Artificial Intelligence in Talent Development

We’ve been hearing so much about artificial intelligence (in the news and in movies) for years and we’ve heard some theories on how it might impact the learning and development world. This week on Train Like You Listen, Brian talks with Margie Meacham of learningtogo.info, who digs into the myths and realities of AI and begins to paint a picture of what the intersection between AI and learning might be.

Transcript of the Conversation with Margie Meacham

Brian Washburn: Welcome, everyone, to another episode of Train Like You Listen, a podcast that happens weekly on all things learning and development, in bite-sized chunks. I’m Brian Washburn, Co-Founder and CEO of Endurance Learning. Just a reminder, Train Like You Listen is brought to you by Soapbox, the world’s first and only rapid authoring tool for instructor-led design. It is like Instant Pot for training design. Just add a few ingredients, how much time, number of participants, learning objectives, and put it all in there, set it for about five seconds, and then you have a lesson plan that gets generated.

We are here today with Margie Meacham, who is the CFO, the Chief Freedom Officer, of learningtogo.info. And we’re going to be talking about the idea of artificial intelligence in talent development. Margie, thank you so much for joining us today.

Margie Meacham: Thank you for having me. I’m really excited to be talking with you, Brian.

6-Word Introduction

Brian Washburn: Well, I’m excited here too. And the reason I’m excited is because this is a really interesting topic. Before we get into the topic, though, we like to introduce our guests with a six-word biography. And so with today’s topic about artificial intelligence and talent development, when I think of this, and if I had to sum up my own career in six words on this topic, I would say, “I welcome our new computer overlords”. How about you, Margie? How would you introduce yourself with this topic?

Margie Meacham: With AI in mind, I say, “I enhance learning through science”.

Brian Washburn: Yeah, it’s a really interesting topic. Before we go too far, though, I want to make sure that we kind of level set for everybody. Because different people, when they think of AI, think of different things. So can you define artificial intelligence and maybe give an example or two so that we can make sure that everyone has the same concept in mind as they’re listening to this conversation?

What is Artificial Intelligence? What Are Some Practical Applications of AI?

Margie Meacham: Absolutely. And in the book I go into more detail because the people actually working in the field are debating how to define it. One thing, it’s kind of easier to say what it isn’t, a lot of times. So for example, it’s not what you’ve seen in the sci-fi movies and Star Trek. We don’t have Commander Data walking around yet. That, the idea of a true sentient being that’s all been created through artificial means is what we call general intelligence, meaning it mostly thinks and acts and behaves like a human being. We’re nowhere near that.

So when we talk about practical applications of artificial intelligence, we’re talking about automating specific tasks that require some degree of judgment and decision-making, and building an application, a software program or an algorithm, that can do that without human intervention. And even that isn’t quite true because the humans did intervene at the beginning when they designed it and trained it. But after that, it should be able to run on its own.

So some examples are, if you need customer service and you go on a site and you’re, say, checking an order from Amazon, and a little bot pops up and says, “can I help you?”, “do you have a question?”, and you start typing in questions, that response you’re getting has already been programmed. There’s not a human being sitting there looking up your order. The bot asks you for your order number, and let me check, and let me tell you when it’s coming. Ultimately, it will refer you to a human being, only if it can’t satisfy your inquiry. So all kinds of banks, financial services, and online shopping sites use this kind of learning.

Brian Washburn: And you referenced your book. And just so that everyone knows, the book is titled AI in Talent Development. And it is available on Amazon. You can go to the ATD website as well to get it. And Margie, in your book, you write that AI and talent development have actually already converged. But it’s taken some time for people in our profession, in this talent development world, to recognize this fact. What do you mean by that?

How Have Artificial Intelligence and Talent Development Converged?

Margie Meacham: Well, I think I can actually relate it to my own personal experience. Because until I started researching for the book about a year and a half ago, I didn’t realize how much a part of our lives artificial intelligence already is. So if you’re talking to Siri, you’re using some kind of a digital assistant on your phone, whether it’s Siri, Alexa, Cortana, OK Google, if you’re using any of those, you are engaging on a regular basis with artificial intelligence.

So it’s not much of a leap to think of how that might be a learning application, so that you could ask a question about a product that you didn’t know. Or “hey, can you recommend some training for me?” Or “I’d like to practice my presentation for tomorrow, can you help me?” While it’s not much of a leap logically, the truth is that we’re not seeing as many of those applications in our industry, in our profession as learning professionals, as we are in a whole lot of other parts of our lives.

And that’s, I guess, what really surprised me, is that the technology’s there, the examples are actually live in the world all around us. And yet examples in L&D and in talent development are relatively few and mostly limited to very large organizations, like the US military, for example, which is heavily invested in artificial intelligence in a lot of their uses, and other very, very large corporations. But for the average learner experience, the examples are few and far between, at least in corporate learning.

Brian Washburn: Now, one reason– and I’ve been a training director at several organizations. They’ve been nonprofits. But I think it is similar for other smaller organizations, where they’ll say, “I’m part of the learning and development team. We don’t have a ton of money in our budget”. Are there actually cost-efficient, low-hanging fruit types of AI that people in the field of learning development, instructional designers, for example, can and should be taking advantage of as they build out learning programs?

More Affordable Ways to Apply Artificial Intelligence In Learning Programs

Margie Meacham: Yeah, absolutely. Two of the easiest ways to enter would be the chatbot and just-in-time performance support. So the chatbot, that’s similar to the experience I was talking about before. It doesn’t have to have a little character, but usually does. Usually, you just type the engagement, but you could also speak it. It’s just slightly —

Brian Washburn: Like Clippy. Like Clippy from Microsoft Word.

Margie Meacham: Yeah, like the original Clippy. Absolutely, way ahead of its time. And a lot of people didn’t– I was enchanted by Clippy. And I just loved the little animation. But a lot of people thought it was a big waste of time.

But it’s that idea. So, for example, you mentioned an LMS. Most organizations have way more content than learners are aware of or are using. And so what a little simple chatbot,  which you can even build them for free. There’s lots of free applications out there. And some of them have special pricing for the education market, for teachers and trainers, because they know we have limited budgets. And they also know we’ll be incredibly loyal if they give us access to their platforms.

You can build that conversation so that the bot draws from, say, data you have in your system about a job title and the role of that job and the performance metrics and maybe how long the person’s been in the job, and can match that against courses that are recommended, and have that sort of guidance counselor discussion, if you will, with the employee, and make it less intimidating to go searching for courses on your own. And maybe find things that aren’t really appropriate or aren’t– like sometimes course titles, I don’t know if you’ve noticed this, they’re wildly disconnected from the actual content. So it can help make sense of all that.

Now, of course, you have to spend the time to link those connections for the bot. But you build it once, and it can handle as many users as necessary all day long, all night long, all the time. So you get this always-on resource. It’s particularly great for global organizations, where you can’t staff for all those needs. But you can be immediately responsive. And the more you use it, the better it gets.

Now, the other beautiful thing about that is the reporting on the back end. So then you can run a report that says, “hey, we’ve got a large percentage searching for a skill we really don’t have treated in our LMS”. Now you know you need to go out and develop that because people are looking for it.

Brian Washburn: Now, do you have a few tools off the top of your head that you could recommend to those people who are like, “ooh, I’m interested, I’m interested, but where do I find these tools?”

Margie Meacham: Ah. Well, you know what? I keep a list, and it changes because there are so many coming and going. So the best thing to do is make sure people have my email address, [email protected], and I’ll be happy to send you my latest one. And then if you have some questions, I’ll be happy to answer a few of them.

Basically, what I recommend is, sign up for a couple of those free services and play with them. Because you’re going to find some interfaces just work better for you, just the way your brain works. They might really all be more or less equally good. But one is really going to feel better for you. And that’s the one you should start with.

Brian Washburn: Now, you mentioned Officer Data from Star Trek. For those of us who are into sci-fi, Data is a great example of artificial intelligence. And there’s also a dark side. There’s an ominous side, whether it’s “2001: A Space Odyssey”, or “The Terminator”, or even Marvel’s “The Age of Ultron”. The idea of AI can be a scary thing. So what are some of the real dangers that people need to keep in mind as they begin to incorporate AI into their learning and talent development programs?

What Dangers Should You Keep In Mind When Incorporating Artificial Intelligence into Your L&D Program?

Margie Meacham: You know, you’re absolutely right. It can be a scary thing, and it should be. Because once you give that power to that program, it’s going to make decisions, by its very nature, without human intervention. And that’s where the big risk is. Its unintended consequences.

So what is now becoming a classic case is that a very large company decided they would remove bias from their hiring process by building a program to select resumes instead of individuals, who came with their own preconceived ideas and could tell by looking at a resume if it was a male or female applicant, or at least a pretty good guess. And they thought, “oh, this is really going to solve it. This is brilliant.”

But they made a mistake in how they trained that bot. They took historical records of people who did well in that job and took their resumes and used that to teach the bot what to look for. Well, those historical successful candidates were, of course, part of the old biased system. So why did they just do? They just taught their bot to replicate those biases.

Brian Washburn: How to be biased. (LAUGHING)

Margie Meacham: Exactly. Now, to their credit, they recognized that pretty early on in the experiment and they discontinued it and went back to the drawing board. 

Another really famous example is, a teenage persona, was supposed to be a teenage girl, was unleashed on social media. And within hours, she became racist and was spouting all these horrible things. They had to take her down.

Well, it’s because, again, they taught her by going online and searching through social media. And sadly– you know, it’s like our children. Our bots do what we do. And that’s the greatest risk is you need to be very, very careful with the example you’re setting for your bot.

Brian Washburn: Absolutely. So Margie, it is a brave new world in this world of talent development. Thank you so much for answering a few questions about AI and talent development. 

Get to Know Margie Meacham

Brian Washburn: Before we leave, I do have a few speed round questions I’d love to ask you, just so that our folks get to know a little bit more. And so the first question that I have is, as you do a presentation, as you get ready to do a presentation, what is your go-to food or snack right before you give a presentation?

Margie Meacham: If it’s in the morning, I make some toast with peanut butter on it. If it’s in the afternoon or evening, it’s pizza.

Brian Washburn: I like it. I like that style. What’s a piece of training technology that you cannot live without?

Margie Meacham: Smartsheet. And a lot of people might not think of that as training technology. But for me, it keeps everything organized. I can always access it. I can attach files. I use a bunch of their project management templates and their content information. So it replaces– it does the work of multiple applications for me. And I think it’s well worth the investment.

Brian Washburn: Nice– smarter not harder. What should people be listening to today or reading as they think about– where else can I find some really smart information?

Margie Meacham: Well, one of the risks with any field that is so rapidly changing, is nearly every book is out of date within a year of publication. You know, if you don’t keep those books up to date, that’s what happens. So what I like to do is I like to recommend that people stay on top through websites and news feeds and those kinds of things.

And I find two things– the ZDNet news feed, which is kind of all things IT. And if you don’t think of yourself as being in the IT profession, you’re working in any field of talent development, you need to reframe your image of what you do. Because we are all IT workers. We could not do what we do without technology. And that’s going to be more and more the case, even for classroom-led training. We are STEM workers, and so we all need to embrace that. So I think that’s a great place to look.

The other thing is, it’s called the TOPBOTS newsletter, which is all AI all the time. And if you like, I can also provide a link to that so you can put it up with this podcast.

Brian Washburn: Excellent. That would be great. And then speaking of links, final question, do you have any shameless plug for us before we leave here?

Margie Meacham: Oh, yes, I have a few. So first of all, you did mention my new book, which is from ATD Press, very proud of that. You can find it on Amazon. And that’s AI in Talent Development. I’m told it’s a nice quick read. And that’s really what I try to do, is make sense of very technical things. My first book is still doing really well. And that’s called Brain Matters: How to Help Anyone Learn Anything Using Neuroscience, also on Amazon.

Those two, kind of, show you the intersection of my thought process and where my career’s gone. Because I started focusing on neuroscience and how our brains work, and I couldn’t help but notice that the work we’re doing in artificial brains is very closely aligned and starting to overlap. So those two fields are converging, which means we really need to pay attention to it as learning professionals. And you can learn more about me at learningtogo.info. I think those are enough shameless plugs for one day, Brian.

Brian Washburn: Well, thank you so much, Margie Meacham for joining us– Margie Meacham, the Chief Freedom Officer at learningtogo.info. Thank you, everyone else, for listening to another episode of Train Like You Listen, a weekly podcast, which you can find on Spotify, on Apple, on iHeartRadio or wherever you get your podcasts. And if you like what you hear, go ahead and give us a rating, because that’s how other people find out about us. Until next week, happy training, everyone.