers. So one is just our direct tools, right. So we have access to whether it's Runway, DALL·E, Midjourney, Eleven labs, chat GPT, Bard, Bing, all these tools that are, I think of them almost like a production assistant right. They help make things go faster. There's probably going to be noise reduction that's done by algorithms and very smart software on this podcast. Right. And I remember when we used to do it the old slow, hard way. So all these kind of direct tools to help both in the creation once we have an idea, but even before that, as a thought partner, right.

Help me come up with an idea. Maybe we should use AI to come up with ideas for the next round of podcasts. Feed it what we've already done, what we tend to talk about, right? Logical things like that. So those are quick. There's then also, at the same time, all sorts of power ups in all of the software we already have.

Yes. I see those buttons, like, in everything that I do.

In everything. And sometimes it's like, amazing, and sometimes it's like, okay, great. And I just keep moving on. Right. And they're evolving and expect to see every tool that you own having an AI power up of some sort. We're then looking at, how do we build AI or use AI in the learning experiences or whatever it is that we're building, right? So can we be using AI to create a role play partner? Can we be using AI to give personalized and highly nuanced feedback about complex subjects? Can we use AI to help us analyze? Those are generative. But can we use AI to help us analyze and create a taxonomy or an implied taxonomy of large course catalogs or large knowledge bases and to help us identify gaps or to match up where we may have holes in what our learning offerings are? We had that opportunity to build AI into every tool and product that we're building, whether it's a learning product, a performance support, the whole nine. After that. Well, at the same time, because we're getting new tools and everybody else is getting new tools, all of the work that people are doing in our organizations is ripe for AI transformation of some sort.

I mean, not all of it, but a lot of it, right? And so not only do we get these assistance, we have to provide learning opportunities for everybody else in the organization who are now getting new assistants to work with and new tools. So you change how claims processing is done. You change how my route gets scheduled when I have a, you know, powerful supply chain tool. Right. And then you have to teach people how to use it. So there's lots of work for instructional designers, learning designers, performance consultants in that space. And then, quite frankly, our leaders are dealing with so much change, so much rethinking of strategies, like in not, not just incremental strategy, but gigantic leaps ahead in strategy. So the leadership development that we offer needs to encompass this as well.

How we train and onboard people, how we create learning experiences and platforms, how we analyze what's going on. I mean, basically everything we do and everything we do it about is changing. And that is a huge opportunity for learning development professionals to be at the forefront.

Okay, so lots of different ways that AI is being used. Is this an opportunity for us as professionals, or could it also be maybe a little bit of a danger for us? I know we've heard that quote of, you know, or, you know, there's this fear out there that AI is going to be taking your job. And then we hear, you know, oh, it's not AI is taking your job, it's people who are using AI will take your job. All of that?

Yes. Yes, it is both. It will change the way we work. It will change the way the people around us at work. It will change the mix of our work, the types of roles we need, and how things get done. We may spend less time doing some things that, you know, the promise, but the promise is we spend less time doing rote boring things. Now, some of that rote boring stuff is the stuff of people's entire jobs, and that's what they're really good at. Right? And so there's going to be a lot of change, and I think that some of the resistance is just that fear of change, but there's also a certain amount of excitement in that we can do so many cool things.

And just like, I'm old enough to remember when cell phones came out, when PowerPoint came out, when, you know, email newsletters came out, right? All these, gosh, I feel old now anyways. But like, they changed the dynamic, right? The roles that were needed in the past, they were not necessarily needed now going forward, everybody now had access or a lot more people had access to do something that they didn't have access to do before because it required specialized tools, knowledge, right. And money. And for a while, or maybe still, there's a whole lot of junk that gets created, right? All of a sudden, right? There's, if everybody can make a PowerPoint deck, then everybody can. But not everybody makes a great PowerPoint deck, but there's no stopping you. So there's a lot of, you know, we'll see these cycles, I think, and this isn't going to be any different. It may feel like it's moving faster, but it will cause a lot of change. So the question then becomes, right, if it's here, it's not even, it's coming, it's here.

It's already transforming the way we work, the possibilities that are available to us, the kinds of things that we can do. One of the things that we're doing within TorrenceLearning, thinking a lot about how best to use it, where are appropriate places to use it and not to use it. How do we protect our clients and our people's data and our learner's data as we're using AI, and how do we support people in being a part of that kind of organization? It's transform right now. It is already transforming how just even our small boutique company operates, right. And we want to make sure that we just don't open up the tools and say, here you go, everybody. Have a good time. And instead creating those structures and those supports we have the WISE AT AI framework really looking at so WISE is wisdom and inclusiveness and safe and secure, equitable, accountable, transparent use of artificial intelligence. And that framework really looks at all of the ways in which we use AI, but it's not enough just to have an ethical framework.

And here's a tool, everybody. So we're starting with our AI driver's license. How do you get up to speed? What are the kinds of things that you do when you are well supported? It's like teaching your kids to drive, right? You're well supported with your family, you go to class, you get hours and hours of practice and support. New situations come up like all this, you know, you're learning to drive in the summertime, and then, you know, up north it's cold and then it snows and, oh my gosh, it's like you have to learn how to drive all over again, right? And so we'll have that kind of onboarding experience at the same time giving the keys to everybody and saying, let's do this together because you're going to go more fun places than any one of us could go alone.

Okay. How'd that go?

Okay. That was super hard because there's so much to talk about and I know there'll be other times, and I just kind of risk rambling because it's exciting and fun.

Yeah. This is Meg Fairchild and Megan Torrance, and this has been a podcast from TorranceLearning. Tangents is the official podcast of TorranceLearning, as though we have an unofficial one. Tangents is hosted by Meg Fairchild and Megan Torrance. It's produced by Dean Castile and Meg Fairchild, engineered and edited by Dean Castile with original music also by Dean Castile. This episode was fact checked by Meg Fairchild.